


技术领域technical field
本发明涉及智能看护技术领域,尤其涉及一种脑卒中偏瘫患者用离床预警系统。The invention relates to the technical field of intelligent nursing, in particular to an early warning system for getting out of bed for hemiplegic patients with cerebral apoplexy.
背景技术Background technique
脑卒中又称脑血管意外(Cerebral Vascular Accident,CVA),是一种因脑动脉系统病变引起的血管痉挛、闭塞或破裂,造成急性发展的脑局部循环障碍和以偏瘫为主的肢体功能障碍,包括缺血性卒中(Ischemic Stroke)和出血性卒中(Hemorrhagic Stroke)两类。脑卒中作为一类常见的神经系统疾病,因其发病率、死亡率、复发率和致残率均较高,已经成为严重威胁居民生命健康和生活质量的重大疾病。糖尿病是缺血性脑卒中的独立危险因素,长期高血糖增加中风风险,糖尿病患者中风发病率是正常人的四倍,高血糖通过多种途径损伤脑血管导致动脉粥样硬化,影响血管壁弹性和硬度,出现血管内膜斑块形成、狭窄、闭塞等病理改变,由于血脂异常、高血压、动脉粥样硬化、血液黏稠度增高等并发症导致心脏、大脑及全身组织受损,发生缺血性或出血性症状。Stroke, also known as Cerebral Vascular Accident (CVA), is a kind of vasospasm, occlusion or rupture caused by lesions of the cerebral arterial system, resulting in acute development of cerebral circulatory disorder and limb dysfunction mainly with hemiplegia. Including ischemic stroke (Ischemic Stroke) and hemorrhagic stroke (Hemorrhagic Stroke) two categories. As a common neurological disease, stroke has become a major disease that seriously threatens residents' life, health and quality of life because of its high morbidity, mortality, recurrence and disability rates. Diabetes is an independent risk factor for ischemic stroke. Long-term hyperglycemia increases the risk of stroke. The incidence of stroke in diabetic patients is four times that of normal people. Hyperglycemia damages cerebral blood vessels through various pathways, leading to atherosclerosis and affecting the elasticity of blood vessel walls. Due to complications such as dyslipidemia, hypertension, atherosclerosis, and increased blood viscosity, the heart, brain and systemic tissues are damaged and ischemia occurs. Sexual or bleeding symptoms.
脑卒中会造成上运动神经元的损伤,常常导致中枢性的瘫痪,造成肢体的功能障碍,包括阳性症状与阴性症状。其中的阴性症状有以下几个方面:肌力的下降、运动控制能力的降低及肢体协调性的下降等;而阳性症状包括反射亢进、痉挛程度的增加等。此外还有一些特殊的运动协调障碍模式:如共同收缩、异常协同运动等。而脑中风偏瘫后的异常协同运动模式已经成为了上肢运动功能障碍的典型特征,这些异常的运动模式阻碍了正常运动模式的完成,对患者的日常生活活动性能造成了非常严重的影响。据全国第三次国民死因调查统计,国内第一大死亡原因是脑卒中,幸存者75%以上留有不同程度的后遗症,其中40%为重度残疾,包括肢体、语言、认知等方面的障碍,常见且对患者影响最大的是运动功能障碍,尤以偏瘫最常见。70%以上的患者不同程度的丧失生活及工作能力,严重影响了患者的日常生活活动(Activitiesof Daily Living,ADL)能力。据相关研究显示,脑卒中患者在急性治疗期、康复治疗阶段、返回社区生活中有过跌倒的比率分别为14%~64.5%、24%~47%和37.5%~73%,跌倒已成为脑卒中患者的一种发生率极高的主要并发症。Stroke can cause damage to upper motor neurons, often leading to central paralysis, resulting in limb dysfunction, including positive symptoms and negative symptoms. The negative symptoms include the following aspects: decreased muscle strength, decreased motor control, and decreased limb coordination; while positive symptoms include hyperreflexia and increased spasticity. In addition, there are some special motor coordination disorder patterns: such as co-contraction, abnormal coordinated movement and so on. The abnormal coordinated movement patterns after cerebral apoplexy hemiplegia has become a typical feature of upper limb motor dysfunction. These abnormal movement patterns hinder the completion of normal movement patterns, and have a very serious impact on the patients' activities of daily living. According to the National Third National Cause of Death Survey, the largest cause of death in China is stroke. More than 75% of the survivors have sequelae of varying degrees, of which 40% are severely disabled, including physical, language, cognitive and other obstacles. , The most common and most affecting patient is motor dysfunction, especially hemiplegia is the most common. More than 70% of patients lose their ability to live and work to varying degrees, which seriously affects their ability to perform activities of daily living (ADL). According to relevant studies, the rates of stroke patients who have fallen during acute treatment, rehabilitation treatment, and returning to community life are 14% to 64.5%, 24% to 47%, and 37.5% to 73%, respectively. A major complication with a very high incidence in stroke patients.
跌倒是指出现突然发生的、不自主的、非故意的体位改变而倒在地上或更低的平面上。跌倒会造成脑部损伤、软组织损伤、骨折和脱臼甚至死亡等伤害,尤其对脑卒中患者,跌倒及其后果会给患者及家属造成巨大的身心伤害,严重影响患者及家属的生活质量,对跌倒的恐惧造成部分患者减少活动或其家属限制患者活动,结果导致患者自理能力下降。同时跌倒也导致患者住院费用及住院时间增加,给家庭和社会带来巨大负担。为了有效预防脑卒中患者跌倒的发生,目前常用的方法为采用量表对患者进行评估,筛选易跌倒高危人群,采取保证患者居住的环境安全、加强患者及家属防跌倒知识健康宣教、床头挂警示牌等统一措施预防患者跌倒,但以上措施缺乏针对性,目前尚无现有技术提出针对脑卒中偏瘫患者进行离床跌倒风险预防及干预的护理装置。因此,到目前为止,跌倒尤其是针对脑卒中偏瘫患者的离床跌倒风险仍然是困扰医护人员的主要问题之一。A fall is a sudden, involuntary, unintentional change in body position that results in a fall to the ground or a lower level. Falls can cause brain damage, soft tissue damage, fractures and dislocations and even death, especially for stroke patients. Falls and their consequences can cause huge physical and mental harm to patients and their families, seriously affecting the quality of life of patients and their families. The fear of the disease caused some patients to reduce their activities or their family members to limit the patient's activities, resulting in a decline in the patient's self-care ability. At the same time, falls also lead to increased hospitalization costs and length of stay for patients, bringing a huge burden to families and society. In order to effectively prevent the occurrence of falls in stroke patients, the current commonly used methods are to use scales to evaluate patients, screen high-risk groups who are prone to falls, take measures to ensure the safety of the living environment for patients, strengthen the knowledge of patients and their families to prevent falls, health education, bedside hanging There are unified measures such as warning signs to prevent patients from falling, but the above measures are lacking in pertinence. At present, there is no existing technology that proposes a nursing device for the prevention and intervention of the risk of falling out of bed for patients with stroke and hemiplegia. Therefore, so far, the risk of falling out of bed, especially for stroke patients with hemiplegia, is still one of the main problems perplexing medical staff.
如授权公开日为2019年5月21日的授权公告号为CN208876548U的专利文献所提出的一种看护系统,包括:睡眠监测器、信号转发器、服务器及终端设备,睡眠监测器与信号转发器连接,信号转发器与服务器连接,服务器与终端设备连接;睡眠监测器采集用户的微动信号,并将微动信号发送至信号转发器;信号转发器将微动信号发送至服务器;服务器接收微动信号,并根据微动信号得到生理特征信号,服务器根据生理特征信号得到用户的睡眠信息及活动信息,并将睡眠信息及活动信息发送至终端设备,活动信息包括:用户在床或离床,睡眠信息包括:用户的睡眠状态及用户的睡眠质量。该看护系统根据用户的生理特征信号获取得到用户的睡眠信息及活动信息,从而实现看护的智能化,有效的增加看护力度。For example, a nursing system proposed in the patent document with the authorization announcement number CN208876548U on May 21, 2019, includes: a sleep monitor, a signal transponder, a server and terminal equipment, a sleep monitor and a signal transponder Connection, the signal transponder is connected to the server, and the server is connected to the terminal device; the sleep monitor collects the user's micro-motion signal and sends the micro-motion signal to the signal transponder; the signal transponder sends the micro-motion signal to the server; the server receives the micro-motion signal. The server obtains the user's sleep information and activity information according to the physiological characteristic signal, and sends the sleep information and activity information to the terminal device. The activity information includes: the user is in or out of bed, The sleep information includes: the user's sleep state and the user's sleep quality. The nursing system obtains the sleep information and activity information of the user according to the physiological characteristic signal of the user, thereby realizing the intelligentization of nursing and effectively increasing the nursing intensity.
又如公开日为2020年2月28日的公开号为CN110853299A的专利文献所提出的一种儿童防掉床和离床检测报警装置,在床的一侧设置床栏(1),还包括安装在床头一侧的光电发射管LED1(2),安装在床头另一侧的光电接收管V1(3),光电接收管V1用来接收光电发射管LED1的发射信号,在床头的另一侧安装无线发射器(4),与无线发射器对应的无线接收器安装在儿童身上,在床下安装红外传感器IRX(5),还包括与光电发射管LED1、光电接收管V1、无线发射器、红外传感器IRX连接的外围电路;其所设置的报警装置能够时刻对儿童的睡觉状态进行监控,当儿童不慎掉床或是离床时,能够发出警报。Another example is a child anti-falling bed and bed-leaving detection and alarm device proposed in the patent document with the publication date of February 28, 2020 and the publication number CN110853299A, a bed rail (1) is provided on one side of the bed, and also includes installation The phototransmitting tube LED1(2) on one side of the bedside, the photoelectric receiving tube V1(3) installed on the other side of the bedside, the photoelectric receiving tube V1 is used to receive the emission signal of the photoelectric transmitting tube LED1, and the photoelectric receiving tube V1 is used to receive the emission signal of the photoelectric transmitting tube LED1, and the photoelectric receiving tube V1(3) is installed on the other side of the bedside. A wireless transmitter (4) is installed on one side, the wireless receiver corresponding to the wireless transmitter is installed on the child, an infrared sensor IRX (5) is installed under the bed, and the photoelectric transmitting tube LED1, the photoelectric receiving tube V1, and the wireless transmitter are also installed. , The peripheral circuit connected to the infrared sensor IRX; the alarm device set up can monitor the sleeping state of the child at all times, and can issue an alarm when the child accidentally falls off the bed or leaves the bed.
针对上述专利文献所存在的预警性差的问题,如下现有技术提出了具有较好预警性的技术方案:Aiming at the problem of poor early warning in the above-mentioned patent documents, the following prior art proposes a technical solution with good early warning:
例如授权公告日为2016年8月31日的授权公告号为CN103824418B的专利文献所提出的一种离床监护的报警系统,该离床监护的报警系统包括两个压电薄膜传感器、处理器以及报警器。两个压电薄膜传感器沿床的长边延伸方向依次铺设在床上,并同步连续采集来自床上的压力信号。处理器根据两个压力信号分别形成床上人体的两个周期性生理特征信号,并在两个周期性生理特征信号同步中断时,判断人体摔落离床,而在两个周期性生理特征信号前后中断时,判断人体先是坐起再起身自行离床。报警器在摔落离床时发出报警提示。其报警系统能及时发现人体摔落离床,便于做出迅速的补救措施。该专利文献还涉及安装有该离床监护的报警系统的床、与该离床监护的报警系统配套使用的离床监护的报警装置及其报警方法。For example, the patent document with the authorization announcement date of August 31, 2016 and the authorization announcement number CN103824418B proposes an alarm system for bed-leaving monitoring. The bed-leaving monitoring alarm system includes two piezoelectric film sensors, a processor and a Alarm system. Two piezoelectric thin-film sensors are sequentially laid on the bed along the extending direction of the long side of the bed, and synchronously and continuously collect pressure signals from the bed. The processor respectively forms two periodic physiological characteristic signals of the human body on the bed according to the two pressure signals, and when the two periodic physiological characteristic signals are interrupted synchronously, determines that the human body falls off the bed, and when the two periodic physiological characteristic signals are interrupted synchronously, the processor determines that the human body falls off the bed. When it is interrupted, it is judged that the human body first sits up and then gets up to get out of the bed on its own. The alarm sounds when you fall off the bed. Its alarm system can detect the human body falling off the bed in time, which is convenient for making quick remedial measures. The patent document also relates to a bed equipped with the alarm system for out-of-bed monitoring, an alarm device for out-of-bed monitoring used in conjunction with the alarm system for out-of-bed monitoring, and an alarm method thereof.
现有的如上述专利文献所提出的离床报警装置要实现离床报警的功能,必须是在被监护对象的行动能力非常好的基础上才能实现,因为其装置判断人体是否自行离床得先判断人体是否直立坐起身,从仰卧姿势直接转换为坐姿的过程对被监护对象的腹部力量要求非常大,该动作对于行动不便的例如脑卒中偏瘫患者此类人群而言是不可能完成的动作,因而上述装置无法适用于行动不便的例如脑卒中偏瘫患者此类人群的离床报警,只会增大误警率。The existing bed-leaving alarm device as proposed in the above-mentioned patent documents needs to realize the function of bed-leaving alarm, which must be realized on the basis of the very good mobility of the monitored object, because the device judges whether the human body gets out of bed on its own first. The process of judging whether the human body is sitting upright or not, and the process of directly converting from a supine position to a sitting position requires a lot of abdominal strength of the monitored object. This action is impossible for people with inconvenience such as stroke and hemiplegia. Therefore, the above-mentioned device cannot be applied to the out-of-bed alarm for people with inconvenient mobility, such as stroke hemiplegia patients, and will only increase the false alarm rate.
又例如公开日为2019年5月17日的公开号为CN109757928A的专利文献所提出的一种防摔智能婴儿床,至少包括婴儿床本体和与婴儿床本体固接的婴儿床床架,防摔智能婴儿床还包括婴儿翻越检测模块、若干个手部行为检测模块和若干个脚部行为检测模块。在至少一个特定事件发生之时,通过若干个脚部行为检测模块中的至少一个和若干个手部行为检测模块中的至少一个获取并记录该特定事件发生之时防摔智能婴儿床的压力变化信息,并且基于接收到的压力变化信息进行婴儿翻越预估分析并输出与之匹配的婴儿翻越预估结果和/或婴儿翻越风险等级至中央处理模块,中央处理模块基于接收到的婴儿翻越预估结果和/或婴儿翻越风险等级向由监护人操作的智能终端发出预警提示和/或通过声光提示模块发出第一声光信息。Another example is a kind of anti-falling smart crib proposed by the patent document with the publication date of May 17, 2019 and the publication number CN109757928A, which at least includes a crib body and a crib bed frame fixed to the crib body, which is anti-falling. The smart crib also includes a baby jumping detection module, several hand behavior detection modules and several foot behavior detection modules. When at least one specific event occurs, at least one of several foot behavior detection modules and at least one of several hand behavior detection modules acquire and record the pressure change of the anti-fall smart crib when the specific event occurs information, and based on the received pressure change information, carry out an infant leaping prediction analysis and output the matching infant leaping prediction result and/or infant leaping risk level to the central processing module, and the central processing module is based on the received infant leaping prediction. As a result, and/or the baby has passed the risk level, an early warning prompt is sent to the intelligent terminal operated by the guardian and/or the first sound and light information is sent out through the sound and light prompt module.
而诸如上述专利文献所提出的离床报警装置,其利用用户手部、脚部分别与床体上设置的分区域的压力传感器之间进行交互的动作过程,能够提供较好的预警作用,但其面向的对象也只能局限于离床之前还需要翻越床架的婴幼儿,同样地无法适用于行动不便的注入高龄患者术后、膝关节或髋关节置换的患者、术后因贫血或比较虚弱的患者或是脑卒中偏瘫患者,其不听医护人员劝告,擅自下床,也不叫家属陪同,导致意外自行离床或是坠床事件的发生。However, such as the bed exit alarm device proposed in the above-mentioned patent documents, it utilizes the interaction process between the user's hands and feet and the pressure sensors in the sub-regions provided on the bed body, which can provide a better early warning effect, but It can only be aimed at infants and young children who need to climb over the bed frame before getting out of bed. It is also not suitable for injection into elderly patients with inconvenience after surgery, patients with knee or hip joint replacements, patients due to anemia or comparisons after surgery. Weak patients or stroke hemiplegia patients do not listen to the advice of medical staff, get out of bed without permission, and do not ask their family members to accompany them, resulting in accidental getting out of bed or falling out of bed.
针对上述现有技术文献虽然具有较好预警性但适用范围局限性太大的问题,现有技术提出了否弃行为监测范围有限的非接触式监测设备(诸如上述所列举的设置有多个传感器的床垫),转而采用行为监测能力更好的佩戴式监测设备的技术方案,例如:Aiming at the problem that the above-mentioned prior art documents have good early warning, but the scope of application is too limited, the prior art proposes non-contact monitoring equipment (such as the ones listed above, which are provided with a plurality of sensors) with a limited range of monitoring of abandonment behavior. mattresses), and switch to technical solutions of wearable monitoring devices with better behavioral monitoring capabilities, such as:
公开日为2019年7月5日的公开号为CN109966088A的专利文献所提出的一种临床预警系统,其包括电子标签、标签读取模块、病房路由终端、云平台、监护终端和护士站终端;电子标签,包括有设置于患者脚部的脚环,脚环内设有RFID电子标签;标签读取模块,设置于床体下方,包括有屏蔽罩,屏蔽罩上设有朝向床侧方的开口,屏蔽罩内设有用于对RFID电子标签进行无线读取的读取单元。与现有技术相比,该临床预警系统中在处于病床下方的标签读取模块读取到电子标签时,表示患者下床,由病房路由终端传输给云平台,云平台对信息进行处理,分别传输给陪护终端和护士站终端,这样实时监测脚环离床距离,并实时预警跌落风险,及时向陪护人员和护士站发出预警信息。A clinical early warning system proposed by the patent document with the publication date of July 5, 2019, whose publication number is CN109966088A, includes an electronic label, a label reading module, a ward routing terminal, a cloud platform, a monitoring terminal and a nurse station terminal; The electronic label includes a foot ring arranged on the patient's foot, and an RFID electronic label is arranged in the foot ring; the label reading module is arranged under the bed body and includes a shielding cover, and the shielding cover is provided with an opening facing the side of the bed , a reading unit for wirelessly reading the RFID electronic tag is arranged in the shielding cover. Compared with the prior art, in the clinical early warning system, when the electronic label is read by the label reading module under the hospital bed, it means that the patient gets out of bed, and the ward routing terminal transmits it to the cloud platform, and the cloud platform processes the information, respectively. It is transmitted to the escort terminal and the nurse station terminal, so that the distance between the foot ring and the bed can be monitored in real time, and the risk of falling can be warned in real time, and early warning information can be sent to the escort personnel and the nurse station in time.
此类技术方案未考虑实际应用时,被监护对象可能仅仅是将脚部伸出床体外沿就引起了该装置的警报,然而实际上被监护对象并完全没有下床也更没有要自行下床的趋势。When this kind of technical solution does not consider the practical application, the supervised object may just put his feet out of the outer edge of the bed to cause the alarm of the device, but in fact, the supervised object does not get out of bed at all, nor does he want to get out of bed by himself. the trend of.
此外,一方面由于对本领域技术人员的理解存在差异;另一方面由于发明人做出本发明时研究了大量文献和专利,但篇幅所限并未详细罗列所有的细节与内容,然而这绝非本发明不具备这些现有技术的特征,相反本发明已经具备现有技术的所有特征,而且申请人保留在背景技术中增加相关现有技术之权利。In addition, on the one hand, there are differences in the understanding of those skilled in the art; on the other hand, because the inventor has studied a large number of documents and patents when making the present invention, but the space limit does not list all the details and contents in detail, but this is by no means The present invention does not possess the features of the prior art, on the contrary, the present invention already possesses all the features of the prior art, and the applicant reserves the right to add relevant prior art to the background art.
发明内容SUMMARY OF THE INVENTION
本发明提出了一种脑卒中偏瘫患者用离床预警系统,尤其是指适用于同一侧上下肢均存在运动功能障碍的且区别有患侧上下肢与健侧上下肢的被监护对象的离床预警系统。The invention provides an early warning system for getting out of bed for stroke hemiplegia patients, in particular, it is suitable for getting out of bed of a supervised object who has motor dysfunction on the same side of the upper and lower limbs and distinguishes between the upper and lower limbs of the affected side and the upper and lower limbs of the healthy side. early warning system.
本发明的离床预警系统是针对现有技术中为实现离床报警功能所提出的离床报警装置所存在的不足而提出的,现有技术之不足在于:针对具有高发生率及高危害性的跌倒问题尤其是针对脑卒中单侧偏瘫患者的自行离床跌倒问题,现有技术中为实现离床报警功能所提出的离床报警装置大致可分为基于非接触式监测设备或佩戴式监测设备的解决方案。其一,就现有技术中如授权公告号为CN103824418B的专利文献所提出的基于非接触式监测设备如智能床垫所提出的解决方案而言,此类解决方案对人体是否自行离床的判断,等同于判断人体是否直立坐起身,实际上,直立坐起身的动作需从仰躺姿势直接转换为坐姿,该过程对被监护对象的腹部力量要求非常大。因此此类解决方案中离床报警功能的实现,是建立在被监护对象的行动能力非常好的基础上的,对于行动不便的例如脑卒中偏瘫患者此类人群而言,该动作是难度非常大甚至不可能完成的。因而此类解决方案无法适用于行动不便的例如脑卒中偏瘫患者此类人群的离床报警,只会增大误警率。其二,针对基于佩戴式监测设备的如公开号为CN109966088A的专利文献所提出的基于内设有RFID电子标签的脚环的解决方案,此类解决方案中离床报警功能的实现,是通过监测脚环是否移动出床体之外的区域来实现的,判定其只要脚环移动出床体即为离床并进行报警,然而,此类解决方案未考虑实际应用时,被监护对象可能仅仅是将脚部伸出床体外沿,而并非已经离床也更没有要自行离床的趋势,但该情况下仍会引起该装置的警报,误警率高,反而增大护理人员工作负担,同时由于其在活动度较高的脚部设置脚环,不仅佩戴时不适感强烈,而且监测目的非常明显,容易引起患者反感而自行摘除,无法监测到其是否擅自离床。尤其是针对如脑卒中单侧偏瘫患者的被监护对象,其患侧上下肢均存在运动功能障碍且肢体感觉受损严重,患者往往需要利用健侧的支撑作用才能移动患侧,对人工辅助护理的依赖程度以及行动受限的反感程度都非常高。The bed-leaving warning system of the present invention is proposed in view of the shortcomings of the bed-leaving alarm device proposed in the prior art for realizing the bed-leaving alarm function. The deficiencies of the prior art are: The problem of falling out of bed, especially for unilateral hemiplegia patients with cerebral apoplexy, falls out of bed on their own. In the prior art, the out-of-bed alarm device proposed for realizing the function of out-of-bed alarm can be roughly divided into two types based on non-contact monitoring equipment or wearable monitoring equipment. equipment solutions. First, as for the solutions proposed in the prior art based on non-contact monitoring equipment such as smart mattresses proposed in the patent document with the authorization announcement number CN103824418B, such solutions determine whether the human body gets out of bed by itself. , which is equivalent to judging whether the human body sits upright or not. In fact, the action of sitting upright needs to be directly converted from the supine position to the sitting position. This process requires a lot of abdominal strength of the supervised object. Therefore, the realization of the alarm function of getting out of bed in this type of solution is based on the very good mobility of the monitored object. For people with inconvenient mobility, such as stroke hemiplegia patients, this action is very difficult. Impossible even. Therefore, this kind of solution cannot be applied to the out-of-bed alarm for people with limited mobility, such as stroke hemiplegia patients, and will only increase the false alarm rate. Second, for the solution based on the foot ring with RFID electronic tag in the patent document with the publication number of CN109966088A based on wearable monitoring equipment, the realization of the alarm function of getting out of bed in this kind of solution is achieved by monitoring. It is realized by whether the foot ring moves out of the area outside the bed, and it is determined that as long as the foot ring moves out of the bed, it is to leave the bed and alarm. However, when this kind of solution does not consider the actual application, the monitored object may only be Extending the foot out of the outer edge of the bed does not mean that you have already left the bed, and there is no tendency to get out of the bed by yourself. However, in this case, the alarm of the device will still be caused, and the false alarm rate is high, which will increase the workload of the nursing staff. Due to the fact that the foot ring is set on the foot with high activity, it is not only uncomfortable when worn, but also the monitoring purpose is very obvious, which is easy to cause the patient to be disgusted and remove it by himself, and it is impossible to monitor whether he has left the bed without authorization. Especially for supervised subjects such as stroke patients with unilateral hemiplegia, their upper and lower limbs on the affected side have motor dysfunction and severe limb sensory impairment. Patients often need to use the support of the healthy side to move the affected side. The degree of dependence and the degree of aversion to restricted movement are very high.
以此,针对上述现有技术中离床报警装置之不足,本发明提出了脑卒中偏瘫患者用离床预警系统,所述系统包括:采集模块,其用于获取由仅佩戴于被监护对象的患侧上下肢的穿戴式设备所采集到的行为数据;风控等级划分模块,其用于根据被监护对象历史风控数据来确定与之对应的风控等级,其中,所述被监护对象尤其是指同一侧上下肢均存在运动功能障碍的且区别有患侧上下肢与健侧上下肢的人群,所述系统还包括:预警信息处理器,其被配置为至少基于由采集模块从佩戴于被监护对象的患侧上下肢的至少一个穿戴式设备所采集到的行为数据中所提取到的至少一个运动特征值之间的与由监护人员所操作的至少一个移动数字设备所确定的运动功能障碍评估结果所对应的阶段属性关联规则以及预设的风控等级来判断其行为数据是否触发预警。优选地,在触发预警时将预警信息传递至周边的由监护人员所携带的至少一个移动数字设备。Therefore, in view of the deficiencies of the bed-leaving alarm device in the above-mentioned prior art, the present invention proposes a bed-leaving warning system for stroke hemiplegia patients. The behavior data collected by the wearable devices of the upper and lower limbs on the affected side; the risk control level division module, which is used to determine the corresponding risk control level according to the historical risk control data of the monitored object, wherein the monitored object is especially Refers to people who have motor dysfunction on the same side of the upper and lower limbs and distinguish between the upper and lower limbs on the affected side and the upper and lower limbs on the unaffected side. The system further includes: an early warning information processor, which is configured to The movement function between at least one movement feature value extracted from the behavior data collected by at least one wearable device of the affected side upper and lower limbs of the monitored subject and at least one mobile digital device operated by the guardian The stage attribute association rule corresponding to the obstacle assessment result and the preset risk control level are used to judge whether its behavior data triggers an early warning. Preferably, when an early warning is triggered, the early warning information is transmitted to at least one mobile digital device carried by the guardian in the surrounding area.
本申请通过设置仅穿戴于存在运动功能障碍的一侧上下肢的穿戴式设备,由于患侧肢体感觉受损严重,感知能力低,对穿戴式设备的接受度更好,并且保留了健侧不受限的良好活动能力,同时患侧肢体活动程度较低,大大地降低了需要处理的数据量。基于此,本发明中预警信息处理器是在区别于不同患者的不同风险控制等级以及不同偏瘫单侧的运动功能障碍程度的基础上,限定出的用于指示预警危险度且彼此预警危险度不同的若干监测模式,从而预警信息处理器能够基于患者当前的行为数据与预设若干监测模式相比对,基于比对结果以及预设的患侧上下肢之间的阶段属性关联规则来判断是否需要预警,提高了在危险发生前就通知监护人员为被监护对象提供及时的看护或辅助的预警时效性。In the present application, by setting a wearable device that is only worn on the upper and lower limbs on the side with motor dysfunction, due to the severely damaged limbs on the affected side, the perception ability is low, the acceptance of the wearable device is better, and the unaffected side is preserved. Restricted good mobility, coupled with lower limb mobility on the affected side, greatly reduces the amount of data that needs to be processed. Based on this, the early warning information processor in the present invention is defined based on the different risk control levels of different patients and the degree of motor dysfunction of different unilateral hemiplegia, and is used to indicate the early warning risk and the early warning risks are different from each other. Several monitoring modes are set, so that the early warning information processor can compare the current behavior data of the patient with several preset monitoring modes, and judge whether it is necessary to Early warning improves the timeliness of early warning of notifying guardians to provide timely care or assistance for the supervised object before danger occurs.
根据一种优选实施方式,所述运动特征值至少包括由佩戴于被监护对象的患侧上肢的第一穿戴式设备所采集到的行为数据中的第一运动特征值,以及由佩戴于被监护对象的患侧下肢的第二穿戴式设备所采集到的行为数据的第二运动特征值,其中,所述采集模块中预存储有第一运动特征值与第二运动特征值之间的用于指示第一运动特征值与第二运动特征值所分别对应的运动特征变化趋势的阶段属性关联规则。According to a preferred embodiment, the motion feature value includes at least the first motion feature value in the behavior data collected by the first wearable device worn on the affected upper limb of the subject to be monitored, and the first motion feature value from the behavior data collected by the first wearable device worn on the affected upper limb of the monitored subject. The second motion feature value of the behavior data collected by the second wearable device of the affected lower limb of the subject, wherein the acquisition module pre-stores a value between the first motion feature value and the second motion feature value for A stage attribute association rule indicating the change trend of the motion feature corresponding to the first motion feature value and the second motion feature value respectively.
本发明中该离床预警系统基于穿戴式设备所采集到患侧上下肢的行为数据、以及由摆放姿势检测模块所分析确定的摆放姿势和/或姿势变化趋势,将其与行为规则模块中预设有的运动特征变化趋势进行比对,使得该系统能够适应于脑卒中偏瘫患者的卧床体位摆放的特殊性要求来对其卧床行为进行监测,并由预警信息处理器基于比对结果以及预设的患侧上下肢之间的阶段属性关联规则来判断是否需要预警,提高了在危险发生前就通知监护人员为被监护对象提供及时的看护或辅助的预警时效性。In the present invention, the bed-leaving early warning system is based on the behavior data of the upper and lower limbs on the affected side collected by the wearable device, and the posture and/or posture change trend analyzed and determined by the posture detection module, which is combined with the behavior rule module. The pre-set movement characteristics change trends in the system are compared, so that the system can adapt to the special requirements of stroke hemiplegia patients' bed rest position to monitor their bed rest behavior, and the early warning information processor is based on the comparison results. As well as the preset association rules of stage attributes between the upper and lower limbs of the affected side to determine whether an early warning is required, it improves the timeliness of early warning of notifying the guardians to provide timely care or assistance to the monitored object before danger occurs.
如下先统一列举本发明的离床预警系统所包括的多个模块:该系统包括用于采集被监护对象的行为数据的采集模块、用于确定风控等级的风控等级划分模块、用于判断触发预警的预警信息处理器、用于确定当前摆放姿势的摆放姿势检测模块、用于预设运动特征变化趋势的行为规则模块、佩戴于被监护对象患侧的穿戴式设备、由监护人员携带的移动数字设备以及内设有处理器和传感器的床垫。此外,床垫上布置有用于采集患者压力变化的压力传感器阵列以及与该压力传感器阵列相连接的处理器。在本发明中所提及的上述设备可以均为计算机处理器,图1示出脑卒中偏瘫患者用离床预警系统的简化逻辑流程图,所述逻辑流程图的操作表示可以硬件、计算机指令或其组合实现的一系列操作。在计算机指令的背景下,所述操作表示被存储在一个或多个计算机可读存储介质上的计算机可执行指令,所述计算机可执行指令在被一个或多个计算机处理器执行时执行所述的操作。一般而言,计算机可执行指令包括执行特定功能或实现特定数据类型的例程、程序、对象、部件、数据结构等。描述操作的顺序不旨在被解释为具有限制性,并且任何数目的所描述的操作可以任何顺序和/或并行地组合以实现所述过程。另外,模块之间的数据传输过程可以在配置有可执行指令的一个或多个计算机系统的控制下执行,并且可以被实现为代码(例如,可执行指令、一个或多个计算机程序或者一个或多个应用),所述代码在一个或多个计算机处理器上统一地执行,或者通过硬件实现,或者通过上述两者的组合来实现。代码可以被存储在计算机可读存储介质上,例如以计算机程序的形式,所述计算机程序包括可由一个或多个处理器执行的多个指令。计算机可读存储介质可以是非临时的。在一些实施例中,图1中模块之间的数据传输过程可存储在计算机处理器的存储器中,并计算机处理器执行。The multiple modules included in the bed-leaving early warning system of the present invention are firstly listed as follows: the system includes a collection module for collecting behavior data of a monitored object, a risk control level division module for determining the risk control level, and a An early warning information processor that triggers an early warning, a posture detection module for determining the current posture, a behavior rule module for presetting the trend of movement characteristics, a wearable device worn on the affected side of the monitored object, and a Portable mobile digital devices and mattresses with processors and sensors inside. In addition, the mattress is provided with a pressure sensor array for collecting changes in the patient's pressure and a processor connected to the pressure sensor array. The above-mentioned devices mentioned in the present invention may all be computer processors. FIG. 1 shows a simplified logic flow diagram of a bed-leaving warning system for stroke hemiplegia patients. The operation of the logic flow diagram indicates that hardware, computer instructions or A series of operations implemented by its combination. In the context of computer instructions, the operations represent computer-executable instructions stored on one or more computer-readable storage media that, when executed by one or more computer processors, perform the operation. Generally, computer-executable instructions include routines, programs, objects, components, data structures, etc. that perform particular functions or implement particular data types. The order in which the operations are described is not intended to be construed as limiting, and any number of the described operations may be combined in any order and/or in parallel to implement the process. Additionally, data transfer processes between modules may be performed under the control of one or more computer systems configured with executable instructions, and may be implemented as code (eg, executable instructions, one or more computer programs, or one or more multiple applications), the code is executed uniformly on one or more computer processors, either by hardware, or by a combination of both. The code may be stored on a computer-readable storage medium, eg, in the form of a computer program comprising a plurality of instructions executable by one or more processors. Computer-readable storage media may be non-transitory. In some embodiments, the data transfer process between the modules in FIG. 1 may be stored in the memory of the computer processor and executed by the computer processor.
所描述的特征可以数字电子电路、或以计算机硬件、固件、软件或其组合来实现。设备可以被实现在由可编程处理器执行的计算机程序产品中,所述计算机程序产品有形地体现在信息载体中,例如在机器可读存储装置中;并且方法步骤可以由可编程处理器来执行,所述可编程处理器执行指令程序以通过操作输入数据和产生输出来执行所描述的实现方式的功能。所描述的特征可以有利地被实现在可在可编程系统上执行的一个或多个计算机程序中,所述可编程系统包括:至少一个可编程处理器,所述至少一个可编程处理器被连接以从数据存储系统接收数据和指令并且向其传输数据和指令;至少一个输入装置;以及至少一个输出装置。计算机程序是可以直接或间接地用于计算机以执行某一活动或带来某一结果的一组指令。计算机程序可以任何形式的编程语言编写,包括编译型语言或解释型语言,并且所述计算机程序可以任何形式部署,包括作为独立式程序或作为模块、部件、子例程、或适合于在计算环境中使用的其他单元。The described features can be implemented in digital electronic circuitry, or in computer hardware, firmware, software, or a combination thereof. The apparatus may be implemented in a computer program product executed by a programmable processor, the computer program product being tangibly embodied in an information carrier, for example in a machine-readable storage device; and method steps may be performed by the programmable processor , the programmable processor executes a program of instructions to perform the functions of the described implementation by operating on input data and generating output. The described features may advantageously be implemented in one or more computer programs executable on a programmable system comprising: at least one programmable processor connected to to receive data and instructions from and transmit data and instructions to a data storage system; at least one input device; and at least one output device. A computer program is a set of instructions that can be used, directly or indirectly, on a computer to perform a certain activity or bring about a certain result. Computer programs may be written in any form of programming language, including compiled or interpreted languages, and the computer programs may be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or suitable for use in a computing environment other units used in .
用于执行指令程序的适合处理器举例来讲包括通用微处理器和专用微处理器两者、以及任何种类的计算机的单处理器或多个处理器中的一个。一般而言,处理器将从只读存储器或随机存取存储器或者两者中接收指令和数据。计算机的必要元件是用于执行指令的处理器以及用于存储指令和数据的一个或多个存储器。一般而言,计算机将还包括用于存储数据文件的一个或多个大容量存储装置,或者操作性地连接以与之通信;这类装置包括磁盘,诸如内置硬盘和可移除盘;磁光盘;以及光盘。适合于有形地体现计算机程序指令和数据的存储装置包括所有形式的非易失性存储器,举例来讲包括:半导体存储器装置,诸如EPROM、EEPROM和闪存装置;磁盘,诸如内置硬盘和可移除盘;磁光盘;以及CD-ROM和DVD-ROM盘。处理器和存储器可以由ASIC(专用集成电路)补充或纳入到其中。Suitable processors for the execution of the program of instructions include, by way of example, both general and special purpose microprocessors, as well as a single processor or one of multiple processors of any kind of computer. In general, a processor will receive instructions and data from read-only memory or random access memory, or both. The essential elements of a computer are a processor for executing instructions and one or more memories for storing instructions and data. Generally, a computer will also include, or be operatively connected to communicate with, one or more mass storage devices for storing data files; such devices include magnetic disks, such as internal hard disks and removable disks; magneto-optical disks ; and CD-ROM. Storage devices suitable for tangibly embodying computer program instructions and data include all forms of non-volatile memory including, by way of example: semiconductor memory devices such as EPROM, EEPROM and flash memory devices; magnetic disks such as internal hard disks and removable disks ; magneto-optical discs; and CD-ROM and DVD-ROM discs. The processor and memory may be supplemented by or incorporated into an ASIC (Application Specific Integrated Circuit).
根据一种优选实施方式,所述系统还包括行为规则模块,所述行为规则模块分别与摆放姿势检测模块和风控等级划分模块相连,并且其用于预设与至少一个摆放姿势分别对应的用于指示在该摆放姿势下可能将出现的运动特征变化趋势。本申请中行为规则模块针对由摆放姿势检测模块所确定的若干摆放姿势分别对应有预设的不同运动特征变化趋势,能够区别于各摆放姿势下所可能出现的危险动作或行为,直接于预设运动特征变化趋势进行比对即可判断其动作或行为是否存在潜在风险,避免了现有技术中对大量数据进行分析处理再判断而导致数据处理反馈时间长的问题。According to a preferred embodiment, the system further includes a behavior rule module, the behavior rule module is respectively connected with the pose detection module and the risk control level division module, and is used to preset at least one pose respectively corresponding to the module. It is used to indicate the change trend of the movement characteristics that may appear in this pose. In the present application, the behavior rule module corresponds to a plurality of postures determined by the posture detection module, respectively corresponding to different trends of movement characteristics. By comparing the change trend of the preset motion features, it can be judged whether the action or behavior has potential risks, which avoids the problem of long data processing and feedback time caused by analyzing and processing a large amount of data and then judging in the prior art.
根据一种优选实施方式,所述运动特征变化趋势至少包括针对已接受过体位变化指导的被监护对象的运动特征变化趋势以及针对尚未接受过体位变化指导的被监护对象的运动特征变化趋势。这里所指的体位变化指导主要是指在被监护对象已经住院一段时间,经由监护对象教导其正确合适的翻身或起身姿势。相对地,未接受过体位变化指导主要是指被监护对象刚住院或住院时间不长,尚未进行翻身或起身姿势指导。以此区别出的两种运动特征变化趋势,能够区别出当前被监护对象在脱离监护的情况下更可能出现的动作或行为,能够有效地提高数据比对处理的速度,进一步地提高了对被监护对象的监护准确性以及有效性。According to a preferred embodiment, the motion feature change trend includes at least a motion feature change trend for a monitored object that has received body position change guidance and a motion feature change trend for a monitored object that has not received body position change guidance. The body position change instruction referred to here mainly refers to the correct and appropriate posture for turning over or getting up through the guardian object when the supervised object has been hospitalized for a period of time. On the other hand, those who have not received body position change guidance mainly refer to the fact that the supervised object has just been hospitalized or has not been hospitalized for a long time, and has not yet been guided to turn over or get up. The change trends of the two motion characteristics distinguished by this can distinguish the actions or behaviors that are more likely to occur when the currently monitored object is out of monitoring, which can effectively improve the speed of data comparison and processing, and further improve the accuracy of the monitored object. The accuracy and effectiveness of the guardianship of the guardian.
根据一种优选实施方式,由所述风控等级划分模块所确定的具有最高风控等级的被监护对象的运动功能障碍程度不完全低于其他风控等级下的被监护对象。针对部分独立性较好的被监护对象,其偏瘫侧运动功能障碍程度较小,翻身难度或是起身难度不大,但往往因此过高地以为其已经可以独立下床或随意翻身,造成此类人群的离床跌倒风险比独立性较差的人群更高,本申请中风控等级划分模块基于由移动数字设备所确定的运动功能障碍程度来确定该被监护对象的风控等级,进而能够有区别地对不同被监护对象的行为或动作进行不同程度的预警,医护人员在接收到预警时也可立即知道预警事件的严重程度。According to a preferred embodiment, the degree of motor dysfunction of the monitored object with the highest risk control level determined by the risk control level classification module is not completely lower than that of the monitored objects at other risk control levels. For some supervised subjects with good independence, the degree of motor dysfunction on the hemiplegic side is relatively small, and it is not difficult to turn over or get up, but they often think that they can get out of bed independently or turn over at will. The risk of falling out of bed is higher than that of people with poor independence. In this application, the risk control level classification module determines the risk control level of the supervised object based on the degree of motor dysfunction determined by the mobile digital device, and then can differentiate Different degrees of early warning are given to the behaviors or actions of different supervised objects, and medical staff can immediately know the severity of the warning event when they receive the warning.
根据一种优选实施方式,所述系统还包括摆放姿势检测模块,所述摆放姿势检测模块与所述采集模块相连接,其用于确定被监护对象的患侧与床垫之间的相对位置关系并基于该相对位置关系与至少部分运动特征值来生成被监护对象当前的摆放姿势。由于偏瘫患者体位摆放姿势的特殊性,偏瘫患者卧床时往往需要借助于如图2所示的多个枕头来辅助其保持良肢位,但由于部分肢体是通过枕头间接地施压至床垫上的,存在可能两个摆放姿势所对应的压力分布相似度极高而无法区分开不同姿势的问题。本发明中通过设置摆放姿势检测模块,该模块基于预先确定的患者患肢所在侧与床垫之间的相对位置关系,能够预测确定出患者在床垫上的良肢位的压力分布数据,以此即可通过将当前压力分布数据与预测的压力分布数据相比对,准确地分析得到当前摆放姿势或是姿势变化。According to a preferred embodiment, the system further includes a posture detection module, which is connected to the acquisition module and is used to determine the relative relationship between the affected side of the monitored object and the mattress the positional relationship, and based on the relative positional relationship and at least part of the motion feature values, the current pose of the monitored object is generated. Due to the particularity of the posture of hemiplegic patients, they often need to use multiple pillows as shown in Figure 2 to help them maintain a good limb position when they are in bed, but because some limbs are indirectly pressed to the mattress through pillows Above, there is a problem that the pressure distributions corresponding to the two poses may be so similar that it is impossible to distinguish different poses. In the present invention, by setting a posture detection module, the module can predict and determine the pressure distribution data of the patient's good limb position on the mattress based on the predetermined relative positional relationship between the patient's affected limb and the mattress. In this way, by comparing the current pressure distribution data with the predicted pressure distribution data, the current posture or posture change can be accurately analyzed and obtained.
根据一种优选实施方式,所述床垫上划分有彼此间隔设置且均设置有至少一个传感器的髋骨区域和肩肘区域,所述髋骨区域所对应的床体可回弹变形能力至少相对所述肩肘区域所对应的床体可回弹变形能力更高。由于髋骨区域所对应的床体可回弹变形能力更好,能够减轻脑卒中偏瘫患者侧卧或躺卧时髋骨、骶骨等肢体处所承受的压力,利于血液循环的提升以及侧卧挤压对患侧或健侧的伤害的降低。According to a preferred embodiment, the mattress is divided into a hip region and a shoulder-elbow region that are spaced apart from each other and are each provided with at least one sensor, and the resilience and deformability of the bed corresponding to the hip region is at least relative to all The bed body corresponding to the shoulder and elbow region has higher resilience and deformation ability. Because the bed body corresponding to the hip bone area has better resilience and deformation ability, it can reduce the pressure on the hip bone, sacrum and other limbs when stroke hemiplegia patients lie on their side or lie down, which is beneficial to the improvement of blood circulation and lateral compression. Decreased damage to the affected or unaffected side.
根据一种优选实施方式,所述肩肘区域上所设置的传感器分布密度至少相对所述髋骨区域上所设置的传感器分布密度更大。本申请中适用于同一侧上下肢均存在运动功能障碍的被监护对象适用于的床垫,至少从传感器分布以及床体可回弹变形能力两方面,来在保证被监护对象的舒适性的同时,还提高了数据获取的有效性和灵敏性。According to a preferred embodiment, the distribution density of the sensors arranged on the shoulder and elbow region is at least greater than that of the sensors arranged on the hip bone region. In this application, a mattress suitable for a supervised subject with motor dysfunction on the same upper and lower limbs can ensure the comfort of the supervised subject at least in terms of sensor distribution and the ability of the bed to rebound and deform. , but also improve the effectiveness and sensitivity of data acquisition.
本申请所提出的该系统不仅是发挥上述离床预警作用,还可以通过将上述离床预警系统中参数进行简单调整,即可作为一种适用于脑卒中偏瘫患者的康复系统,该康复系统至少包括第一处理器(采集模块)、第二处理器(风控等级划分模块)、第三处理器(预警信息处理器)、第四处理器、第五处理器、穿戴式设备以及移动数字设备。该康复系统通过设置用于在采集到医护人员确定的患者进行康复训练的信息时进入康复指导模式的第四处理器,由该第四处理器指示本系统中用于预设运动特征变化趋势的第五处理器(行为规则模块)调高其触发阈值,若干康复指导等级与至少一个触发阈值相对应,并相应地选用与患侧上下肢的运动功能障碍程度相对应的康复指导等级,使该系统转变为了在患者动作达标时才会发出通知的康复指导模式,患者能够明确康复训练目标进而达到更好的康复效果,同时由于该康复辅助作用的实现,增强了患者佩戴穿戴式设备的主观意愿,愿意长期佩戴,不会因反感其监测目的而取下,因此反之还能够更好地实现该系统在非康复训练时间段的离床预警监测作用。The system proposed in this application not only plays the role of the above-mentioned early warning of getting out of bed, but also can be used as a rehabilitation system suitable for hemiplegic patients with stroke by simply adjusting the parameters in the above-mentioned early warning system for getting out of bed. The rehabilitation system at least It includes a first processor (collection module), a second processor (wind control level division module), a third processor (early warning information processor), a fourth processor, a fifth processor, wearable devices and mobile digital devices . The rehabilitation system is provided with a fourth processor configured to enter the rehabilitation guidance mode when the information determined by the medical staff for the patient to perform rehabilitation training is collected, and the fourth processor instructs the system for presetting the change trend of the movement characteristics in the system. The fifth processor (behavioral rule module) increases its triggering threshold, several rehabilitation guidance levels correspond to at least one triggering threshold, and correspondingly selects the rehabilitation guidance level corresponding to the degree of motor dysfunction of the upper and lower limbs on the affected side, so that the The system has been transformed into a rehabilitation guidance mode that will only issue a notification when the patient's actions meet the standard. The patient can clarify the rehabilitation training goal and achieve a better rehabilitation effect. At the same time, due to the realization of the auxiliary function of rehabilitation, the subjective willingness of the patient to wear the wearable device is enhanced. , is willing to wear it for a long time, and will not take it off because of disgust for its monitoring purpose, so on the contrary, it can better realize the early warning monitoring function of the system in non-rehabilitation training time periods.
一种脑卒中偏瘫患者用康复系统,该康复系统包括:存储器;以及与所述存储器相耦合的至少一个处理器,至少一个处理器包括:第一处理器,获取由仅佩戴于被监护对象的患侧上下肢的穿戴式设备所采集到的行为数据;第二处理器,用于根据被监护对象历史康复数据来确定与之对应的康复指导等级;第三处理器,其被配置为在确定当前模式为康复指导模式时以调整预设的康复指导等级的方式基于第一处理器从行为数据中所提取到的至少一个运动特征值之间的阶段属性关联规则以及预设的康复指导等级来判断其行为数据是否满足康复要求,并在满足康复要求时将动作达标信息传递至周边的由监护人员所携带的至少一个移动数字设备,其中,第一处理器、第二处理器与第三处理器均设于所述穿戴式设备中。根据一种优选实施方式,至少一个处理器还被配置为预设与至少一个特定姿势分别对应的用于指示在该特定姿势下可能将出现的运动特征变化趋势。优选地,由第四处理器来确定当前模式是否转换为康复指导模式并在转换为康复指导模式时指示本系统中用于预设运动特征变化趋势的第五处理器(行为规则模块)调高其触发阈值,或是由康复指导模式转换至离床预警模式时指示本系统中用于预设运动特征变化趋势的第五处理器(行为规则模块)调低其触发阈值。A rehabilitation system for hemiplegic patients after stroke, the rehabilitation system includes: a memory; and at least one processor coupled with the memory, the at least one processor includes: a first processor, which acquires data obtained by wearing only a subject to be monitored. The behavior data collected by the wearable device of the upper and lower limbs on the affected side; the second processor is used to determine the corresponding rehabilitation guidance level according to the historical rehabilitation data of the monitored object; the third processor is configured to determine When the current mode is the rehabilitation guidance mode, the preset rehabilitation guidance level is adjusted based on the stage attribute association rule between the at least one motion feature value extracted by the first processor from the behavior data and the preset rehabilitation guidance level. Determine whether its behavior data meets the rehabilitation requirements, and when the rehabilitation requirements are met, transmit the action compliance information to the surrounding at least one mobile digital device carried by the guardian, wherein the first processor, the second processor and the third processor All devices are installed in the wearable device. According to a preferred embodiment, the at least one processor is further configured to preset corresponding at least one specific gesture, respectively, to indicate a change trend of the motion feature that may occur in the specific gesture. Preferably, the fourth processor determines whether the current mode is converted into the rehabilitation guidance mode and instructs the fifth processor (behavioral rule module) in the system for the preset movement feature change trend to increase when the current mode is converted into the rehabilitation guidance mode Its triggering threshold value, or instructing the fifth processor (behavioral rule module) in the system for preset movement characteristic change trend to lower its triggering threshold value when switching from rehabilitation guidance mode to bed exit warning mode.
附图说明Description of drawings
图1是本发明所提出的脑卒中偏瘫患者用离床预警系统的简化结构连接关系示意图;Fig. 1 is the simplified structure connection relation diagram of the early warning system for getting out of bed for stroke hemiplegia patients proposed by the present invention;
图2是本发明所提及的被监护对象的体位摆放姿势的简化示意图;和Fig. 2 is the simplified schematic diagram of the body position of the supervised object mentioned in the present invention; and
图3是本发明所提出的离床预警系统中床垫的简化侧视结构示意图。FIG. 3 is a simplified side structural schematic diagram of the mattress in the bed exit warning system proposed by the present invention.
附图标记列表List of reference signs
1:穿戴式设备 2:采集模块1: Wearable device 2: Acquisition module
3:风控等级划分模块 4:预警信息处理器3: Risk control grade division module 4: Early warning information processor
5:行为规则模块 6:摆放姿势检测模块5: Behavior Rule Module 6: Posture Detection Module
7:移动数字设备 8:床垫7: Mobile digital devices 8: Mattresses
9:髋骨区域 10:肩肘区域9: Hip area 10: Shoulder and elbow area
1a:第一穿戴式设备 1b:第二穿戴式设备1a: first
具体实施方式Detailed ways
下面结合附图对本发明进行详细说明。The present invention will be described in detail below with reference to the accompanying drawings.
本发明相关术语及其解释:Terms related to the present invention and their explanations:
穿戴式设备1:穿戴式设备1是指具备部分计算功能、可连接手机及各类终端的便携式配件,可以包括以手腕为支撑的watch类包括手表和腕带等产品,以脚为支撑的shoes类包括鞋、袜子或者其他腿上佩戴产品,以头部为支撑的Glass类包括眼镜、头盔、头带等产品形态。本发明所指的穿戴式设备1主要指的是以手腕为支撑的watch类产品形态的设备。优选地,本发明中所指的穿戴式设备1还可以指以手腕和脚踝为支撑的watch类产品形态的设备。其中,佩戴侧主要是被监护对象的患侧。Wearable device 1: Wearable device 1 refers to portable accessories that have some computing functions and can be connected to mobile phones and various terminals. It can include wrist-supported watches, including watches and wristbands, and feet-supported shoes. The category includes shoes, socks or other products worn on the legs, and the Glass category supported by the head includes glasses, helmets, headbands and other product forms. The wearable device 1 referred to in the present invention mainly refers to a device in the form of a watch product supported by a wrist. Preferably, the wearable device 1 referred to in the present invention may also refer to a device in the form of a watch product supported by a wrist and an ankle. Among them, the wearing side is mainly the affected side of the monitored object.
被监护对象的患侧:被监护对象的患侧指的是被监护对象的出现运动功能障碍的单侧的上肢和下肢。运动功能障碍是脑卒中后最突出的问题,因病灶的不同会引起各种不同的障碍现象,在运动障碍中最典型的就是偏瘫。严重者瘫痪肢体完全不能自主运动、失去感觉,没有肌力,稍轻者瘫痪侧肌力减退,活动不便。The affected side of the monitored object: The affected side of the monitored object refers to the unilateral upper and lower limbs of the monitored object with motor dysfunction. Motor dysfunction is the most prominent problem after stroke. Different lesions can cause various disorders. The most typical movement disorder is hemiplegia. In severe cases, the paralyzed limbs are completely unable to move voluntarily, lose sensation, and have no muscle strength.
行为数据:行为数据包括基于由床垫8上所布置的传感器所采集到的压力数据,所确定的与被监护对象的摆放姿势或是姿势变化信息。行为数据还包括基于由被监护人员所佩戴的穿戴式设备1所采集到的运动数据,所确定的与被监护对象的摆放姿势或是姿势变化信息。行为数据还包括由被监护对象的历史病例数据所确定的被监护对象的患肢所在侧,进而也能够确定被监护对象的患侧与床垫8之间的相对位置关系。Behavioral data: The behavioral data includes information on the position or posture change of the monitored object determined based on the pressure data collected by the sensors arranged on the
相对位置关系:被监护对象的患侧与床垫8之间的相对位置关系,指的是通过预先设定床垫8上用于被监护对象上下床的两侧分别为左侧及右侧,在被监护对象仰躺至床垫8上时被监护对象的患侧所处的床垫8左侧或床垫8右侧。Relative positional relationship: The relative positional relationship between the affected side of the monitored object and the
被监护对象历史风控数据:此处所提及的历史数据指的是医院信息系统中所存储的被监护对象的基础信息以及就诊信息等。本发明中所提及的历史数据还包括由监护人员所输入的关于该被监护对象的量表评估结果、历史行为数据(如历史自行离床次数、历史下床跌倒次数)。Historical risk control data of the monitored object: The historical data mentioned here refers to the basic information and medical treatment information of the monitored object stored in the hospital information system. The historical data mentioned in the present invention also includes the scale evaluation results and historical behavior data (such as the historical times of getting out of bed by themselves, and the historical times of getting out of bed and falling) entered by the guardian.
风控等级:风控等级指的是根据被监护对象历史风控数据,来确定的被监护对象所对应的离床风险控制等级,其包括Ⅰ级(基本独立但过高估计自己活动能力)、Ⅱ级(有条件独立或极轻度依赖)、Ⅲ级(中度或重度依赖)、Ⅳ级(极重度或完全依赖)。风控等级是用于针对不同独立程度的被监护对象提供不同限制程度的运动风险控制。单个风控等级包括某一摆放姿势下单侧肢体运动限制程度。Risk control level: The risk control level refers to the risk control level of leaving the bed corresponding to the monitored object based on the historical risk control data of the monitored object. Grade II (conditional independence or very mild dependence), grade III (moderate or severe dependence), and grade IV (very severe or complete dependence). The risk control level is used to provide different degrees of exercise risk control for supervised objects with different degrees of independence. A single risk control level includes the degree of unilateral limb movement restriction in a certain posture.
同一侧上下肢均存在运动功能障碍:在本发明中所指的被监护对象主要是同一侧上下肢均存在运动功能障碍的人群,即同一侧的上肢与下肢均存在活动不便行动困难的运动功能障碍。此类患者大部分时间都是在病床上度过的,通常为避免肌张力过高和活动能力丧失等病发症,需要由监护人员辅助被监护对象调整至合适的卧床体位摆放姿势,体位摆放将直接关系到康复预后的好坏。Both the upper and lower limbs on the same side have motor dysfunction: in the present invention, the monitored objects are mainly people who have motor dysfunction on the same side of the upper and lower limbs, that is, the upper and lower limbs on the same side have motor functions that are inconvenient and difficult to move. obstacle. Such patients spend most of their time in the hospital bed. Usually, in order to avoid complications such as hypertonia and loss of mobility, it is necessary for the guardian to assist the monitored object to adjust to the appropriate bed position. The placement will be directly related to the prognosis of rehabilitation.
运动特征值:运动特征值指的是由行为数据所确定的被监护对象在床上所处的摆放姿势、压力分布情况、肢体运动数据(上肢或下肢动作的运动幅度等参数)。具体地,运动特征值包括由预警信息处理器从由佩戴于被监护对象的患侧上肢的第一穿戴式设备1a所采集到的行为数据中所提取到的第一运动特征值,以及由预警信息处理器从由佩戴于被监护对象的患侧下肢的第二穿戴式设备1b所采集到的行为数据中所提取到的第二运动特征值。这里所提及的第一运动特征值与第二运动特征值主要指的是运动特征值中肢体运动数据这一块所包含的内容,也就是运动特征值还可以包括摆放姿势所对应的第三运动特征值、第四.....优选地,第一运动特征值与第二运动特征值之间存在阶段属性关联规则。Motion feature value: The motion feature value refers to the position of the monitored object on the bed, the pressure distribution, and the limb motion data (parameters such as the motion range of the upper or lower limb movements) determined by the behavior data. Specifically, the motion feature value includes the first motion feature value extracted by the early warning information processor from the behavior data collected by the first wearable device 1a worn on the affected side upper limb of the monitored object, and the early warning information processor. The information processor extracts the second motion feature value from the behavior data collected by the second
移动数字设备7:移动数字设备7指的是基于电池供电的手持设备等,如移动电话、计算机、便携式媒体播放器、遥控设备、个人数字助理、寻呼设备、GPS定位装置、PDA、计算器、便携式医疗设备等等。本发明中移动数字设备7主要是由监护人员随身携带及操作。主要起到将预警信息以视觉、听觉、触觉等方式来使监护人员获知预警信息的作用,并能够在其操作界面展示至少一个量表来与监护人员进行交互,获取由监护人员所输入的输入信息并根据该输入信息生成量表评估结果。Mobile digital device 7: Mobile
量表:量表或称功能综合评定量表,是用客观、有效而准确的方法来评定患者的功能障碍的、用于监护人员了解被监护对象的功能状况、制定康复治疗方案和评定疗效的前提。其可以包括:功能综合评定量表(functional comprehensive assessment,FCA)量表,用以评测患者综合功能;简易精神状态检查表(mini-mental state examination,MMSE),采用1975年Folstein等编制的量表经修改的MMSE中译本,实施及计分方法为每题答对给1分,总分范围0~30分,用于评测患者认知功能;Barthel指数(BI),采用1965年由Barthel等编制的量表,用于评测患者日常生活活动(Activity of Daily Living,ADL)能力;生活质量指数(the quality of life index,QLI),对患者的活动、日常生活、健康、支持和前景5个项目进行评测,实施及计分方法为每项最高分2分,最低分0分,总分范围0~10分,用于评测患者生活质量;功能独立性评定(Function Independent Measure,FIM)量表,FIM量表是残疾患者日常生活活动能力评估中一项有效的检测工具。由监护人员所操作的至少一个移动数字设备7所确定的运动功能障碍评估结果,可以包括包括Ⅰ级(基本独立但过高估计自己活动能力)、Ⅱ级(有条件独立或极轻度依赖)、Ⅲ级(中度或重度依赖)、Ⅳ级(极重度或完全依赖)。运动功能障碍评估结果可以是以被监护对象的独立性(主要指的是患者完成某一规定动作或项目所需要的帮助程度)较好或较差两个结果之一来表示。被监护对象的独立性可以是患者完成半起身或下床的动作所需要的帮助程度。被监护对象的独立性较好包括Ⅰ级(基本独立但过高估计自己活动能力)和Ⅱ级(有条件独立或极轻度依赖),被监护对象的独立性较差包括Ⅲ级(中度或重度依赖)、Ⅳ级(极重度或完全依赖)。Scale: The scale or the functional comprehensive assessment scale is used to assess the patient's functional impairment in an objective, effective and accurate method, and is used by the guardians to understand the functional status of the monitored object, formulate rehabilitation treatment plans and evaluate the curative effect. premise. It can include: functional comprehensive assessment (FCA) scale, which is used to evaluate the comprehensive function of patients; mini-mental state examination (MMSE), which adopts the scale developed by Folstein et al. in 1975. The revised Chinese translation of MMSE, the implementation and scoring method is 1 point for each correct answer, with a total score range of 0 to 30 points, which is used to evaluate the cognitive function of patients; The scale is used to evaluate the patient's activities of daily living (Activity of Daily Living, ADL); the quality of life index (the quality of life index, QLI), the patient's activity, daily life, health, support and
摆放姿势:也称体位摆放姿势或良肢位,是指为防止或对抗痉挛姿势的出现,保持肩关节及早期诱发分离运动而设计的一种治疗体位。该点即为脑卒中偏瘫患者的卧床体位摆放的特殊性要求。脑卒中偏瘫患者的典型姿势表现为上肢的肩下沉后缩,肘关节屈曲,前臂旋前,腕关节掌屈,手指屈曲;下肢的外旋,髋膝关节伸直,足下垂内翻。早期注意并保持床上的正确体位,有助于预防或减轻上述痉挛姿势的出现和加重。如图2所示,通常选用以下体位:患侧卧位、健侧卧位、仰卧位。"患侧卧位"即患侧在下,健侧在上。头部用枕头舒适的支撑,患侧上肢前伸,使肩部向前,确保肩胛骨的内缘平靠于胸壁。上臂前伸以避免肩关节受压和后缩。肘关节伸展,前臂旋后,手指张开,掌心向上。健侧上肢不能放在身前,因会带动整个躯干向前而引起肩胛骨后缩。患侧下肢在后,患髋关节微后伸,膝关节略屈曲,足底蹬支撑物。"健侧卧位"即健侧在下,患侧在上,头部枕头不宜过高。患侧上肢下垫一枕头,肩前屈90°~130°,肘和腕伸展,前臂旋前,腕关节背伸,患侧骨盆旋前,髋、膝关节呈自然半屈曲位,置于枕上;患足与小腿尽量保持垂直位,注意足不能内翻悬于枕头边缘;身后可放置枕头支撑,有利于身体放松。健侧下肢平放在床上,轻度伸髋,稍屈膝。"仰卧位"即头下置一枕头,但不宜过高,面部朝向患侧;患侧肩部垫一比躯干略高的枕头,将伸展的上肢置于枕上,防止肩胛骨后缩;前臂旋后,手掌心向上,手指伸展、张开;在患侧臀部及大腿下垫枕,以防止患侧骨盆后缩。Posture: Also known as body position or good limb position, it refers to a therapeutic position designed to prevent or resist the appearance of spastic posture, maintain the shoulder joint and induce separation movement early. This point is the special requirement for the placement of the bed position for hemiplegia patients with stroke. The typical postures of hemiplegic patients with stroke are as follows: shoulder sinking and retraction, elbow flexion, forearm pronation, wrist palm flexion, and finger flexion of the upper limb; external rotation of the lower limb, extension of the hip and knee joint, and foot drop and varus. Early attention to and maintaining the correct position on the bed can help prevent or reduce the appearance and exacerbation of these spastic positions. As shown in Figure 2, the following positions are usually used: lying on the affected side, lying on the unaffected side, and supine. "Ill-side lying position" means that the affected side is down and the unaffected side is up. The head is comfortably supported with a pillow, and the upper limbs on the affected side are extended forward, so that the shoulders are forward, making sure that the inner edge of the scapula is flat against the chest wall. Extend your upper arms forward to avoid shoulder compression and retraction. Elbow extended, forearm supinated, fingers open, palm up. The upper limb of the unaffected side cannot be placed in front of the body, as it will drive the entire trunk forward and cause the scapula to retract. The lower limb of the affected side is behind, the hip joint is slightly extended, the knee joint is slightly flexed, and the soles are supported. The "healthy side lying position" means that the healthy side is down, the affected side is up, and the head pillow should not be too high. Place a pillow under the upper extremity of the affected side, flex the shoulders 90° to 130° forward, extend the elbow and wrist, pronate the forearm, extend the wrist joint dorsally, pronate the pelvis on the affected side, and place the hip and knee joints in a natural semi-flexed position on the pillow. ; Keep the affected foot and the calf in a vertical position as much as possible, pay attention to the fact that the foot cannot be turned inversion and hang on the edge of the pillow; a pillow can be placed behind it to support the body, which is conducive to the relaxation of the body. Lay the unaffected leg flat on the bed, slightly extend the hip, and slightly bend the knee. "Supine position" means placing a pillow under the head, but it should not be too high, with the face facing the affected side; a pillow slightly higher than the trunk is placed on the shoulder of the affected side, and the stretched upper limb is placed on the pillow to prevent the scapula from retracting; the forearm is supinated , palm up, fingers stretched, open; in the affected side of the hip and thigh pillow to prevent the affected side of the pelvis retraction.
运动特征变化趋势:在该摆放姿势下可能将出现的运动特征变化趋势,指的是在监护人员调整了被监护对象的姿势至合适的摆放姿势后,被监护对象在无监护的情况下可能出现的行为。其包括危险系数极低的肢体小幅度抬放翻转等且被监护对象的摆放姿势不改变的第一模式、危险系数中等的尝试翻身或是尝试起身且被监护对象的独立性差的第二模式、危险系数较大的尝试翻身或是尝试起身且被监护对象的独立性较好的第三模式、以及危险系数较大的肢体小幅度抬放翻转等且被监护对象的摆放姿势发生改变的第四模式。区别于不同的体位摆放姿势,各体位摆放姿势分别对应有预定义的第一模式、第二模式、第三模式和第四模式。Motion feature change trend: The motion feature change trend that may appear in this pose refers to the fact that after the guardian adjusts the posture of the object to be monitored to a suitable pose, the object to be monitored will not be supervised. possible behavior. It includes the first mode in which the risk factor is extremely low and the limbs are slightly lifted and turned, and the posture of the supervised object does not change, and the second mode in which the risk factor is moderately trying to turn over or trying to get up and the supervised object is less independent. , those with a high risk factor try to turn over or try to get up and the third mode in which the supervised object is more independent, and those with a large risk factor lift and flip the limbs in small steps and the supervised object's posture changes. Fourth mode. Different from different body position placement postures, each body position placement posture corresponds to a predefined first mode, second mode, third mode and fourth mode respectively.
阶段属性关联规则:阶段属性关联规则与由监护人员所操作的至少一个移动数字设备7所确定的运动功能障碍评估结果相对应。这里所提及的阶段属性关联规则指的是根据由用户当前的运动功能障碍评估结果所确定的运动功能障碍程度,区别于患者在当前阶段下所伴有的运动功能障碍的程度,来确定的第一运动特征值所对应的运动特征变化趋势与第二运动特征值所对应的运动特征变化趋势。这里所提及的运动特征变化趋势,主要是指保持在某一摆放姿势下的被监护对象在无监护的情况下可能出现的行为,其主要用于区别第一模式、第二模式、第三模式和第四模式之间的界限/触发阈值。进一步优选地,本发明中所提及的“预警信息处理器4基于预设的风控等级以及第一运动特征值与第二运动特征值之间的与由监护人员所操作的至少一个移动数字设备7所确定的运动功能障碍评估结果所对应的阶段属性关联规则来判断其行为数据是否触发预警”中,阶段属性关联规则与风控等级只是用于预警信息处理器4判断行为数据是否触发预警的部分待处理数据。Stage attribute association rule: The stage attribute association rule corresponds to the motor dysfunction assessment result determined by at least one mobile
针对阶段属性关联规则如下举例说明:在由监护人员所操作的至少一个移动数字设备7所确定的运动功能障碍评估结果为被监护对象的独立性较差时,确定与该情况下所对应的上肢预设运动幅度(上肢运动幅度触发阈值)、上肢预设挪动幅度(上肢挪动幅度触发阈值)、下肢预设运动幅度(下肢运动幅度触发阈值)以及下肢预设挪动幅度(下肢挪动幅度触发阈值),以及基于确定的上述幅度/触发阈值,可以区别出第一模式、第二模式、第三模式和第四模式之间的界限,并且能够通过整体地调高或调低四个模式的上述幅度/触发阈值,可以使得该系统在离床预警模式与康复指导模式之间转换。区别于离床预警模式与康复指导模式下所对应的提醒方式,离床预警模式可以是电话铃声式持续地响铃且必须由医护人员手动才能关掉,康复指导模式可以是短信式简短地提示音而只是起到提示医护人员与被监护对象的作用即可。For the stage attribute association rule, the following example illustrates: when the motor dysfunction assessment result determined by at least one mobile
为明确运动特征变化趋势与体位摆放姿势之间的相关性,针对运动特征变化趋势进一步举例说明:当医护人员辅助患者调整至呈健侧卧位的体位摆放姿势时(即图2中的最后一个示意图,该示意图中患者侧卧且其患侧位于健侧上方),由于床垫8的右侧设置有枕头且此时患侧位于床垫8右侧,即在无监护的情况下,患者想要下床,需利用健侧支撑,先将患侧朝向床垫8的左侧翻转,翻转至仰卧姿势再继续使用健侧来起身。患者无法在无监护的情况下自行朝向床垫右侧翻转。该过程中,患者需要先将放置在枕头上的患侧上肢收回,收回至患侧腰附近,同时利用健侧的力量逐渐将患侧下肢翻转至床垫左侧来。该过程中,由于患者在健侧卧位上,其健侧较为靠近床垫8的左侧边沿,即若患者朝向床垫8的左侧翻身,很有可能直接翻下床垫8或是出于非常靠近床边沿的危险位置上。该过程中,患者在健侧卧位上,也可能仅仅只是想要调整患肢的位置,来缓解可能出现的由长时间压迫引起的血液循环不畅,即有可能利用健侧来上下活动患侧上肢或小幅度挪动患侧下肢。In order to clarify the correlation between the change trend of movement characteristics and body position, further examples are given for the change trend of movement characteristics: when the medical staff assists the patient to adjust to the position of the unaffected side lying position (that is, the position in Figure 2). The last schematic diagram, in this schematic diagram, the patient is lying on the side and the affected side is located above the healthy side), since the right side of the
通过上述对处于健侧卧位的体位摆放姿势下的患者在无监护的情况下可能出现的行为的分析,以下对该体位摆放姿势所对应的第一模式、第二模式、第三模式和第四模式分别进行预设:若佩戴于患侧上肢的穿戴式设备1已采集到满足上肢预设运动幅度的行为数据,则在监测到患侧下肢的穿戴式设备1所采集到的行为数据满足下肢预设运动幅度、并且监测到患者由侧躺转换为仰躺或是由仰躺转换为侧躺时,确定当前患者情况为肢体小幅度抬放翻转等且被监护对象的摆放姿势发生改变的危险系数较大的第四模式。Through the above-mentioned analysis of the behavior of the patient in the unsupervised position in the unsupervised position, the first mode, the second mode and the third mode corresponding to the position are as follows. Preset separately from the fourth mode: if the wearable device 1 worn on the upper limb on the affected side has collected behavior data that meets the preset motion range of the upper limb, the behavior collected by the wearable device 1 on the lower limb on the affected side is monitored. When the data satisfies the preset motion range of the lower limbs, and the patient is monitored from lying on the side to lying on the back or from lying on the back to lying on the side, it is determined that the current patient's condition is a small lift and flip of the limb and the posture of the monitored object. A fourth mode with a higher risk of change.
若佩戴于患侧上肢的穿戴式设备1已采集到满足上肢预设运动幅度的行为数据,并且被监护对象的独立性较好,则在监测到患侧下肢的穿戴式设备1所采集到的行为数据满足下肢预设运动幅度时,或是在监测到床垫8右侧上压力分布逐渐减少且左侧上压力分布逐渐增加时,由于被监护对象的独立性较好,翻身难度或起身难度不大,因而危险系数较大,确定其为第三模式。If the wearable device 1 worn on the upper limb on the affected side has collected behavioral data that meets the preset motion range of the upper limb, and the independence of the monitored object is good, then the data collected by the wearable device 1 on the lower limb on the affected side is collected When the behavior data meets the preset motion range of the lower limbs, or when the pressure distribution on the right side of the
若佩戴于患侧上肢的穿戴式设备1已采集到满足上肢预设运动幅度的行为数据,并且被监护对象的独立性较差,则在监测到患侧下肢的穿戴式设备1所采集到的行为数据满足下肢预设运动幅度时,或是在监测到床垫8右侧上压力分布逐渐减少且左侧上压力分布逐渐增加时,患者通常是在尝试翻身或尝试起身,但由于被监护对象的独立性较差,翻身难度高,因而危险系数为中等,确定其为第二模式。If the wearable device 1 worn on the upper limb on the affected side has collected behavioral data that meets the preset motion range of the upper limb, and the independence of the monitored object is poor, then the data collected by the wearable device 1 on the lower limb on the affected side is collected when the monitored object is less independent. When the behavior data meets the preset motion range of the lower limbs, or when the pressure distribution on the right side of the
在佩戴于患侧上肢的穿戴式设备1采集到满足上肢预设挪动幅度的行为数据、或是在监测到患侧下肢的穿戴式设备1所采集到的行为数据满足下肢预设挪动幅度,并且患者姿势未变化时,患者可能只是需要小幅度调整当前姿势而危险系数较低,确定其为第一模式。The behavior data collected by the wearable device 1 worn on the upper limb on the affected side meets the preset movement range of the upper limb, or the behavior data collected by the wearable device 1 which monitors the lower limb on the affected side meets the preset movement range of the lower limb, and When the patient's posture does not change, the patient may only need to adjust the current posture by a small amount and the risk factor is low, and it is determined as the first mode.
针对“已接受过体位变化指导的被监护对象的运动特征变化趋势以及针对尚未接受过体位变化指导的被监护对象的运动特征变化趋势”:这里所指的体位变化指导主要是指在被监护对象已经住院一段时间,经由监护对象教导其正确合适的翻身或起身姿势。相对地,未接受过体位变化指导主要是指被监护对象刚住院或住院时间不长,尚未进行翻身或起身姿势指导。以此区别出的两种运动特征变化趋势,能够区别出当前被监护对象在脱离监护的情况下更可能出现的动作或行为,能够有效地提高数据比对处理的速度,进一步地提高了对被监护对象的监护准确性以及有效性。For "the change trend of the movement characteristics of the supervised subjects who have received the guidance of body position change and the change trend of the movement characteristics of the supervised subjects who have not received the guidance of the body position change": the body position change guidance referred to here mainly refers to the change of the movement characteristics of the supervised subjects He has been hospitalized for a period of time, and he is taught the correct and appropriate posture for turning over or getting up by the guardian. On the other hand, those who have not received body position change guidance mainly refer to the fact that the supervised object has just been hospitalized or has not been hospitalized for a long time, and has not yet been guided to turn over or get up. The change trends of the two motion characteristics distinguished by this can distinguish the actions or behaviors that are more likely to occur when the currently monitored object is out of monitoring, which can effectively improve the speed of data comparison and processing, and further improve the accuracy of the monitored object. The accuracy and effectiveness of the guardianship of the guardian.
如图1所示出的是本发明所提出的脑卒中偏瘫患者用离床预警系统的简化结构连接关系示意图。Fig. 1 is a schematic diagram showing the simplified structure and connection relationship of the bed-leaving warning system for stroke hemiplegia patients proposed by the present invention.
该系统包括穿戴式设备1,本发明所指的穿戴式设备1主要指的是以手腕和脚踝为支撑的watch类产品形态的设备。如授权公告日为2017年8月29日的公告号CN104524760B的专利文献中所提出的采集模块2,其通过被监护对象在运动时所佩戴的被开启的智能手环,其中内置有能够获取三个方向加速度的三轴陀螺仪传感器,以此实时捕获智能手环/患肢的实时加速度值及振动幅度。其中,穿戴式设备1中内置传感器不限于三轴陀螺仪传感器,任何能够实现检测篮球动作向上加速度和向前加速度及振动幅度的传感器均可,例如重力加速度等。三轴陀螺仪传感器能同时测定六个方向的位置、移动轨迹、加速。穿戴式设备1内置设置模块,用于预先设置抬起、翻转、放下等肢体动作对应的传感器捕获的位置、移动轨迹、加速区间/幅度。The system includes a wearable device 1, and the wearable device 1 referred to in the present invention mainly refers to a device in the form of a watch product supported by a wrist and an ankle. For example, the
该系统包括用于采集被监护对象的行为数据的采集模块2、用于确定风控等级的风控等级划分模块3、用于判断触发预警的预警信息处理器4、用于确定当前摆放姿势的摆放姿势检测模块6、用于预设运动特征变化趋势的行为规则模块5、佩戴于被监护对象患侧的穿戴式设备1、由监护人员携带的移动数字设备7以及内设有处理器和传感器的床垫8。此外,床垫8上布置有用于采集患者压力变化的压力传感器阵列以及与该压力传感器阵列相连接的处理器。在本发明中所提及的上述设备可以均为计算机处理器,图1示出脑卒中偏瘫患者用离床预警系统的简化逻辑流程图,所述逻辑流程图的操作可以表示硬件、计算机指令或其组合实现的一系列操作。在计算机指令的背景下,所述操作表示被存储在一个或多个计算机可读存储介质上的计算机可执行指令,所述计算机可执行指令在被一个或多个计算机处理器执行时执行所述的操作。The system includes a
在监护人员将被监护对象调整至某一摆放姿势的情况下由监护人员通过其操作的移动数字设备7录入或由摆放姿势检测模块6确定调整后的摆放姿势,当被监护对象在床垫8上活动肢体或是自行调节摆放姿势时由设于床垫8上的处理器来获取由多个传感器所采集到的压力变化数据并基于其生成关于被监护对象的压力分布数据以及压力变化数据,该处理器将床垫8上用于分析被监护对象行为趋势、摆放姿势或摆放姿势变化趋势的压力变化相关信息(包括压力分布数据以及压力变化数据)传递至采集模块2。When the guardian adjusts the object to be monitored to a certain posture, it is entered by the guardian through the mobile
穿戴式设备1在被监护对象在床垫8上活动肢体或是自行调节摆放姿势时获取被监护对象的尤其是指患侧上肢与下肢分别对应的且用于提取第一运动特征变化趋势以及第二运动特征变化趋势的行为数据,穿戴式设备1在预设的用于实时地监测患者行为情况的预定时间间隔(可以是指1min或30m in)下将其采集到的行为数据传输至采集模块2。The wearable device 1 obtains the information of the monitored object when the monitored object moves the limbs on the
采集模块2将其获取到的床垫8压力相关信息以及行为数据一并传输至摆放姿势检测模块6,并且采集模块2在获取到由该穿戴式设备1所确定的被监护对象的行为数据时基于该行为数据来生成与各行为数据对应的至少包括上肢预设运动幅度、上肢预设挪动幅度、下肢预设运动幅度以及下肢预设挪动幅度的运动特征值并将其生成的该运动特征值传输至行为规则模块5。The
摆放姿势检测模块6对其接收到数据(床垫8压力相关信息和/或行为数据)进行处理并对处理得到的床垫8上的压力分布情况中是否出现上下明显断层和/或一侧的压力分布相对另一侧是否呈弥散状进行判断进而判断得到被监护对象当前的摆放姿势信息,摆放姿势检测模块6将该摆放姿势信息传输至行为规则模块5与风控等级划分模块3。作为优选的实施方式,此处摆放姿势信息的确定主要是基于设于床垫8上的压力相关信息所确定的或是由护理人员在调整好摆放姿势后手动录入来确定的。The
针对摆放姿势检测模块6进一步举例说明:由于床垫8上设置有压力传感器,通过对压力传感器所采集到的数据进行处理,即可获得当前床垫8上的压力分布情况。如图2所示,当获得的压力分布情况中未出现上下明显断层、并且一侧的压力分布相对另一侧呈弥散状时,基于已知的患者患侧与床垫8之间的相对位置关系(即患者仰躺时患侧更靠近床垫8左侧或右侧的位置关系),摆放姿势检测模块6生成当前患者处于仰卧位的体位摆放姿势的摆放姿势信息。又例如,如图2所示,当获得的压力分布情况中出现上下明显断层、并且一侧的压力分布相对另一侧呈弥散状时,基于已知的患者患侧与床垫8之间的相对位置关系,摆放姿势检测模块6生成当前患者处于健侧卧位或是患侧卧位的体位摆放姿势的摆放姿势信息。其中,“压力分布情况中出现上下明显断层”指的是:由于患者侧卧时需要将一侧上肢与一侧下肢分别搁置在枕头上,尤其是患者的患侧上肢必须完全展开地搭放在枕头上,而不同于正常人群可任意地将两侧上肢放置在距离自己头部/身体较近的位置上,以此,分别搁置在床垫8上下侧的一侧上肢与一侧下肢之间的床垫8未受到压力作用,而出现从压力分布图中观察到的上下之间存在未监测到压力作用的明显断层。并且该明显断层只存在于健侧卧位或是患侧卧位。“一侧的压力分布相对另一侧呈弥散状”指的是从压力分布图中观察可得到相对弥散程度更高的一侧,根据图2所示,相对弥散程度更高是由于伸展开的一侧上肢及下肢搭放在枕头上所引起的,因此可以确定该相对弥散程度更高的一侧为患者伸展开的一侧上肢及下肢所在的床垫8上的一侧。例如,当确定床垫8的左侧上相对弥散程度更高,并且已知患者为右侧上下肢瘫痪时,摆放姿势检测模块6生成当前患者处于患侧卧位的体位摆放姿势的摆放姿势信息。例如,当确定床垫8的右侧上相对弥散程度更高,并且已知患者为右侧上下肢瘫痪时,摆放姿势检测模块6生成当前患者处于健侧卧位的体位摆放姿势的摆放姿势信息。A further example is given for the posture detection module 6: since the
行为规则模块5基于其预设的用于预测保持在某一摆放姿势下的被监护对象在无监护的情况下可能出现的行为的运动特征变化趋势,对其接收到的由所述摆放姿势检测模块6所确定的摆放姿势信息与由所述采集模块2所确定的至少包括第一运动特征值和第二运动特征值的多个运动特征值进行处理并生成至少包括该运动特征值的且用于指示患侧上肢或患侧下肢行为情况的患肢动作数据,并将其传输至预警信息处理器4。The
风控等级划分模块3被配置为在基于监护人员对被监护对象的摆放姿势进行调整后而由监护人员通过其操作的移动数字设备7录入或由摆放姿势检测模块6确定调整后的摆放姿势信息时和/或在基于处于无监护状态下的被监护对象在床垫8上活动肢体或是自行调节摆放姿势后而由摆放姿势检测模块6确定其自行调整后的摆放姿势信息时基于该摆放姿势信息来输出预设的与该摆放姿势相对应的且用于指示患侧肢体运动限制程度的风控等级数据,并将该数据传输至预警信息处理器4。单个风控等级包括某一摆放姿势下单侧肢体运动限制程度。风控等级包括Ⅰ级(基本独立但过高估计自己活动能力)、Ⅱ级(有条件独立或极轻度依赖)、Ⅲ级(中度或重度依赖)和Ⅳ级(极重度或完全依赖)。进一步地,至少两个风控等级被划分为对被监护对象的独立性的评价。Ⅰ级(基本独立但过高估计自己活动能力)和Ⅱ级(有条件独立或极轻度依赖)被划分至被监护对象的独立性较好的评价,Ⅲ级(中度或重度依赖)、Ⅳ级(极重度或完全依赖)被划分至被监护对象的独立性较差的评价。The risk control
预警信息处理器4基于其所接收到的由行为规则模块5所确定的患肢动作数据以及由所述风控等级划分模块3所确定的风控等级数据和/或对被监护对象的独立性评价来判断是否需要针对当前在床垫8上活动肢体或是自行调节摆放姿势的被监护对象进行预警,在判断确定该患肢动作数据满足至少一个运动特征变化趋势中的至少一个模式时即满足预警条件,在触发条件时将该被监护对象的床号、姓名、预警内容等发送至周边的监护人员。The early
优选地,如图3所示,本申请提出了适用于同一侧上下肢均存在运动功能障碍的被监护对象的床垫,至少从传感器分布以及床体可回弹变形能力两方面,来在保证被监护对象的舒适性的同时,还提高了数据获取的有效性和灵敏性。本发明中床垫8上划分有彼此间隔设置且均设置有至少一个传感器的髋骨区域9和肩肘区域10。髋骨区域9对应被监护对象躺卧时臀部所处的区域,该区域沿与人体高度方向相垂直的径向延伸,呈长条状。肩肘区域10对应被监护对象的肩部至手肘之间的区域,该区域沿与人体高度方向相垂直的径向延伸,呈长条状。髋骨区域9所对应的床体可回弹变形能力至少相对肩肘区域10所对应的床体可回弹变形能力更高。Preferably, as shown in FIG. 3 , the present application proposes a mattress suitable for a supervised subject with motor dysfunction on the same side of the upper and lower limbs, at least in terms of the sensor distribution and the resilience and deformability of the bed to ensure While the comfort of the monitored object, it also improves the effectiveness and sensitivity of data acquisition. In the present invention, the
由于髋骨区域9所对应的床体可回弹变形能力更好,能够减轻脑卒中偏瘫患者侧卧或躺卧时髋骨、骶骨等肢体处所承受的压力,利于血液循环的提升以及侧卧挤压对患侧或健侧的伤害的降低。并且本发明所采用的传感器为柔性薄膜网格状触觉压力传感器,这种传感器厚度仅为0.1mm,柔性很好,能够更好地提高检测精度和速度。Because the bed body corresponding to the hip bone area 9 has better resilience and deformation ability, it can reduce the pressure on the hip bone, sacrum and other limbs when the stroke hemiplegia patient is lying on the side or lying down, which is beneficial to the improvement of blood circulation and the compression of the side lying. Decreased damage to the affected or unaffected side. And the sensor used in the present invention is a flexible film grid-like tactile pressure sensor, the thickness of this sensor is only 0.1 mm, the flexibility is good, and the detection accuracy and speed can be better improved.
进一步优选地,肩肘区域10上所设置的传感器分布密度至少相对髋骨区域9上所设置的传感器分布密度更大。由于被监护对象与肩肘区域10之间可能的接触面积远小于被监护对象与髋骨区域9之间可能的接触面积,因此将其传感器分布密度相对提高,以利于检测精度的提升。本发明中所采用的设于床垫8上的传感器优选地为欣佰特科技北京有限公司所生产的Tekscan触觉及压力分布传感器,其硬件包括基于PC机的A/D转换电路和可重复使用的传感器,其结合基于MS Windows的压力显示和分析软件构成压力监测系统,该系统可对任何接触面的压力分布进行静态和动态测量,以直观、形象的二维、三维彩色图象实时显示压力轮廓和各种数据,并对整个测量过程进行录像和/或存储,监护人员可随时对测量记录进行查看、分析。Further preferably, the distribution density of the sensors arranged on the shoulder and
需要注意的是,上述具体实施例是示例性的,本领域技术人员可以在本发明公开内容的启发下想出各种解决方案,而这些解决方案也都属于本发明的公开范围并落入本发明的保护范围之内。本领域技术人员应该明白,本发明说明书及其附图均为说明性而并非构成对权利要求的限制。本发明的保护范围由权利要求及其等同物限定。It should be noted that the above-mentioned specific embodiments are exemplary, and those skilled in the art can come up with various solutions inspired by the disclosure of the present invention, and these solutions also belong to the disclosure scope of the present invention and fall within the scope of the present invention. within the scope of protection of the invention. It should be understood by those skilled in the art that the description of the present invention and the accompanying drawings are illustrative rather than limiting to the claims. The protection scope of the present invention is defined by the claims and their equivalents.
| Application Number | Priority Date | Filing Date | Title |
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| CN202010214132.XACN111387990B (en) | 2020-03-24 | 2020-03-24 | A bed-leaving warning system for stroke patients with hemiplegia |
| CN202211644862.9ACN115969358B (en) | 2020-03-24 | 2020-03-24 | A rehabilitation system for hemiplegic patients after stroke |
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| CN202010214132.XACN111387990B (en) | 2020-03-24 | 2020-03-24 | A bed-leaving warning system for stroke patients with hemiplegia |
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| CN202211644862.9ADivisionCN115969358B (en) | 2020-03-24 | 2020-03-24 | A rehabilitation system for hemiplegic patients after stroke |
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| CN111387990Atrue CN111387990A (en) | 2020-07-10 |
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| CN202010214132.XAActiveCN111387990B (en) | 2020-03-24 | 2020-03-24 | A bed-leaving warning system for stroke patients with hemiplegia |
| CN202211644862.9AActiveCN115969358B (en) | 2020-03-24 | 2020-03-24 | A rehabilitation system for hemiplegic patients after stroke |
| Application Number | Title | Priority Date | Filing Date |
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| CN202211644862.9AActiveCN115969358B (en) | 2020-03-24 | 2020-03-24 | A rehabilitation system for hemiplegic patients after stroke |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113314235A (en)* | 2021-05-19 | 2021-08-27 | 郑州大学 | Real-time data acquisition-based stroke early warning and active intervention system |
| CN113362925A (en)* | 2021-06-29 | 2021-09-07 | 山东第一医科大学附属省立医院(山东省立医院) | Automatic good limb position control method and device |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1927117A (en)* | 2005-09-07 | 2007-03-14 | 首都医科大学宣武医院 | Device for detecting hand movement function and using method thereof |
| US20080169931A1 (en)* | 2007-01-17 | 2008-07-17 | Hoana Medical, Inc. | Bed exit and patient detection system |
| US20150112151A1 (en)* | 2012-02-09 | 2015-04-23 | Masimo Corporation | Patient position detection system |
| CN204515998U (en)* | 2015-04-13 | 2015-07-29 | 金华市中心医院 | Prevent from bed warning system |
| CN105877759A (en)* | 2016-04-01 | 2016-08-24 | 深圳市前海安测信息技术有限公司 | Off-bed monitoring system and method based on Internet of Things |
| CN106456932A (en)* | 2015-04-14 | 2017-02-22 | 华为技术有限公司 | A method, device and terminal equipment for reminding users |
| CN106805952A (en)* | 2015-12-02 | 2017-06-09 | 首都医科大学宣武医院 | Thrombolysis patient safety monitoring and alarm system |
| CN106821388A (en)* | 2016-12-30 | 2017-06-13 | 上海大学 | Cerebral apoplexy patient lower limb rehabilitation quantitative evaluating method |
| US20170224253A1 (en)* | 2016-02-10 | 2017-08-10 | Covidien Lp | Patient bed-exit prediction and detection |
| CN107213003A (en)* | 2017-07-26 | 2017-09-29 | 公安县人民医院 | A kind of Neurology hemiplegic patient mobility aids of lower limb recovery |
| WO2018010644A1 (en)* | 2016-07-12 | 2018-01-18 | 王春宝 | Autonomous training method and system |
| CN109276807A (en)* | 2018-11-18 | 2019-01-29 | 郑州大学 | Functional electrical stimulation therapy device for lower limbs of hemiplegic patients based on mirror rehabilitation therapy |
| CN208823240U (en)* | 2018-04-11 | 2019-05-07 | 重庆医科大学附属第三医院(捷尔医院) | A kind of patient is from bed calling system |
| CN109741834A (en)* | 2018-11-13 | 2019-05-10 | 安徽乐叟健康产业研究中心有限责任公司 | A monitoring system for stroke patients |
| US20190166030A1 (en)* | 2012-12-05 | 2019-05-30 | Origin Wireless, Inc. | Method, apparatus, server and system for vital sign detection and monitoring |
| CN208942643U (en)* | 2018-04-27 | 2019-06-07 | 安阳师范学院 | Intelligent medical mattress system |
| CN109875789A (en)* | 2019-03-26 | 2019-06-14 | 杜振华 | A kind of comprehensive Restoring nursing bed of paralytic |
| CN109963508A (en)* | 2016-10-12 | 2019-07-02 | 皇家飞利浦有限公司 | Method and device for determining fall risk |
| CN109966088A (en)* | 2019-04-11 | 2019-07-05 | 深圳市人民医院 | A clinical early warning system |
| CN209373766U (en)* | 2019-02-28 | 2019-09-10 | 李继华 | A kind of wearable intelligent early-warning monitoring device for preventing high risk of fall |
| US20190307405A1 (en)* | 2018-04-10 | 2019-10-10 | Hill-Rom Services, Inc. | Patient risk assessment based on data from multiple sources in a healthcare facility |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN205594849U (en)* | 2016-04-29 | 2016-09-21 | 泰山医学院 | Prevent tumbleing from bed alarm system |
| US20180228430A1 (en)* | 2017-02-10 | 2018-08-16 | Mindmaze Holding Sa | System, method and apparatus for rehabilitation with tracking |
| CN107982898B (en)* | 2017-12-07 | 2019-07-30 | 苏州脉吉医疗技术有限公司 | The training system and method for rehabilitation exercise |
| CN108814894A (en)* | 2018-04-12 | 2018-11-16 | 山东大学 | The upper limb rehabilitation robot system and application method of view-based access control model human body pose detection |
| CN110123573B (en)* | 2019-04-18 | 2021-10-26 | 华南理工大学 | Rehabilitation robot training system for compensatory movement monitoring and inhibition of hemiplegic upper limb |
| CN110298279A (en)* | 2019-06-20 | 2019-10-01 | 暨南大学 | A kind of limb rehabilitation training householder method and system, medium, equipment |
| CN110880364A (en)* | 2019-09-26 | 2020-03-13 | 华中科技大学协和深圳医院 | Cloud computing intelligent rehabilitation training system and method |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1927117A (en)* | 2005-09-07 | 2007-03-14 | 首都医科大学宣武医院 | Device for detecting hand movement function and using method thereof |
| US20080169931A1 (en)* | 2007-01-17 | 2008-07-17 | Hoana Medical, Inc. | Bed exit and patient detection system |
| US20150112151A1 (en)* | 2012-02-09 | 2015-04-23 | Masimo Corporation | Patient position detection system |
| US20190166030A1 (en)* | 2012-12-05 | 2019-05-30 | Origin Wireless, Inc. | Method, apparatus, server and system for vital sign detection and monitoring |
| CN204515998U (en)* | 2015-04-13 | 2015-07-29 | 金华市中心医院 | Prevent from bed warning system |
| CN106456932A (en)* | 2015-04-14 | 2017-02-22 | 华为技术有限公司 | A method, device and terminal equipment for reminding users |
| CN106805952A (en)* | 2015-12-02 | 2017-06-09 | 首都医科大学宣武医院 | Thrombolysis patient safety monitoring and alarm system |
| US20170224253A1 (en)* | 2016-02-10 | 2017-08-10 | Covidien Lp | Patient bed-exit prediction and detection |
| CN105877759A (en)* | 2016-04-01 | 2016-08-24 | 深圳市前海安测信息技术有限公司 | Off-bed monitoring system and method based on Internet of Things |
| WO2018010644A1 (en)* | 2016-07-12 | 2018-01-18 | 王春宝 | Autonomous training method and system |
| CN109963508A (en)* | 2016-10-12 | 2019-07-02 | 皇家飞利浦有限公司 | Method and device for determining fall risk |
| CN106821388A (en)* | 2016-12-30 | 2017-06-13 | 上海大学 | Cerebral apoplexy patient lower limb rehabilitation quantitative evaluating method |
| CN107213003A (en)* | 2017-07-26 | 2017-09-29 | 公安县人民医院 | A kind of Neurology hemiplegic patient mobility aids of lower limb recovery |
| US20190307405A1 (en)* | 2018-04-10 | 2019-10-10 | Hill-Rom Services, Inc. | Patient risk assessment based on data from multiple sources in a healthcare facility |
| CN208823240U (en)* | 2018-04-11 | 2019-05-07 | 重庆医科大学附属第三医院(捷尔医院) | A kind of patient is from bed calling system |
| CN208942643U (en)* | 2018-04-27 | 2019-06-07 | 安阳师范学院 | Intelligent medical mattress system |
| CN109741834A (en)* | 2018-11-13 | 2019-05-10 | 安徽乐叟健康产业研究中心有限责任公司 | A monitoring system for stroke patients |
| CN109276807A (en)* | 2018-11-18 | 2019-01-29 | 郑州大学 | Functional electrical stimulation therapy device for lower limbs of hemiplegic patients based on mirror rehabilitation therapy |
| CN209373766U (en)* | 2019-02-28 | 2019-09-10 | 李继华 | A kind of wearable intelligent early-warning monitoring device for preventing high risk of fall |
| CN109875789A (en)* | 2019-03-26 | 2019-06-14 | 杜振华 | A kind of comprehensive Restoring nursing bed of paralytic |
| CN109966088A (en)* | 2019-04-11 | 2019-07-05 | 深圳市人民医院 | A clinical early warning system |
| Title |
|---|
| XU, QIAN;LIU, QI;GE, HAITAO: "Tumor recurrence versus treatment effects in glioma A comparative study of three dimensional pseudo-continuous arterial spin labeling and dynamic susceptibility contrast imaging", 《MEDICINE》* |
| 于从,张冬山,陈静莹,申智兰,李丹,梁真,谢小华.: "非接触式监测系统预防老年重症患者跌倒和坠床风险的效果观察", 《岭南急诊医学杂志》* |
| 陈健安: "董氏奇穴治疗中风后上肢痉挛性偏瘫的临床观察", 《万方》* |
| 陈新华,李姗姗,于虹,高兰.: "早期胃癌内镜黏膜下剥离术个体化综合护理模式探讨", 《武警医学》* |
| 高兰,宋泽茹,牟善芳: "卒中后疲劳干预的研究进展", 《中西医结合心脑血管病杂志》* |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113314235A (en)* | 2021-05-19 | 2021-08-27 | 郑州大学 | Real-time data acquisition-based stroke early warning and active intervention system |
| CN113362925A (en)* | 2021-06-29 | 2021-09-07 | 山东第一医科大学附属省立医院(山东省立医院) | Automatic good limb position control method and device |
| CN113362925B (en)* | 2021-06-29 | 2022-04-08 | 山东第一医科大学附属省立医院(山东省立医院) | Automatic good limb position control method and device |
| Publication number | Publication date |
|---|---|
| CN115969358B (en) | 2024-12-10 |
| CN111387990B (en) | 2022-11-04 |
| CN115969358A (en) | 2023-04-18 |
| Publication | Publication Date | Title |
|---|---|---|
| US10849549B2 (en) | Systems, devices, and methods for tracking abdominal orientation and activity | |
| Van de Vel et al. | Non-EEG seizure-detection systems and potential SUDEP prevention: state of the art | |
| El-Bendary et al. | Fall detection and prevention for the elderly: A review of trends and challenges | |
| US9655546B2 (en) | Pressure Ulcer Detection Methods, Devices and Techniques | |
| JP5051767B2 (en) | Device for monitoring human condition parameters | |
| US10264971B1 (en) | System and methods for integrating feedback from multiple wearable sensors | |
| US8647268B2 (en) | Patient monitoring apparatus | |
| EP3295871B1 (en) | Pressure ulcer detection device | |
| CN108670220A (en) | A kind of intellectual monitoring device for assisting health monitoring | |
| KR102239671B1 (en) | Method and system of predicting risk of falling down and dementia through gait information of the aged | |
| AU2006242132A1 (en) | Method and system for wearable vital signs and physiology, activity, and environmental monitoring | |
| JP3225990U (en) | A system for recording, analyzing and providing real-time alerts of accident risk or need for assistance based on continuous sensor signals | |
| CN111916211A (en) | Safety monitoring system and method suitable for disabled old people | |
| WO2022036624A1 (en) | Monitoring method and apparatus, electronic device, and storage medium | |
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| CA3019931A1 (en) | Pressure ulcer detection methods, devices and techniques | |
| US20230113555A1 (en) | Systems, devices, and methods for tracking abdominal orientation and activity for treatment and prevention of pressure sores | |
| Gamboa et al. | Patient tracking system | |
| Leake | Fall detectors for people with dementia | |
| Bobby et al. | Smart glove for elderly patients | |
| US20240081726A1 (en) | Systems, devices, and methods for tracking abdominal orientation and activity for prevention of poor disease outcomes | |
| Naditz | Still standing: Telemedicine devices and fall prevention | |
| Deshpande et al. | Development of a Wearable Technology for the Early Detection of Pressure Ulcers in Nursing Homes | |
| CN119969981A (en) | A health status monitoring system | |
| Aziz | Design and Validation of a Fall Event Detection System using Wearable Sensors: A Machine Learning Approach |
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