Disclosure of Invention
In view of the above problems, the invention provides a wearable intelligent transfusion method and device and a computing device.
According to one aspect of the present invention, there is provided a wearable intelligent infusion method comprising:
The method comprises the steps of pre-scanning a bar code on a patient infusion bag by using a code scanning unit to obtain infusion information, uploading the infusion information to a cloud server, and recommending an optimal infusion scheme by the cloud server based on a pre-trained infusion scheme matching model according to a patient history medical record, current physiological data and medicine information, wherein the optimal infusion scheme comprises the steps of providing a pharmacist examination party, medication risk classification, vein puncture difficulty pre-rating, infusion tool preference level sequencing, a target dropping speed curve and a physiological parameter monitoring threshold according to a machine learning algorithm, wherein the infusion information comprises patient identity information, infusion medication names, medication concentration, dosage, specification, medication methods, medication frequency, medication time, prescribing doctors, examination party pharmacists, static medication information and relevant time node information;
The optimal infusion solution is wirelessly transmitted to a computer and a PDA information receiving system and displayed to a medical staff for confirmation, the medical staff receives infusion information through the PDA and checks the identity of a patient, a nurse evaluates the patient according to the optimal infusion solution and confirms the intravenous puncture difficulty rating, an infusion tool is selected to complete intravenous puncture, the infusion drip speed is initialized through a drip speed control unit, the deviation between the actual drip speed and the target drip speed is monitored in real time by utilizing a PID dynamic drip speed control algorithm, and the output of the drip speed control unit is automatically regulated, wherein when the drip speed deviation exceeds a preset threshold value or the infusion is completed or blocked, a voice alarm is sent out through an automatic voice alarm unit;
The physiological parameters of a patient are monitored by using a multi-parameter physiological monitoring unit, a physiological parameter baseline model is established according to the historical physiological parameters of the patient, deviation between the physiological parameters and the physiological parameter baseline model is evaluated in real time, and when the deviation exceeds a preset threshold value, physiological abnormality is judged and early warning is triggered, wherein the physiological parameters comprise body temperature, heart rate/pulse, respiration, blood pressure and blood oxygen saturation.
In an alternative mode, the dripping speed control unit controls the dripping speed of the transfusion by adopting a peristaltic pump driven by a stepping motor;
calculating a required target flow according to a target drop speed and the drop number per milliliter, and calculating a target rotating speed according to the target flow and the proportional relation;
The rotating speed of the stepping motor is controlled by adjusting the pulse frequency, wherein the controller calculates the required pulse frequency according to the target rotating speed and generates a corresponding pulse signal to drive the stepping motor.
In an alternative, the controller employs a sinusoidal S-curve acceleration and deceleration control algorithm to calculate the required pulse frequency from the target rotational speed;
Wherein the acceleration of the sinusoidal S-curve a (T) =A×sin (pi T/T), the velocity of the sinusoidal S-curveA is the maximum acceleration and T is the acceleration/deceleration time.
In an alternative way, the multi-parameter physiological monitoring unit comprises:
the electrocardiosignal is in contact with the skin of a patient through the wearable conductive patch and is used for collecting electrocardiosignals in real time and calculating the instantaneous heart rate by utilizing the R wave crest value interval in the electrocardiosignals;
The infrared body temperature sensor is integrated in the wrist strap and used for measuring the body surface temperature of a patient in a non-contact mode;
The breath sensor based on the piezoelectric film acquires the breath frequency by detecting the micro deformation of the thoracic cage when the patient breathes;
the noninvasive blood pressure monitoring module is used for inflating and deflating an air bag integrated on the wrist strap through an air pump;
The noninvasive blood oxygen saturation module measures the blood oxygen saturation of a patient through an optical sensor worn on the wrist or finger.
In an alternative mode, the wearable intelligent transfusion device further comprises a detachable transfusion bag fixing device, wherein the transfusion bag fixing device adopts a magnetic connection mode to quickly fix and detach the transfusion bag;
The infusion bag fixing device is provided with a weight sensor for monitoring weight change of the infusion bag in real time and transmitting the weight change to the cloud server, and when abnormal weight change of the infusion bag is detected, an alarm is automatically sent out to prompt medical staff to check infusion equipment.
In an optional mode, a plurality of sensors are arranged in the pipeline of the wearable intelligent infusion device and are used for monitoring the fluid state in the infusion pipeline in real time;
The sensors comprise a pressure sensor and a bubble detection sensor, the dripping speed control unit is automatically adjusted to ensure the stability of infusion when the pressure in the infusion pipeline is detected to be abnormal, and an alarm is automatically sent to prompt medical staff to remove bubbles when the bubbles in the infusion pipeline are detected.
In an optional mode, the wearable intelligent transfusion device is connected with and detached from the replaceable pipeline unit through a buckle structure or a threaded connection mode;
The replaceable pipeline unit consists of a silica gel hose, a dropping funnel, a flow stopping clamp, a pipeline sensor and a venous needle connected with a patient;
The pipeline sensor comprises an optical drop number sensor integrated below the dropping funnel, wherein the optical drop number sensor adopts an infrared LED as a light source, and drops are identified by detecting the light intensity change received by the photodiode.
In an alternative mode, one end of the replaceable pipeline unit is connected with a vein of a patient through a luer connector, and the other end of the replaceable pipeline unit is connected with a detachable interface of the control module through a fastening structure or a threaded connection mode.
According to another aspect of the present invention, there is provided a wearable intelligent infusion device comprising:
the infusion scheme recommendation module is used for pre-scanning a bar code on a patient infusion bag by using the code scanning unit to acquire infusion information, uploading the infusion information to the cloud server, and recommending an optimal infusion scheme according to a patient history medical record, current physiological data and medicine information by the cloud server based on a pre-trained infusion scheme matching model, wherein the optimal infusion scheme comprises the steps of providing a pharmacist examination party, a medicine danger degree grading, a vein puncture difficulty pre-grading, an infusion tool preference level ordering, a target dripping speed curve and a physiological parameter monitoring threshold according to a machine learning algorithm;
the intelligent drip speed control module is used for wirelessly transmitting the optimal infusion scheme to a computer and PDA information receiving system and displaying the optimal infusion scheme to medical staff for confirmation; the medical staff receives transfusion information through a PDA, checks the identity of a patient, evaluates the patient according to an optimal transfusion scheme, confirms the intravenous puncture difficulty rating, selects an infusion tool to complete intravenous puncture, initializes the transfusion dripping speed through a dripping speed control unit, and automatically adjusts the output of the dripping speed control unit by utilizing the deviation of the PID dynamic dripping speed control algorithm to monitor the actual dripping speed and the target dripping speed in real time, wherein when the dripping speed deviation exceeds a preset threshold value or transfusion is completed or blocked, a voice alarm is sent out through an automatic voice alarm unit;
the parameter monitoring and early warning module is used for monitoring physiological parameters of a patient by using the multi-parameter physiological monitoring unit, establishing a physiological parameter baseline model according to the historical physiological parameters of the patient, evaluating deviation between the physiological parameters and the physiological parameter baseline model in real time, and judging physiological abnormality and triggering early warning when the deviation exceeds a preset threshold, wherein the physiological parameters comprise body temperature, heart rate/pulse, respiration, blood pressure and blood oxygen saturation.
According to yet another aspect of the present invention, there is provided a computing device comprising a processor, a memory, a communication interface and a communication bus, the processor, the memory and the communication interface completing communication with each other through the communication bus;
the memory is used for storing at least one executable instruction, and the executable instruction enables the processor to execute the operation corresponding to the wearable intelligent transfusion method.
According to the scheme provided by the invention, a bar code on a patient infusion bag is pre-scanned by a code scanning unit to obtain infusion information, the infusion information is uploaded to a cloud server, the cloud server recommends an optimal infusion scheme according to a patient history medical record, current physiological data and drug information based on a pre-trained infusion scheme matching model, wherein the optimal infusion scheme comprises a target drip speed curve and a physiological parameter monitoring threshold value, the infusion information comprises a drug name, a dosage and a drip speed range, the optimal infusion scheme is wirelessly transmitted to a computer and a PDA information receiving system and is displayed to a medical staff to confirm, the medical staff initializes the drip speed by a drip speed control unit, a PID dynamic drip speed control algorithm is utilized to monitor the deviation of the actual drip speed and the target drip speed in real time and automatically adjust the output of the drip speed control unit, when the drip speed deviation exceeds a preset threshold value or infusion is completed or blocked, a physiological parameter of a patient is monitored by a multi-parameter physiological monitoring unit, a physiological parameter baseline physiological parameter model is established according to the patient physiological parameter of the patient, the physiological parameter monitoring module is real-time estimated, when the deviation of the physiological parameter and the physiological parameter is preset deviation is triggered, and when the physiological parameter deviation exceeds the physiological parameter model is judged to be abnormal, and the physiological parameter monitoring threshold value is abnormal, and the physiological parameter monitoring parameters include the abnormal heart rate and the heart rate is judged. The invention ensures accurate dripping speed in the infusion process by monitoring the deviation of the actual dripping speed and the target dripping speed in real time and automatically adjusting the output of the dripping speed control unit.
The foregoing description is only an overview of the present invention, and is intended to be implemented in accordance with the teachings of the present invention in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present invention more readily apparent.
Detailed Description
Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
Fig. 1 shows a schematic flow chart of a wearable intelligent infusion method according to an embodiment of the invention. Specifically, as shown in fig. 1, the method comprises the following steps:
Step S101, a bar code on a patient infusion bag is pre-scanned by a code scanning unit to obtain infusion information, the infusion information is uploaded to a cloud server, the cloud server recommends an optimal infusion scheme according to a patient history medical record, current physiological data and medicine information based on a pre-trained infusion scheme matching model, the optimal infusion scheme comprises a step of providing a pharmacist examination party, a medicine danger degree classification, a vein puncture difficulty pre-classification, a transfusion tool preference level ranking, a target dropping speed curve and a physiological parameter monitoring threshold according to a machine learning algorithm, and the infusion information comprises patient identity information, infusion medicine names, medicine concentrations, dosages, specifications, a medicine method, medicine frequency, medicine time, a prescribing doctor, an examination party pharmacist, static allocation medicine information and relevant time node information.
In the embodiment, the infusion information is automatically acquired through the code scanning unit, so that the information input efficiency is improved, the cloud server recommends an optimal infusion scheme by combining the historical medical history of a patient, the current physiological data and the medicine information based on a pre-trained infusion scheme matching model, and real personalized infusion is realized.
Specifically, the bar code scanning gun or the camera of the wearable equipment is integrated with the code scanning unit, so that the bar code on the infusion bag can be read to acquire the infusion information therein. The bar code contains information such as drug name, dosage, production lot number, expiration date, etc. The code scanning unit uploads the acquired infusion information to the cloud server through a wireless network (such as Wi-Fi, bluetooth or mobile network). The cloud server stores patient medical record data, physiological data, drug information and a pre-trained infusion scheme matching model. The infusion solution matching model establishes a mapping relationship between the infusion solution and the patient characteristics by learning a large amount of historical data. The training data of the model includes the patient's history (diagnosis, past history, allergy history), the patient's physiological data (age, sex, body weight, body temperature, heart rate, blood pressure), drug information (drug name, concentration, dosage, indication, contraindications) and infusion protocol (drip rate, infusion time, infusion frequency, physiological parameter monitoring threshold). And the cloud server extracts information such as medicine names, doses and the like from the infusion information after receiving the infusion information, and inputs the information into the infusion scheme matching model by combining the historical medical records and the current physiological data of the patient. The infusion scheme matching model recommends an optimal infusion scheme according to the input information, wherein the optimal infusion scheme comprises a target drip rate curve and a physiological parameter monitoring threshold value. The target drip speed curve describes the change rule of the drip speed along with time in the infusion process, and is adjusted according to the illness state of a patient. And the cloud server transmits the recommended optimal infusion scheme to the computer and PDA information receiving system through a wireless network.
For example, when a 65 year old patient suffering from hypertension and diabetes is infused, a healthcare worker scans a bar code on an infusion bag using a code scanning unit to acquire a drug name (glucose sodium chloride injection), a dose (500 ml) and a drip rate range (20-40 drops/min). And the code scanning unit uploads the information to the cloud server. The cloud server receives the information, extracts the information such as the medicine name and the dosage, and combines the history medical records (hypertension and diabetes) of the patient and the current physiological data (160/100 mmHg and 80 times/min heart rate) to input the information into the infusion scheme matching model. The infusion scheme matching model recommends an optimal infusion scheme according to the input information.
Wherein, the target dropping speed curve is:
0-30 min, 25 drops/min
30-60 Min, 30 drops/min
60-90 Min, 35 drops/min
90-120 Min 30 drops/min
After 120 minutes, 25 drops/min
The physiological parameter monitoring threshold is:
The upper limit of blood pressure is 170/110mmHg
Blood pressure limit 110/70mmHg
Upper limit of heart rate 100 times/min
Heart rate lower limit 60 times/min
And the cloud server transmits the optimal infusion scheme to a computer and PDA information receiving system for confirmation by a pharmacist.
Step S102, the optimal infusion solution is wirelessly transmitted to a computer and a PDA information receiving system and displayed to a medical staff for confirmation, the medical staff receives infusion information through the PDA and checks the identity of a patient, a nurse evaluates the patient according to the optimal infusion solution and confirms the intravenous puncture difficulty rating, an infusion tool is selected to complete intravenous puncture, the infusion solution dripping speed is initialized through a dripping speed control unit, the deviation between the actual dripping speed and the target dripping speed is monitored in real time through a PID dynamic dripping speed control algorithm, the output of the dripping speed control unit is automatically adjusted, and when the dripping speed deviation exceeds a preset threshold value or infusion is completed or blocked, a voice alarm is sent out through an automatic voice alarm unit.
In the embodiment, the optimal infusion scheme is wirelessly transmitted to the computer and the PDA, so that errors in information transmission are reduced, and the time of medical staff is saved. The manual adjustment of the drip speed is easily influenced by subjective factors, and the PID dynamic drip speed control algorithm can accurately control the drip speed of infusion, reduce human errors and ensure the accuracy and safety of infusion. The infusion speed deviation, the infusion completion and the blockage are monitored in real time, medical staff is timely reminded through voice alarm, and the safety of the infusion process is enhanced.
For example, a resident who needs to infuse an antibiotic, a doctor may prescribe an infusion regimen for him that includes a particular drip rate profile. The cloud server matches the optimal transfusion scheme according to the prescription of a doctor and the medical history of a patient, wherein the optimal transfusion scheme comprises qualified antibiotic names, doses and medical chefs, medication risk classification II, vein puncture difficulty pre-classification III, transfusion tool optimization level sequencing (peripheral vein short catheter-peripheral vein indwelling needle-7-number common transfusion needle), target drip speed curve (first 30 minutes 20 drops/min, next 60 minutes 15 drops/min and last 30 minutes 10 drops/min) and physiological parameter monitoring threshold (heart rate exceeds 120 times/min alarm, blood pressure is lower than 90/60mmHg alarm). The solution is transmitted over a wireless network to the nurse station's computer and the nurse's hand-held PDA. After a nurse confirms the scheme on the PDA, checking the identity of the patient, clicking the 'patient assessment' by the nurse according to the optimal infusion scheme, confirming that the intravenous puncture difficulty rating is adjusted to be IV level, clicking the 'infusion tool to select' to jump to start infusion, completing intravenous puncture, and clicking the 'successful puncture' by the nurse on the PDA. The PDA sends the initial drip rate (20 drops/min) to the drip rate control unit of the wearable intelligent infusion device, at which speed the peristaltic pump begins to operate. During infusion, the optical drop rate sensor continuously monitors the actual drop rate and feeds data back to the controller. If the actual drip rate deviates from the target drip rate by more than 2 drops/min, the PID algorithm automatically adjusts the rotational speed of the peristaltic pump to maintain the drip rate steady. If the pressure sensor detects that the pipeline pressure suddenly rises in the infusion process, the pipeline is blocked, and the voice alarm unit sends out a voice prompt of 'pipeline blocking, please check', so as to remind nurses of timely treatment. When the infusion bag approaches to the empty bag, the weight sensor detects the weight change, and the voice alarm unit sends out a voice prompt that the infusion is about to be completed and the replacement is about to be performed.
In an alternative mode, the dripping speed control unit controls the dripping speed of the transfusion by adopting a peristaltic pump driven by a stepping motor;
calculating a required target flow according to a target drop speed and the drop number per milliliter, and calculating a target rotating speed according to the target flow and the proportional relation;
The rotating speed of the stepping motor is controlled by adjusting the pulse frequency, wherein the controller calculates the required pulse frequency according to the target rotating speed and generates a corresponding pulse signal to drive the stepping motor.
In the embodiment, the peristaltic pump is used for conveying through the extrusion hose, and liquid only contacts with the inner wall of the hose, so that contact with other parts of the pump body is avoided, pollution risk is reduced, and sterility of transfusion is guaranteed. The rotating speed of the stepping motor is controlled by adjusting the pulse frequency, so that the stepping motor is conveniently in digital connection with the controller. For example, a drug may need to be infused at 15 drops/min and the infusion set may be 20 drops per ml. The flow coefficient of the peristaltic pump is 0.5 ml/turn, and the step angle of the stepping motor is 1.8 degrees. Target flow = 15/min/20/ml = 0.75 ml/min, target rotational speed = 0.75 ml/min/0.5 ml/revolution = 1.5 revolutions/min (RPM), pulse frequency = 360 degrees/revolution/1.8 degrees/step = 200 steps/revolution, pulse frequency = 1.5 revolutions/min 200 steps/revolution/60 seconds/min = 5Hz. The controller generates a pulse signal with the frequency of 5Hz and inputs the pulse signal to the stepping motor driver, and the stepping motor driver drives the stepping motor to rotate at the speed of 1.5 revolutions per minute, so that the peristaltic pump is driven to deliver the medicine at the flow rate of 0.75 milliliter per minute, namely 15 drops per minute.
In an alternative, the controller employs a sinusoidal S-curve acceleration and deceleration control algorithm to calculate the required pulse frequency from the target rotational speed;
Wherein the acceleration of the sinusoidal S-curve a (T) =A×sin (pi T/T), the velocity of the sinusoidal S-curveA is the maximum acceleration and T is the acceleration/deceleration time.
In this embodiment, the sinusoidal S-curve has better smoothness than acceleration and deceleration curves such as trapezoidal curves and exponential curves. Since the change in acceleration is continuous (sinusoidal function), shocks and vibrations due to abrupt changes in acceleration are avoided. In the intelligent infusion system, the infusion system has more accurate dripping speed control, and avoids discomfort to a patient caused by severe fluctuation of the infusion speed. And simultaneously, noise caused by abrupt acceleration when the stepping motor operates is reduced.
Step S103, monitoring physiological parameters of a patient by using a multi-parameter physiological monitoring unit, establishing a physiological parameter baseline model according to the historical physiological parameters of the patient, evaluating deviation between the physiological parameters and the physiological parameter baseline model in real time, and judging physiological abnormality and triggering early warning when the deviation exceeds a preset threshold, wherein the physiological parameters comprise body temperature, heart rate/pulse, respiration, blood pressure and blood oxygen saturation.
In the embodiment, by establishing the physiological parameter baseline model of the patient, physiological abnormality is found earlier, and even if the current physiological parameter is still in a normal range, obvious deviation occurs relative to the baseline of the patient, and early warning can be performed in time. The physiological parameter baseline model of each patient is established based on the historical data, so that the physiological fluctuation in the normal range can be prevented from being misjudged as abnormal.
In an alternative way, the multi-parameter physiological monitoring unit comprises:
the electrocardiosignal is in contact with the skin of a patient through the wearable conductive patch and is used for collecting electrocardiosignals in real time and calculating the instantaneous heart rate by utilizing the R wave crest value interval in the electrocardiosignals;
The infrared body temperature sensor is integrated in the wrist strap and used for measuring the body surface temperature of a patient in a non-contact mode;
The breath sensor based on the piezoelectric film acquires the breath frequency by detecting the micro deformation of the thoracic cage when the patient breathes;
the noninvasive blood pressure monitoring module is used for inflating and deflating an air bag integrated on the wrist strap through an air pump;
The noninvasive blood oxygen saturation module measures the blood oxygen saturation of a patient through an optical sensor worn on the wrist or finger.
In this embodiment, non-invasive methods such as wearable conductive patches, infrared body temperature sensors, and piezoelectric films are employed to reduce discomfort to the patient. The monitoring is convenient for patients at any time and any place, and is suitable for inpatients and outpatients.
In an alternative mode, the wearable intelligent transfusion device further comprises a detachable transfusion bag fixing device, wherein the transfusion bag fixing device adopts a magnetic connection mode to quickly fix and detach the transfusion bag;
The infusion bag fixing device is provided with a weight sensor for monitoring weight change of the infusion bag in real time and transmitting the weight change to the cloud server, and when abnormal weight change of the infusion bag is detected, an alarm is automatically sent out to prompt medical staff to check infusion equipment.
In the embodiment, the magnetic connection mode is adopted, so that medical staff can conveniently and rapidly fix and detach the infusion bag, and the operation time is saved. The weight change of the infusion bag is monitored in real time through the weight sensor, so that the infusion amount is calculated and transmitted to the cloud server, and the accurate monitoring of the infusion amount is realized. When abnormal weight change of the infusion bag is detected, for example, the infusion speed is too high or too low, the infusion is stopped or the infusion bag leaks, an alarm is automatically sent out, medical staff is prompted to check infusion equipment in time, and the safety of patients is guaranteed. For example, the infusion bag fixing device adopts a magnetic connection mechanism, and comprises a magnet arranged on the fixing device and a metal sheet or a magnetic material arranged on the infusion bag. The infusion bag is firmly fixed on the fixing device through magnetic force. The infusion bag fixing device is provided with a weight sensor for monitoring the weight change of the infusion bag in real time. The weight sensor is connected with the data transmission module, and the data transmission module transmits the acquired weight data to the cloud server through wireless communication. The cloud server processes and analyzes the weight data after receiving the weight data, calculates the infusion amount and the infusion speed according to the weight change, compares the infusion amount and the infusion speed with a preset infusion scheme, and judges whether an abnormality exists or not. When the infusion quantity or infusion speed is detected to be excessively large with the preset scheme or the weight change is abnormal, an alarm system is triggered, and an alarm is sent out through a computer, a PDA or a wearable intelligent infusion device to prompt medical staff.
In an optional mode, a plurality of sensors are arranged in the pipeline of the wearable intelligent infusion device and are used for monitoring the fluid state in the infusion pipeline in real time;
The sensors comprise a pressure sensor and a bubble detection sensor, the dripping speed control unit is automatically adjusted to ensure the stability of infusion when the pressure in the infusion pipeline is detected to be abnormal, and an alarm is automatically sent to prompt medical staff to remove bubbles when the bubbles in the infusion pipeline are detected.
In this embodiment, air embolism caused by air entering the patient body is avoided by detecting air bubbles, and whether the infusion pipeline is blocked or pressed is judged by detecting abnormal pressure so as to automatically adjust the dropping speed. When pressure abnormality or bubbles are detected, an alarm is timely sent out to prompt medical staff to intervene, and potential risks of patients are reduced.
Specifically, a miniature pressure sensor is integrated below a dropping funnel of the infusion pipeline or near a patient end, and the pressure inside the pipeline is monitored in real time and data is transmitted to a control module. When the pipeline is blocked, the pressure can rise, and the pressure sensor detects that the pressure rises to trigger an alarm and automatically reduce or stop the dripping speed. When the pipeline is extruded, the pressure is reduced, and the pressure sensor detects that the pressure is reduced to trigger an alarm and automatically adjust the dripping speed. And a bubble detection sensor (an ultrasonic or optical sensor) is integrated below the dropping funnel or at the position of the pipeline, and is used for monitoring whether bubbles exist in the pipeline in real time and transmitting data to the control module. When detecting that the air bubble passes, an alarm is immediately triggered to prompt medical staff to remove the air bubble and prevent air embolism. The data of the pressure sensor and the bubble detection sensor are linked with the dripping speed control unit, and when the pressure is too high or too low, the dripping speed control unit automatically adjusts the rotating speed of the peristaltic pump to maintain stable dripping speed. When the bubble is detected, the peristaltic pump is stopped immediately to give an alarm, and the infusion is manually or automatically resumed after the bubble is removed.
In an optional mode, the wearable intelligent transfusion device is connected with and detached from the replaceable pipeline unit through a buckle structure or a threaded connection mode;
The replaceable pipeline unit consists of a silica gel hose, a dropping funnel, a flow stopping clamp, a pipeline sensor and a venous needle connected with a patient;
The pipeline sensor comprises an optical drop number sensor integrated below the dropping funnel, wherein the optical drop number sensor adopts an infrared LED as a light source, and drops are identified by detecting the light intensity change received by the photodiode.
In this embodiment, as shown in fig. 2, the fastening structure or the threaded connection reduces the time for replacing the pipeline unit, so as to avoid cross infection among different patients. The optical drop number sensor 2 adopts a non-contact measurement mode, so that direct interference on dropping liquid is avoided.
Specifically, the wearable intelligent transfusion device is provided with a convex buckle, and the replaceable pipeline unit is provided with a corresponding clamping groove. The clamping groove is aligned with the buckle and pressed during connection. When the detachable type electric bicycle is detached, the release button on the clip is pressed down to be separated. Or the wearable intelligent transfusion device is provided with a threaded interface, and the replaceable pipeline unit is provided with a corresponding threaded cap. When in connection, the luer connector is aligned with the threaded interface, and is screwed down by clockwise rotation and unscrewed by anticlockwise rotation when being disassembled. The silica gel hose 1 has good biocompatibility and flexibility and is used for connecting an infusion bag, a drip chamber and a vein needle. The flow stop clip is used for manually adjusting or stopping infusion, a venous needle is connected with a needle (such as a butterfly wing needle) of a vein of a patient, and the venous needle is connected with a luer connector 3 and various venous access. The photodiode is used as a light receiver and is positioned at the other side of the dropping funnel to receive infrared light. When no drip passes, the light intensity received by the photodiode is high. As the drop passes, the intensity of light received by the photodiode decreases due to refraction and absorption of light by the liquid. The frequency of the drop is accurately identified by detecting the frequency of the light intensity change, so that the drop speed is calculated. One end of the replaceable pipeline unit is connected with the vein of the patient through the luer connector 3, and the other end of the replaceable pipeline unit is connected with the detachable interface of the control module through a fastening structure or a threaded connection mode.
According to the scheme provided by the invention, a bar code on a patient infusion bag is pre-scanned by a code scanning unit to obtain infusion information, the infusion information is uploaded to a cloud server, the cloud server recommends an optimal infusion scheme according to a patient history medical record, current physiological data and drug information based on a pre-trained infusion scheme matching model, wherein the optimal infusion scheme comprises a target drip speed curve and a physiological parameter monitoring threshold value, the infusion information comprises a drug name, a dosage and a drip speed range, the optimal infusion scheme is wirelessly transmitted to a computer and a PDA information receiving system and is displayed to a medical staff to confirm, the medical staff initializes the drip speed by a drip speed control unit, a PID dynamic drip speed control algorithm is utilized to monitor the deviation of the actual drip speed and the target drip speed in real time and automatically adjust the output of the drip speed control unit, when the drip speed deviation exceeds a preset threshold value or infusion is completed or blocked, a physiological parameter of a patient is monitored by a multi-parameter physiological monitoring unit, a physiological parameter baseline physiological parameter model is established according to the patient physiological parameter of the patient, the physiological parameter monitoring module is real-time estimated, when the deviation of the physiological parameter and the physiological parameter is preset deviation is triggered, and when the physiological parameter deviation exceeds the physiological parameter model is judged to be abnormal, and the physiological parameter monitoring threshold value is abnormal, and the physiological parameter monitoring parameters include the abnormal heart rate and the heart rate is judged. The invention ensures accurate dripping speed in the infusion process by monitoring the deviation of the actual dripping speed and the target dripping speed in real time and automatically adjusting the output of the dripping speed control unit.
Fig. 3 shows a schematic frame diagram of a wearable intelligent infusion device of an embodiment of the invention. Wearable intelligent infusion device includes:
The infusion solution recommendation module 310 is used for pre-scanning a bar code on a patient infusion bag by using the code scanning unit, uploading the infusion solution to the cloud server, and recommending an optimal infusion solution according to a patient history, current physiological data and drug information based on a pre-trained infusion solution matching model, wherein the optimal infusion solution comprises a target drip rate curve and a physiological parameter monitoring threshold value, the infusion solution comprises a drug name, a dosage and a drip rate range, the intelligent drip rate control module is used for wirelessly transmitting the optimal infusion solution to a computer and a PDA information receiving system and displaying the optimal infusion solution to a medical staff for confirmation, the medical staff initializes the drip rate by using the drip rate control unit, and automatically adjusts the output of the drip rate control unit by utilizing a PID dynamic drip rate control algorithm to monitor the deviation of the actual drip rate and the target drip rate in real time, and when the drip rate deviation exceeds the preset threshold value or the infusion is completed or blocked, the medical staff sends a voice alarm by using the automatic voice alarm unit;
The intelligent drip speed control module 320 is used for wirelessly transmitting the optimal infusion solution to a computer and PDA information receiving system and displaying the optimal infusion solution to a medical staff for confirmation; the medical staff receives transfusion information through a PDA, checks the identity of a patient, evaluates the patient according to an optimal transfusion scheme, confirms the intravenous puncture difficulty rating, selects an infusion tool to complete intravenous puncture, initializes the transfusion dripping speed through a dripping speed control unit, and automatically adjusts the output of the dripping speed control unit by utilizing the deviation of the PID dynamic dripping speed control algorithm to monitor the actual dripping speed and the target dripping speed in real time, wherein when the dripping speed deviation exceeds a preset threshold value or transfusion is completed or blocked, a voice alarm is sent out through an automatic voice alarm unit;
The parameter monitoring and early warning module 330 is configured to monitor physiological parameters of a patient by using the multi-parameter physiological monitoring unit, establish a physiological parameter baseline model according to historical physiological parameters of the patient, evaluate deviation between the physiological parameters and the physiological parameter baseline model in real time, and determine physiological abnormality and trigger early warning when the deviation exceeds a preset threshold, wherein the physiological parameters include body temperature, heart rate/pulse, respiration, blood pressure and blood oxygen saturation.
FIG. 4 illustrates a schematic diagram of an embodiment of a computing device of the present invention, and the embodiments of the present invention are not limited to a particular implementation of the computing device.
As shown in FIG. 4, the computing device may include a processor 402, a communication interface (Communications Interface) 404, a memory 406, and a communication bus 408.
Wherein processor 402, communication interface 404, and memory 406 communicate with each other via communication bus 408. A communication interface 404 for communicating with network elements of other devices, such as clients or other servers. The processor 402 is configured to execute the program 410, and may specifically perform relevant steps in the wearable intelligent infusion method embodiment described above.
In particular, program 410 may include program code including computer-operating instructions.
The processor 402 may be a central processing unit CPU, or an Application-specific integrated Circuit ASIC (Application SPECIFIC INTEGRATED Circuit), or one or more integrated circuits configured to implement embodiments of the present invention. The computing device may include one or more processors of the same type, such as one or more CPUs, or of different types, such as one or more CPUs and one or more ASICs.
Memory 406 for storing programs 410. Memory 406 may comprise high-speed RAM memory or may also include non-volatile memory (non-volatile memory), such as at least one disk memory.
According to the scheme provided by the invention, a bar code on a patient infusion bag is pre-scanned by a code scanning unit to obtain infusion information, the infusion information is uploaded to a cloud server, the cloud server recommends an optimal infusion scheme according to a patient history medical record, current physiological data and drug information based on a pre-trained infusion scheme matching model, wherein the optimal infusion scheme comprises a target drip speed curve and a physiological parameter monitoring threshold value, the infusion information comprises a drug name, a dosage and a drip speed range, the optimal infusion scheme is wirelessly transmitted to a computer and a PDA information receiving system and is displayed to a medical staff to confirm, the medical staff initializes the drip speed by a drip speed control unit, a PID dynamic drip speed control algorithm is utilized to monitor the deviation of the actual drip speed and the target drip speed in real time and automatically adjust the output of the drip speed control unit, when the drip speed deviation exceeds a preset threshold value or infusion is completed or blocked, a physiological parameter of a patient is monitored by a multi-parameter physiological monitoring unit, a physiological parameter baseline physiological parameter model is established according to the patient physiological parameter of the patient, the physiological parameter monitoring module is real-time estimated, when the deviation of the physiological parameter and the physiological parameter is preset deviation is triggered, and when the physiological parameter deviation exceeds the physiological parameter model is judged to be abnormal, and the physiological parameter monitoring threshold value is abnormal, and the physiological parameter monitoring parameters include the abnormal heart rate and the heart rate is judged. The invention ensures accurate dripping speed in the infusion process by monitoring the deviation of the actual dripping speed and the target dripping speed in real time and automatically adjusting the output of the dripping speed control unit.
Those skilled in the art will appreciate that the modules in the apparatus of the embodiments may be adaptively changed and disposed in one or more apparatuses different from the embodiments. The modules or units or components of the embodiments may be combined into one module or unit or component and, furthermore, they may be divided into a plurality of sub-modules or sub-units or sub-components. Any combination of all features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or units of any method or apparatus so disclosed, may be used in combination, except insofar as at least some of such features and/or processes or units are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings), may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise. Furthermore, those skilled in the art will appreciate that while some embodiments herein include some features but not others included in other embodiments, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments can be used in any combination. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The steps in the above embodiments should not be construed as limiting the order of execution unless specifically stated.