技术领域technical field
本发明涉及信息处理技术领域，尤其涉及一种饮食信息监控方法及装置。The invention relates to the technical field of information processing, in particular to a diet information monitoring method and device.
背景技术Background technique
随着社会的发展，人们对于健康的关注越来越重视。例如，儿女通常会担心独自在家的老人的健康、也会担心儿童在幼儿园或学校的健康，具体的如担心这些人群的饮食健康等。在现有技术中，用户可能通过安装在家里或学校的监控了解上述人群的一些活动，从而粗略的确定这些人群的饮食健康等。但是显然这些准确度和精确度都很低，不能够精确有效的反应这些人群的饮食等各方面的信息。With the development of society, people pay more and more attention to health. For example, children usually worry about the health of the elderly who are alone at home, and also worry about the health of children in kindergartens or schools. Specifically, they worry about the diet health of these groups of people. In the prior art, the user may know some activities of the above-mentioned groups of people through monitoring installed at home or school, so as to roughly determine the eating health of these groups of people. However, it is obvious that these accuracy and precision are very low, and cannot accurately and effectively reflect the diet and other information of these groups of people.
发明内容Contents of the invention
有鉴于此，本发明实施例期望提供一种饮食信息监控方法及装置，至少能够解决对特定用户的饮食信息的监控精确低的问题。In view of this, the embodiment of the present invention expects to provide a diet information monitoring method and device, which can at least solve the problem of low accuracy in monitoring the diet information of a specific user.
为达到上述目的，本发明实施例的技术方案是这样实现的：In order to achieve the above object, the technical solution of the embodiment of the present invention is achieved in this way:
本发明实施例第一方面提供一种饮食信息监控方法，所述方法包括：The first aspect of the embodiments of the present invention provides a method for monitoring dietary information, the method comprising:
检测特定用户的手部动作信息；Detect hand movement information of a specific user;
若所述手部动作信息满足预设饮食手势识别算法时，采集所述特定用户的手部图像；If the hand movement information satisfies the preset eating gesture recognition algorithm, collect the hand image of the specific user;
基于所述手部图像判断所述特定用户是否处于饮食状态，形成判断结果；judging whether the specific user is in a state of eating or drinking based on the hand image, and forming a judging result;
将所述判断结果发送给远端设备。Send the judgment result to the remote device.
基于上述方案，所述检测特定用户的手部动作信息，包括：Based on the above scheme, the detection of hand movement information of a specific user includes:
利用手部可穿戴式设备检测所述手部动作信息；Using a hand wearable device to detect the hand movement information;
所述采集所述特定用户的手部图像，包括：The collecting the hand image of the specific user includes:
利用所述手部可穿戴式设备采集所述特定用户的饮食图像数据。The diet image data of the specific user is collected by using the hand wearable device.
基于上述方案，所述基于所述手部图像判断所述特定用户是否处于饮食状态，形成判断结果，包括：Based on the above scheme, the judging whether the specific user is in a state of eating or drinking based on the hand image to form a judging result includes:
判断所述手部图像中是否有指定图像对象；所述指定图像对象包括饮食用具、饮品和食品的至少其中之一；Judging whether there is a specified image object in the hand image; the specified image object includes at least one of eating utensils, drinks and food;
若所述手部图像中包括所述指定图像对象，确定所述特定用户处于饮食状态；If the specified image object is included in the hand image, determine that the specific user is in a state of eating and drinking;
若所述手部图像中不包括所述指定图像对象，确定所述特定用户处于非饮食状态。If the specified image object is not included in the hand image, it is determined that the specific user is in a non-eating state.
基于上述方案，所述若所述手部图像中包括所述指定图像对象，确定所述特定用户处于饮食状态，包括：Based on the above scheme, if the specified image object is included in the hand image, determining that the specific user is in a state of eating and drinking includes:
若所述手部图像中的所述指定图像对象出现在所述特定用户的嘴边，则确定所述特定用户处于所述饮食状态。If the designated image object in the hand image appears near the mouth of the specific user, it is determined that the specific user is in the diet state.
基于上述方案，所述若所述手部图像中的所述指定图像对象出现在所述特定用户的嘴边，则确定所述特定用户处于所述饮食状态，包括：Based on the above solution, if the specified image object in the hand image appears on the mouth of the specific user, then determining that the specific user is in the eating state includes:
若所述手部图像中所述指定图像对象出现在所述特定用户嘴边的概率大于指定概率，则确定所述特定用户处于正常饮食状态。If the probability of the specified image object appearing on the mouth of the specific user in the hand image is greater than the specified probability, it is determined that the specific user is in a normal eating state.
本发明实施例第二方面提供一种饮食信息监控装置，所述装置包括：The second aspect of the embodiment of the present invention provides a diet information monitoring device, the device includes:
检测单元，用于检测特定用户的手部动作信息；A detection unit, configured to detect hand movement information of a specific user;
采集单元，用于若所述手部动作信息满足预设饮食手势识别算法时，采集所述特定用户的手部图像；A collection unit, configured to collect the hand image of the specific user if the hand movement information satisfies a preset eating and drinking gesture recognition algorithm;
判断单元，用于基于所述手部图像判断所述特定用户是否处于饮食状态，形成判断结果；a judging unit, configured to judge whether the specific user is in a state of eating or drinking based on the hand image, and form a judging result;
发送单元，用于将所述判断结果发送给远端设备。A sending unit, configured to send the judgment result to the remote device.
基于上述方案，所述检测单元，具体用于利用手部可穿戴式设备检测所述手部动作信息；Based on the above scheme, the detection unit is specifically configured to detect the hand movement information by using a wearable hand device;
所述采集单元，用于利用所述手部可穿戴式设备采集所述特定用户的饮食 图像数据。The collection unit is configured to use the hand wearable device to collect the diet image data of the specific user.
基于上述方案，所述判断单元，具体用于判断所述手部图像中是否有指定图像对象；所述指定图像对象包括饮食用具、饮品和食品的至少其中之一；若所述手部图像中包括所述指定图像对象，确定所述特定用户处于饮食状态；若所述手部图像中不包括所述指定图像对象，确定所述特定用户处于非饮食状态。Based on the above scheme, the judging unit is specifically configured to judge whether there is a specified image object in the hand image; the specified image object includes at least one of eating utensils, drinks and food; if the hand image contains If the specified image object is included, it is determined that the specific user is in an eating state; if the specified image object is not included in the hand image, it is determined that the specific user is in a non-eating state.
基于上述方案，所述判断单元，具体用于若所述手部图像中的所述指定图像对象出现在所述特定用户的嘴边，则确定所述特定用户处于所述饮食状态。Based on the above solution, the judging unit is specifically configured to determine that the specific user is in the eating state if the specified image object in the hand image appears near the specific user's mouth.
基于上述方案，所述判断单元，具体用于若所述手部图像中所述指定图像对象出现在所述特定用户嘴边的概率大于指定概率，则确定所述特定用户处于正常饮食状态。Based on the above solution, the judging unit is specifically configured to determine that the specific user is in a normal eating state if the probability of the specified image object appearing on the mouth of the specific user in the hand image is greater than a specified probability.
本发明实施例提供的饮食信息监控方法及装置，将采集特定用户的手部动作信息，并在手部动作信息满足饮食手势识别算法时，开启图像采集以采集特定用户的手部图像，再根据手部图像确定特定用户是否处于饮食状态，再发送给远端设备。结合手部动作信息及手部图像，能够精确的远程监控特定用户是否处于饮食状态，相对于在房间内安装监控设备，显然监控结果准确度和精确度得到了大大的提升。The diet information monitoring method and device provided by the embodiments of the present invention will collect the hand movement information of a specific user, and when the hand movement information satisfies the diet gesture recognition algorithm, start image acquisition to collect the hand image of the specific user, and then according to The image of the hand determines whether a particular user is eating or not, and then sends it to the remote device. Combined with hand movement information and hand images, it is possible to accurately remotely monitor whether a specific user is eating or drinking. Compared with installing monitoring equipment in the room, the accuracy and precision of the monitoring results have been greatly improved.
附图说明Description of drawings
图1为本发明实施例提供的第一种饮食监控方法的流程示意图；Fig. 1 is a schematic flow chart of the first diet monitoring method provided by the embodiment of the present invention;
图2为本发明实施例提供的饮食监控装置的流程示意图；2 is a schematic flow diagram of a diet monitoring device provided by an embodiment of the present invention;
图3为本发明实施例提供的手部可穿戴式设备的结构示意图；Fig. 3 is a schematic structural diagram of a hand wearable device provided by an embodiment of the present invention;
图4本发明实施例提供的手部动作信息监控的效果示意图；Fig. 4 is a schematic diagram of the effect of hand movement information monitoring provided by the embodiment of the present invention;
图5为本发明实施例提供的第二种饮食监控方法的流程示意图。Fig. 5 is a schematic flowchart of a second diet monitoring method provided by an embodiment of the present invention.
具体实施方式detailed description
为使本发明的目的、技术方案和优点更加清楚明白，以下举实施例并参照附图，对本发明进一步详细说明。In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail by citing the following embodiments and referring to the accompanying drawings.
实施例一：Embodiment one:
如图1所示，本实施例一种饮食信息监控方法，所述方法包括：As shown in Figure 1, a method for monitoring dietary information in this embodiment, the method includes:
步骤S110：检测特定用户的手部动作信息；Step S110: Detecting hand movement information of a specific user;
步骤S120：若所述手部动作信息满足预设饮食手势识别算法时，采集所述特定用户的手部图像；Step S120: If the hand movement information satisfies the preset eating gesture recognition algorithm, collect the hand image of the specific user;
步骤S130：基于所述手部图像判断所述特定用户是否处于饮食状态，形成判断结果；Step S130: judge whether the specific user is in a state of eating or drinking based on the hand image, and form a judgment result;
步骤S140：将所述判断结果发送给远端设备。Step S140: Send the judgment result to the remote device.
在本实施例中首先会采集特定用户的手部运动信息，这里的特定用户可包括年纪在第一指定岁数上的老人，也可以为在第二指定岁数一下的小孩，当然也可以是残疾人、智障人士等指定的用户。所述手部运动动作，可包括手部的运动轨迹，手部姿态等信息。在本实施例中可利用加速度传感器来检测等，这里的手部动作信息可以用三轴加速度传感器来检测。In this embodiment, the hand movement information of a specific user is first collected. The specific user here may include an elderly person at the first specified age, a child below the second specified age, or a disabled person. , mentally handicapped and other designated users. The movement of the hand may include information such as the trajectory of the hand, the posture of the hand, and the like. In this embodiment, an acceleration sensor can be used for detection, and the hand movement information here can be detected by a three-axis acceleration sensor.
在步骤S120中将首先识别所述手部动作信息是否满足饮食手势识别算法，若满足所述饮食手势识别算法，则开启图像采集功能，采集特定用户的手部图像。由于特定用户进行饮食通常有一定的特设的运动轨迹，可以通过所述手部动作信息中的运动轨迹来确定所述特定用户的当前手部动作信息是否是满足所述手势识别算法。在本实施例中所述手部图像，可为至少包括部分用户手部的图像。在步骤S120中，在采集所述手部图像时，可以按照指定时间间隔来采集，例如按周期采集所述手部图像，例如2秒钟采集一副所述手部图像，这样的话，若特定用户确实在处于饮食状态，在饮食状态中可以采集到多幅所述手部图像。且在本实施例中在步骤S120中确定特定用户的手部动作信息满足饮食手势识别算法时，才开始采集所述特定用户的手部图像，这样的话，可以减少无效图像的监控，同时节省监控设备的功耗。尤其若采集所述手部图像的设备为移动设备时，可以大大的节省设备的能耗，以及大大简化采集图像导致的操作。In step S120, firstly, it will be identified whether the hand motion information satisfies the eating gesture recognition algorithm, and if it satisfies the eating gesture recognition algorithm, the image collection function will be turned on to collect the hand image of a specific user. Since a specific user usually has a certain ad hoc movement trajectory when eating or drinking, it can be determined whether the current hand movement information of the specific user satisfies the gesture recognition algorithm through the movement trajectory in the hand movement information. In this embodiment, the hand image may be an image including at least part of the user's hand. In step S120, when the hand image is collected, it can be collected according to a specified time interval, for example, the hand image is collected periodically, for example, one hand image is collected every 2 seconds. The user is indeed in a state of eating and drinking, and multiple hand images can be collected in the state of eating and drinking. And in this embodiment, when it is determined in step S120 that the hand motion information of a specific user satisfies the eating gesture recognition algorithm, the image of the specific user's hand is collected. The power consumption of the device. Especially if the device that collects the hand image is a mobile device, the energy consumption of the device can be greatly saved, and the operation caused by image collection can be greatly simplified.
在步骤S130中可以根据所述手部图像直接判断出所述特定用户是否处于饮食状态，形成判断结果。在步骤S140中可以将所述判断结果发送给远端设备， 方便所述特定用户的监护人或家人直接检测到特定用户的饮食状态。采用本实施例所述饮食监控方法，通过采集特定用户手部动作和手部图像的结合，可以精确的判断出特定用户是否处于饮食状态。In step S130, it can be directly judged according to the hand image whether the specific user is in a state of eating or drinking, and a judgment result is formed. In step S140, the judgment result can be sent to the remote device, so that the guardian or family members of the specific user can directly detect the eating status of the specific user. By adopting the diet monitoring method described in this embodiment, it can be accurately judged whether a specific user is in a state of eating or not by collecting a combination of hand movements and hand images of a specific user.
在步骤S140通过将所述判断结果发送给远端设备，方便特定用户的监护人或家人远程精确的监控的特定用户的饮食状态。In step S140, by sending the judgment result to the remote device, it is convenient for the guardian or family member of the specific user to remotely and accurately monitor the dietary status of the specific user.
进一步地，所述步骤S110可包括：利用手部可穿戴式设备检测所述手部动作信息；所述步骤S120可包括：利用所述手部可穿戴式设备采集所述特定用户的饮食图像数据。Further, the step S110 may include: using a wearable hand device to detect the hand movement information; the step S120 may include: using the wearable hand device to collect the diet image data of the specific user .
在本实施例中所述手部可穿戴式设备可为智能手环、智能手表或智能指环等智能设备。该手部可穿戴式设备能够包括能够检测手部运动的传感器，以及采集图像的照相机或摄像机等结构。利用手部可穿戴式设备来进行检测，设备具有携带方便、结构简单、硬件成本低且具有检测结果精确的特点。In this embodiment, the wearable hand device may be a smart device such as a smart bracelet, a smart watch, or a smart ring. The wearable hand device can include a sensor capable of detecting hand movement, and a camera or video camera for collecting images. The hand wearable device is used for detection. The device has the characteristics of convenient portability, simple structure, low hardware cost and accurate detection results.
进一步地，所述步骤S130可包括：判断所述手部图像中是否有指定图像对象；所述指定图像对象包括饮食用具、饮品和食品的至少其中之一；若所述手部图像中包括所述指定图像对象，确定所述特定用户处于饮食状态；若所述手部图像中不包括所述指定图像对象，确定所述特定用户处于非饮食状态。Further, the step S130 may include: judging whether there is a designated image object in the hand image; the designated image object includes at least one of eating utensils, drinks and food; if the hand image includes the If the specified image object is used, it is determined that the specific user is in a state of eating or drinking; if the specified image object is not included in the hand image, it is determined that the specific user is in a non-eating state.
这里的饮食用具可包括筷子、勺子、就餐用的刀叉及杯子等饮食所用到的物具。当然所述指定图像对象还可包括饮品和食品本身。这里的饮品具体可如牛奶、饮料等。所述食品可包括水果、饭菜等。在步骤S130中可以利用图像识别技术，识别出所述手部图像中是否包括所述指定图像对象。The eating utensils here may include chopsticks, spoons, knives and forks for dining, cups and other used utensils for eating and drinking. Of course, the specified image objects may also include beverages and food itself. The drinks here may specifically be milk, beverages and the like. The food may include fruits, meals, and the like. In step S130, image recognition technology may be used to identify whether the specified image object is included in the hand image.
在本实施例中所述步骤S110中的手部动作满足饮食手势运动，同时在手部图像中采集到表征处于饮食状态的指定图像对象，这个时候特定用户处于饮食状态的概率非常高，故在本实施例中可认为在步骤S130在手部图像中发现了所述指定图像对象，就认为特定用户处于饮食状态。若手部图像中未发现所述指定图像对象，可能特定用户只是巧合做了与饮食过程中相似的动作，不认为特定用户处于饮食状态。显然本实施例所述的饮食信息监控方法具有监控结果精确的特点。In this embodiment, the hand movement in step S110 satisfies the eating and drinking gesture movement, and at the same time, a specified image object representing the eating and drinking state is collected in the hand image. At this time, the probability that the specific user is in the eating and drinking state is very high, so in In this embodiment, it can be considered that the specified image object is found in the hand image in step S130, and it is considered that the specific user is in a state of eating and drinking. If the specified image object is not found in the hand image, it may be that the specific user just coincidentally performed a similar action to that of eating and drinking, and the specific user is not considered to be in a state of eating and drinking. Obviously, the diet information monitoring method described in this embodiment has the characteristics of accurate monitoring results.
进一步地，所述步骤S130具体包括：Further, the step S130 specifically includes:
若所述手部图像中的所述指定图像对象出现在所述特定用户的嘴边，则确定所述特定用户处于所述饮食状态。当然，为了进一步提高监控的精确度，在步骤S130中在所述指定图像对象出现在所述特定用户的嘴边时，才确定所述特定用户处于饮食状态。If the designated image object in the hand image appears near the mouth of the specific user, it is determined that the specific user is in the diet state. Of course, in order to further improve the monitoring accuracy, it is determined that the specific user is eating or drinking only when the specified image object appears near the specific user's mouth in step S130.
进一步地，所述若所述手部图像中的所述指定图像对象出现在所述特定用户的嘴边，则确定所述特定用户处于所述饮食状态，包括：若所述手部图像中所述指定图像对象出现在所述特定用户嘴边的概率大于指定概率，则确定所述特定用户处于正常饮食状态。当所述指定图像对象出现在用户嘴边时，说明了特定用户处于饮食状态，但是该处于正常饮食还是处于异常饮食，在本实施例中，将会统计采集的N张手部图像中包括所述指定图像对象出现嘴边的手部图像占N张所述手部图像中的概率，若该概率大于指定值，才认为特定用户处于正常饮食状态，否则可能该特定用户的饮食状态出现异常。例如，某位老人因肠胃不好，虽然进食，但是进食很少，在用餐时间内吃的食物很少；显然这时用户处于非正常饮食状态。当然老人的监护人或家人可能不仅想了解老人是否有进行饮食，同时还向了解老师是否能够正常饮食，因为这直接关系着老人的健康。Further, if the specified image object in the hand image appears on the mouth of the specific user, determining that the specific user is in the eating state includes: if the specified image object in the hand image If the probability that the specified image object appears on the mouth of the specific user is greater than the specified probability, it is determined that the specific user is in a normal eating state. When the specified image object appears on the user's mouth, it indicates that the specific user is in a state of eating, but whether the user is in a normal diet or in an abnormal diet. In this embodiment, the N hand images collected statistically include all The probability that the hand image near the mouth of the specified image object accounts for the probability of the N hand images. If the probability is greater than the specified value, the specific user is considered to be in a normal eating state, otherwise the specific user’s eating state may appear abnormal. For example, a certain old man eats because of a bad stomach, but eats very little, and eats very little food during the meal time; it is obvious that the user is in an abnormal eating state at this time. Of course, the guardian or family members of the elderly may not only want to know whether the elderly is eating, but also ask whether the teacher can eat normally, because this is directly related to the health of the elderly.
本实施例所述饮食监控方法，在具体的实现过程中，还会存储所述手部动作信息和所述手部图像，方便后续用户查看以及进行后续的数据深度的处理。The diet monitoring method described in this embodiment, in a specific implementation process, will also store the hand movement information and the hand image, which is convenient for subsequent users to view and perform subsequent deep data processing.
总之本实施例所述饮食信息监控方法，能够方便远程精确的监控特定用户的饮食状态。In a word, the dietary information monitoring method described in this embodiment can facilitate remote and accurate monitoring of the dietary status of a specific user.
实施例二：Embodiment two:
如图2所示，本实施例提供一种饮食信息监控装置，所述装置包括：As shown in Figure 2, this embodiment provides a diet information monitoring device, the device includes:
检测单元110，用于检测特定用户的手部动作信息；A detection unit 110, configured to detect hand movement information of a specific user;
采集单元120，用于若所述手部动作信息满足预设饮食手势识别算法时，采集所述特定用户的手部图像；The collection unit 120 is configured to collect the hand image of the specific user if the hand movement information satisfies the preset eating gesture recognition algorithm;
判断单元130，用于基于所述手部图像判断所述特定用户是否处于饮食状 态，形成判断结果；A judging unit 130, configured to judge whether the specific user is in a state of eating or drinking based on the hand image, and form a judging result;
发送单元140，用于将所述判断结果发送给远端设备。The sending unit 140 is configured to send the judgment result to the remote device.
本实施例所述饮食信息监控装置可对应于能够监控特定用户的设备，例如，可对应于特定用户的手部可穿戴式设备。The diet information monitoring device in this embodiment may correspond to a device capable of monitoring a specific user, for example, may correspond to a wearable device in the hand of a specific user.
所述检测单元110可对应于陀螺仪或加速度传感器等结构，所述加速度传感器可包括三轴加速度传感器。The detection unit 110 may correspond to structures such as a gyroscope or an acceleration sensor, and the acceleration sensor may include a three-axis acceleration sensor.
所述采集单元120可对应于能够进行图像采集的各种结构，例如照相机或摄像机等结构。The acquisition unit 120 may correspond to various structures capable of image acquisition, such as a camera or video camera.
所述判断单元130可对应于处理器或处理电路等。所述处理器可包括应用处理器、数字信号处理器、中央处理器、微处理器或可编程阵列等结构。所述处理电路可包括专用集成电路，通过执行预定的指令，可以判断所述特定用户是否处于饮食状态，形成对应的判断结果。The judging unit 130 may correspond to a processor or a processing circuit or the like. The processor may include an application processor, a digital signal processor, a central processing unit, a microprocessor, or a programmable array. The processing circuit may include an application-specific integrated circuit, and by executing predetermined instructions, it may be determined whether the specific user is in a state of eating or drinking, and a corresponding determination result may be formed.
所述发送单元140可包括各种类型的发送接口，所述发送接口可对应于各种类型的天线等无线发送接口，例如WiFi接口、蓝牙接口等。The sending unit 140 may include various types of sending interfaces, and the sending interfaces may correspond to various types of wireless sending interfaces such as antennas, such as WiFi interfaces, Bluetooth interfaces, and the like.
总之本实施例所述的饮食监控装置能够实现实施例一所述的任意一个饮食监控方法的技术方案，同样具有能够精确远程监控特定用户饮食的特点。In short, the diet monitoring device described in this embodiment can realize any technical solution of the diet monitoring method described in Embodiment 1, and also has the feature of being able to accurately and remotely monitor the diet of a specific user.
所述检测单元110，具体用于利用手部可穿戴式设备检测所述手部动作信息；The detection unit 110 is specifically configured to use a wearable hand device to detect the hand movement information;
所述采集单元120，用于利用所述手部可穿戴式设备采集所述特定用户的饮食图像数据。The collection unit 120 is configured to use the wearable hand device to collect the diet image data of the specific user.
在本实施例中利用所述手部可穿戴式设备，通常可穿戴式设备具有体积小、佩戴方便及智能性高的特点。在本实施例中利用所述检测单元110和所述采集单元120都利用手部可穿戴式设备来分别进行手部动作信息的检测及手部图像的采集，具有实现简便、成本低廉及使用方便的特点。In this embodiment, the hand wearable device is used. Generally, the wearable device has the characteristics of small size, easy wearing and high intelligence. In this embodiment, both the detection unit 110 and the collection unit 120 use wearable hand devices to detect hand movement information and collect hand images, which is easy to implement, low in cost and easy to use. specialty.
进一步地，所述判断单元130，具体用于判断所述手部图像中是否有指定图像对象；所述指定图像对象包括饮食用具、饮品和食品的至少其中之一；若所述手部图像中包括所述指定图像对象，确定所述特定用户处于饮食状态；若 所述手部图像中不包括所述指定图像对象，确定所述特定用户处于非饮食状态。Further, the judging unit 130 is specifically configured to judge whether there is a specified image object in the hand image; the specified image object includes at least one of eating utensils, drinks and food; if the hand image contains If the specified image object is included, it is determined that the specific user is in an eating state; if the specified image object is not included in the hand image, it is determined that the specific user is in a non-eating state.
在本实施例中所述判断单元130通过对所述手部图像的识别，识别出所述手部图像中是否包括指定图像对象，来确定所述特定用户是否处于饮食状态。In this embodiment, the judging unit 130 determines whether the specific user is eating or drinking by identifying whether the hand image includes a specified image object by identifying the hand image.
当然为了进一步精确确定所述特定用户是否处于饮食状态，在本实施例中，所述判断单元130，具体用于若所述手部图像中的所述指定图像对象出现在所述特定用户的嘴边，则确定所述特定用户处于所述饮食状态。在本实施例若所述指定图像对象出现的特定的用户嘴边，表示特定用户确实有进行饮食，这个时候才确定所述特定用户处于饮食状态，就能够保证判断结果的精确性。Of course, in order to further accurately determine whether the specific user is in a state of eating or drinking, in this embodiment, the judging unit 130 is specifically configured to, if the specified image object in the hand image appears on the specific user's mouth side, it is determined that the specific user is in the diet state. In this embodiment, if the specified image object appears near the mouth of the specific user, it means that the specific user is indeed eating or drinking. Only at this time can it be determined that the specific user is in a state of eating and drinking, which can ensure the accuracy of the judgment result.
当然，在本实施例中所述判断单元130，具体用于若所述手部图像中所述指定图像对象出现在所述特定用户嘴边的概率大于指定概率，则确定所述特定用户处于正常饮食状态。在本实施例中所述判断单元130不仅能够用于判断特定用户是处于饮食状态还是处于非饮食状态，还能够判断用户是否处于正常饮食状态，再次提高了所述饮食信息监控装置的智能性及用户使用满意度。Of course, in this embodiment, the judging unit 130 is specifically configured to determine that the specific user is in a normal state if the probability that the specified image object in the hand image appears on the mouth of the specific user is greater than the specified probability. Diet status. In this embodiment, the judging unit 130 can not only be used to judge whether a specific user is in a eating state or a non-eating state, but also can judge whether the user is in a normal eating state, which improves the intelligence and performance of the diet information monitoring device again. User satisfaction.
值得注意的是：本实施例所述的饮食信息监控装置还包括存储单元，该存储单元能够用于存储所述手部动作信息及所述手部图像。It should be noted that the diet information monitoring device described in this embodiment further includes a storage unit, which can be used to store the hand movement information and the hand image.
以下结合上述任意实施例提供两个具体示例：Two specific examples are provided below in conjunction with any of the above-mentioned embodiments:
示例一：Example one:
如图3所示，本示例提供一种手部可穿戴式设备，该手部可穿戴式设备可由四部分组成，分别是数据采集模块、数据分析模块、数据存储模块和网络接口模块。这里的数据采集模块可对应于前述实施例中的检测单元110和采集单元120。这里的数据分析模块可对应于前述实施例中的判断模块130。这里的网络接口模块可对应于前述实施例中的发送单元140、As shown in Figure 3, this example provides a wearable hand device, which can be composed of four parts, namely a data acquisition module, a data analysis module, a data storage module and a network interface module. The data acquisition module here may correspond to the detection unit 110 and the acquisition unit 120 in the foregoing embodiments. The data analysis module here may correspond to the judging module 130 in the foregoing embodiments. The network interface module here may correspond to the sending unit 140,
数据采集模块通过采集加速度传感器数据和摄像头数据，采集到的数据由数据分析模块处理分析，处理分析的结果可通过网络接口模块发送至用户监控终端。The data collection module collects acceleration sensor data and camera data, and the collected data is processed and analyzed by the data analysis module, and the processing and analysis results can be sent to the user monitoring terminal through the network interface module.
数据采集模块包括加速度传感器和摄像头。老人佩戴手部可穿戴式设备主要实现以下两种功能：The data acquisition module includes an acceleration sensor and a camera. The wearable device worn by the elderly mainly realizes the following two functions:
1.1通过手部可穿戴式设备的加速度传感器采集老人手部运动信息；1.1 Collect the hand movement information of the elderly through the acceleration sensor of the hand wearable device;
1.2通过摄像头采集老人的图像数据。这里的老人即为前述实施例中所述的特定用户的一种。1.2 Collect the image data of the elderly through the camera. The old man here is one of the specific users described in the foregoing embodiments.
数据采集模块采集的数据由数据分析模块处理分析。数据分析模块包括2个智能算法：饮食手势识别算法和就餐状态智能判断算法。The data collected by the data acquisition module is processed and analyzed by the data analysis module. The data analysis module includes 2 intelligent algorithms: eating gesture recognition algorithm and intelligent judgment algorithm of dining status.
手部可穿戴式设备对手部运动信息进行采集，采集的运动信息通过饮食手势识别算法，判断老人手部运动是否符合处于吃饭时手部夹菜和进食状态的运动规律。当检测到老人处于夹菜和进食状态时，触发可穿戴设备的摄像头在特定动作节点进行图像的采集，通过对手势运动信息和摄像头采集图像联合分析判断老人饮食行为状态。The wearable hand device collects hand movement information, and the collected movement information is used to judge whether the hand movement of the elderly conforms to the movement law of the hand picking and eating state through the eating gesture recognition algorithm. When it is detected that the elderly is in the state of picking up food and eating, the camera of the wearable device is triggered to collect images at specific action nodes, and the eating behavior status of the elderly is judged by joint analysis of gesture motion information and images collected by the camera.
图4显示的是手部可穿戴式设备中的三轴加速度传感器检测到的老人吃饭时手部运动所造成的加速度变化情况。其中R1、Y1、B1三条曲线表示的是传感器输出的XYZ三个轴向的加速度值变化情况，P1线表示的是总的加速度值的变化情况(即Sqrt(X^2+Y^2+Z^2)的值的变化情况)。在执行的是饮食手势识别时，不对XYZ轴的具体方向进行区分，只区分三个方向上加速度的变化情况。Figure 4 shows the acceleration changes caused by the hand movement of the elderly when eating, detected by the three-axis acceleration sensor in the hand wearable device. Among them, the three curves of R1, Y1, and B1 represent the change of the acceleration value of the XYZ three axes output by the sensor, and the P1 line represents the change of the total acceleration value (that is, Sqrt(X^2+Y^2+Z ^2) value changes). When the recognition of eating and drinking gestures is performed, the specific directions of the XYZ axes are not distinguished, but only the changes in acceleration in the three directions are distinguished.
手部可穿戴式设备中的三轴加速度传感器对吃饭手势的加速度值进行采集。由于饮食时手在进食过程，手腕在靠近桌子和到嘴边这两个地方时会有大的加速度，以使手部从运动到静止或从静止到运动。而在手的抬起、放下过程中(介于桌子和嘴边这两点之间)手的运动是相对匀速的，此时传感器采集到的XYZ三个轴向的加速度值变化情况更多地是由于手势的变化导致xyz轴的转动，使得1g的重力加速度在xyz上的投射大小不一样。因此，当检测到三轴加速度传感器的值满足以下变化规律时，则判定老人吃饭时手部存在夹菜和进食的行为：The three-axis acceleration sensor in the hand wearable device collects the acceleration value of the eating gesture. Because the hands are in the process of eating when eating, the wrist will have a large acceleration when it is close to the table and to the mouth, so that the hand will change from motion to rest or from rest to motion. However, in the process of raising and lowering the hand (between the table and the mouth), the movement of the hand is relatively uniform, and the acceleration values of the XYZ three axes collected by the sensor change more It is because the change of the gesture causes the rotation of the xyz axis, so that the projection size of the acceleration of gravity of 1g on the xyz is different. Therefore, when it is detected that the value of the three-axis acceleration sensor satisfies the following change rules, it is determined that the old man has the behavior of holding vegetables and eating with his hands when eating:
在可穿戴设备检测后的一段时间内，检测总的加速度值大于一定阈值Gt所对应的时间点，对于这些被检测出的时间点，若任意两个时间点之间的时间距离小于Tmin，则这些时间点归为一个集合，并选取该集合中间距 较密集(dt时间内点最多)的点中加速度值最大的点作为备选特征点(如图4所示的T1，T2，T5)；若对于这些备选特征点所确定的区间，存在任意3个连续的备选特征点所确定的两个连续的区间内，如[T1,T2],[T2,T5]内，满足以下条件：Within a period of time after the wearable device is detected, the detected total acceleration value is greater than the time point corresponding to a certain threshold Gt. For these detected time points, if the time distance between any two time points is less than Tmin, then These time points are classified as a set, and the point with the largest acceleration value among the points with denser intervals (the most points in the dt time) in the set is selected as an alternative feature point (T1, T2, T5 as shown in Figure 4); If there are two consecutive intervals determined by any three consecutive candidate feature points in the interval determined by these candidate feature points, such as [T1, T2], [T2, T5], the following conditions are met:
在[T1,T2]区间内，有两个轴向存在加速度平均值Ga、Gb分别大于阈值G1和阈值G3且第三个轴向的加速度平均值Gc小于阈值G6。In the interval [T1, T2], there are two axial acceleration averages Ga and Gb greater than the threshold G1 and threshold G3 respectively and the third axial acceleration average Gc is less than the threshold G6.
在[T2,T3]区间内，存在时间区间[T3,T4],有两个轴向存在加速度平均值Ga、Gb分别小于阈值G2和阈值G4且第三个轴向的加速度平均值Gc大于阈值G5。In the [T2, T3] interval, there is a time interval [T3, T4], there are two axial acceleration averages Ga and Gb that are less than the threshold G2 and threshold G4 respectively, and the third axial acceleration average Gc is greater than the threshold G5.
上述[T2,T3]、[T3,T4]、[T4,T5]各时间段对应的意义如下：The corresponding meanings of the above [T2,T3], [T3,T4], [T4,T5] time periods are as follows:
在[T2,T3]时间内，有一段连续的时间存在总的加速度值小于1g，其中T3为总的加速度值从小于1g到大于等于1g的分界点；同时在[T4,T5]时间内，有一段连续的时间也存在总的加速度值小于1g，其中T4为总的加速度值从大于等于1g到小于1g的分界点。这其中，在T2时刻所产生的大于1g的加速度是由于手要抬起，手为了克服重力加速度以使手的运动速度从0到瞬间大于0；在[T2,T3]这个时间段内所存在的总加速度值小于1g的那段时间，其存在的原因可理解为由于人在夹菜至嘴边的过程中，在将要把菜夹到嘴边之前，开始出现减速所造成，从而在随后的很短时间内，在菜真正到达嘴边时，手运动的速度变为0；在[T3,T4]这段时间内，手在嘴边，及手受重力加速度放下但未到达桌边时，传感器检测到的总的加速度值基本为重力加速度值，即1g；在[T4,T5]这个时间段内所存在的总加速度值小于1g的那段时间，其存在的原因可理解为由于手在受重力加速度落下至桌子的过程中，在手将要到达桌子之前，手开始出现减速所造成，从而在随后的很短时间内，在手真正接触桌子时，手运动的速度由大于0瞬间变为0，因此在T5时刻存在传感器检测到加速度值大于1g的情况。In [T2, T3] time, there is a continuous period of time where the total acceleration value is less than 1g, where T3 is the cut-off point for the total acceleration value from less than 1g to greater than or equal to 1g; at the same time in [T4, T5] time, There is also a continuous period of time when the total acceleration value is less than 1g, where T4 is the cut-off point for the total acceleration value from greater than or equal to 1g to less than 1g. Among them, the acceleration greater than 1g generated at T2 is due to the fact that the hand needs to be lifted to overcome the acceleration of gravity to make the hand’s movement speed from 0 to instantly greater than 0; during the time period [T2, T3] The reason for the existence of the time when the total acceleration value is less than 1g can be understood as that the deceleration begins to occur before the food is brought to the mouth during the process of picking the food to the mouth, so that in the subsequent In a short period of time, when the dish actually reaches the mouth, the speed of the hand movement becomes 0; during the period [T3, T4], when the hand is near the mouth, and when the hand is put down by the acceleration of gravity but has not reached the edge of the table, The total acceleration value detected by the sensor is basically the gravitational acceleration value, that is, 1g; during the time period [T4, T5] when the total acceleration value is less than 1g, the reason for its existence can be understood as the hand is in the In the process of falling to the table under the acceleration of gravity, the hand starts to decelerate before it reaches the table, so that in a short period of time afterwards, when the hand actually touches the table, the speed of the hand movement changes from greater than 0 to 0, so there is a situation that the sensor detects that the acceleration value is greater than 1g at time T5.
满足以上条件，则T1、T2、T5这3个备选特征点则为确定的特征点。对于上述的3个特征点，T2对应夹好菜准备抬手进食的时刻，T1和T5对 应进食结束后回到桌子上再次要夹菜的时刻。而T3至T4区间的中间时刻对应于进食的时刻。If the above conditions are met, the three candidate feature points T1, T2, and T5 are determined feature points. For the above three feature points, T2 corresponds to the moment when the food is picked up and ready to be eaten, and T1 and T5 correspond to the time when the food is returned to the table after eating. And the middle moment of the interval T3 to T4 corresponds to the moment of eating.
当检测到老人手部存在夹菜和进食行为后，启动摄像头，每隔一定周期C采集拍摄老人进食图像。分析判断图像，若采集的图像中有筷子或勺子出现在嘴边，且出现的次数大于采集次数的一定比例P，则老人处于就餐状态。这的就餐状态为前述饮食状态的其中之一。这里比例P对应着上述指定概率。When it is detected that there is food picking and eating behavior in the hands of the old man, the camera is started to collect and shoot the eating images of the old man every certain period C. Analyze and judge the image, if there are chopsticks or spoons appearing near the mouth in the collected image, and the number of occurrences is greater than a certain proportion P of the collection times, then the old man is in the eating state. This eating state is one of the aforementioned eating states. Here the proportion P corresponds to the above specified probability.
数据存储模块由数据存储单元组成，负责存储采集的手部运动数据和图像数据。The data storage module is composed of a data storage unit, which is responsible for storing the collected hand motion data and image data.
网络接口模块提供WIFI和2G/3G/4G移动网络接入功能。通过该模块，可穿戴设备能够与外部终端、平台进行数据及信息传递。The network interface module provides WIFI and 2G/3G/4G mobile network access functions. Through this module, wearable devices can communicate data and information with external terminals and platforms.
示例二：Example two:
如图5所示，本示例提供一种所述手部可穿戴式设备检测老人饮食状态的方法，包括：As shown in Figure 5, this example provides a method for the wearable hand device to detect the eating status of the elderly, including:
步骤S1：检测老人手部发送运动；Step S1: Detect the hand movement of the elderly;
步骤S2：判断手部存在夹菜和进食行为？若是则进入步骤S3，若否进入步骤S6。Step S2: Judging whether there is food picking and eating behavior in the hands? If yes, go to step S3; if not, go to step S6.
步骤S3：启动摄像头，每隔一定周期C拍摄老人进食图像。Step S3: start the camera, and take pictures of the old man eating every certain period C.
步骤S4：判断图像中与偶筷子或勺子出现在嘴边的次数是否大于采集次数的一定比例P？若是进入步骤S5；若否则进入步骤S6。Step S4: Determine whether the number of times the pair of chopsticks or spoons appear near the mouth in the image is greater than a certain proportion P of the number of collection times? If yes, go to step S5; otherwise, go to step S6.
步骤S5：确定老人处于就餐状态。Step S5: Determine that the elderly is in the state of eating.
步骤S6：确定老人处于非几餐状态。Step S6: Determine that the old man is in a non-several meal state.
在本申请所提供的几个实施例中，应该理解到，所揭露的设备和方法，可以通过其它的方式实现。以上所描述的设备实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，如：多个单元或组件可以结合，或可以集成到另一个系统，或一些特征可以忽略，或不执行。另外，所显示或讨论的各组成部分相互之间的耦合、 或直接耦合、或通信连接可以是通过一些接口，设备或单元的间接耦合或通信连接，可以是电性的、机械的或其它形式的。In the several embodiments provided in this application, it should be understood that the disclosed devices and methods may be implemented in other ways. The device embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods, such as: multiple units or components can be combined, or May be integrated into another system, or some features may be ignored, or not implemented. In addition, the coupling, or direct coupling, or communication connection between the various components shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be electrical, mechanical or other forms of.
上述作为分离部件说明的单元可以是、或也可以不是物理上分开的，作为单元显示的部件可以是、或也可以不是物理单元，即可以位于一个地方，也可以分布到多个网络单元上；可以根据实际的需要选择其中的部分或全部单元来实现本实施例方案的目的。The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units; Part or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.
另外，在本发明各实施例中的各功能单元可以全部集成在一个处理模块中，也可以是各单元分别单独作为一个单元，也可以两个或两个以上单元集成在一个单元中；上述集成的单元既可以采用硬件的形式实现，也可以采用硬件加软件功能单元的形式实现。In addition, each functional unit in each embodiment of the present invention can be integrated into one processing module, or each unit can be used as a single unit, or two or more units can be integrated into one unit; the above-mentioned integration The unit can be realized in the form of hardware or in the form of hardware plus software functional unit.
本领域普通技术人员可以理解：实现上述方法实施例的全部或部分步骤可以通过程序指令相关的硬件来完成，前述的程序可以存储于一计算机可读取存储介质中，该程序在执行时，执行包括上述方法实施例的步骤；而前述的存储介质包括：移动存储设备、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、磁碟或者光盘等各种可以存储程序代码的介质。Those of ordinary skill in the art can understand that all or part of the steps for realizing the above-mentioned method embodiments can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the Including the steps of the foregoing method embodiment; and the aforementioned storage medium includes: various storage devices, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disk A medium on which program code can be stored.
以上所述，仅为本发明的具体实施方式，但本发明的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本发明揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本发明的保护范围之内。因此，本发明的保护范围应以所述权利要求的保护范围为准。The above is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Anyone skilled in the art can easily think of changes or substitutions within the technical scope disclosed in the present invention. Should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be determined by the protection scope of the claims.
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510778853.2ACN106709401A (en) | 2015-11-13 | 2015-11-13 | Diet information monitoring method and device |
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510778853.2ACN106709401A (en) | 2015-11-13 | 2015-11-13 | Diet information monitoring method and device |
| Publication Number | Publication Date |
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| CN106709401Atrue CN106709401A (en) | 2017-05-24 |
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510778853.2APendingCN106709401A (en) | 2015-11-13 | 2015-11-13 | Diet information monitoring method and device |
| Country | Link |
|---|---|
| CN (1) | CN106709401A (en) |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108108690A (en)* | 2017-12-19 | 2018-06-01 | 深圳创维数字技术有限公司 | A kind of method, apparatus, equipment and storage medium for monitoring diet |
| CN108279022A (en)* | 2018-03-12 | 2018-07-13 | 众米智能科技（深圳）有限公司 | Intelligent gesture identifying system, the baby spoon fork with the system and implementation method |
| CN110826506A (en)* | 2019-11-11 | 2020-02-21 | 上海秒针网络科技有限公司 | Target behavior identification method and device |
| CN114581837A (en)* | 2022-03-21 | 2022-06-03 | 宁波星巡智能科技有限公司 | Intelligent identification method, device and equipment for infant feeding information and storage medium |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2000245713A (en)* | 1999-02-26 | 2000-09-12 | Sanyo Electric Co Ltd | Behavior recognizing device |
| US20090082699A1 (en)* | 2007-09-21 | 2009-03-26 | Sun Lee Bang | Apparatus and method for refining subject activity classification for recognition of daily activities, and system for recognizing daily activities using the same |
| CN102368297A (en)* | 2011-09-14 | 2012-03-07 | 北京英福生科技有限公司 | Equipment, system and method for recognizing actions of detected object |
| CN102567743A (en)* | 2011-12-20 | 2012-07-11 | 东南大学 | Automatic identification method of driver gestures based on video images |
| US20130336519A1 (en)* | 2012-06-14 | 2013-12-19 | Robert A. Connor | Willpower Watch (TM) -- A Wearable Food Consumption Monitor |
| CN104765980A (en)* | 2015-05-04 | 2015-07-08 | 哈尔滨理工大学 | Intelligent diet assessment method based on cloud computing |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2000245713A (en)* | 1999-02-26 | 2000-09-12 | Sanyo Electric Co Ltd | Behavior recognizing device |
| US20090082699A1 (en)* | 2007-09-21 | 2009-03-26 | Sun Lee Bang | Apparatus and method for refining subject activity classification for recognition of daily activities, and system for recognizing daily activities using the same |
| CN102368297A (en)* | 2011-09-14 | 2012-03-07 | 北京英福生科技有限公司 | Equipment, system and method for recognizing actions of detected object |
| CN102567743A (en)* | 2011-12-20 | 2012-07-11 | 东南大学 | Automatic identification method of driver gestures based on video images |
| US20130336519A1 (en)* | 2012-06-14 | 2013-12-19 | Robert A. Connor | Willpower Watch (TM) -- A Wearable Food Consumption Monitor |
| CN104765980A (en)* | 2015-05-04 | 2015-07-08 | 哈尔滨理工大学 | Intelligent diet assessment method based on cloud computing |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108108690A (en)* | 2017-12-19 | 2018-06-01 | 深圳创维数字技术有限公司 | A kind of method, apparatus, equipment and storage medium for monitoring diet |
| CN108108690B (en)* | 2017-12-19 | 2022-02-11 | 深圳创维数字技术有限公司 | Method, device, equipment and storage medium for monitoring diet |
| CN108279022A (en)* | 2018-03-12 | 2018-07-13 | 众米智能科技（深圳）有限公司 | Intelligent gesture identifying system, the baby spoon fork with the system and implementation method |
| CN110826506A (en)* | 2019-11-11 | 2020-02-21 | 上海秒针网络科技有限公司 | Target behavior identification method and device |
| CN114581837A (en)* | 2022-03-21 | 2022-06-03 | 宁波星巡智能科技有限公司 | Intelligent identification method, device and equipment for infant feeding information and storage medium |
| Publication | Publication Date | Title |
|---|---|---|
| KR102396291B1 (en) | Method for processing data and electronic device thereof | |
| JPWO2016143404A1 (en) | Information processing apparatus, information processing method, and program | |
| CN106709401A (en) | Diet information monitoring method and device | |
| US20180144427A1 (en) | Worker data detection system, terminal device, and worker data detection method | |
| US20180122214A1 (en) | Hand hygiene system | |
| CN110179471A (en) | Tumble detection method, tumble detection device, tumble detection apparatus, and storage medium | |
| EP2652676A1 (en) | Gesture control for monitoring vital body signs | |
| WO2015083411A1 (en) | Information-processing apparatus, information-processing method, and program | |
| US20160132642A1 (en) | Device and method for monitoring food intake | |
| CN105512501A (en) | Intelligent diet analysis system | |
| CN103859721A (en) | Intelligent walking stick for tumbling remote monitoring and nursing | |
| CN105631788A (en) | Information processing methods, information processing apparatuses and information processing system | |
| Zhou et al. | Monitoring dietary behavior with a smart dining tray | |
| US11478096B2 (en) | Food monitoring system | |
| CN109300526A (en) | A recommendation method and mobile terminal | |
| JP2017224174A (en) | Information acquisition terminal, information collection device, behavior observation system, information acquisition terminal control method, and information collection device control method | |
| JP6654721B1 (en) | Eating system, computer program, and information device | |
| CN107229216A (en) | A kind of intelligent watch and its control method | |
| US11462006B2 (en) | Systems and methods for monitoring consumption | |
| JP2014086038A (en) | Action recognition system | |
| JP2014123214A (en) | Electronic apparatus | |
| JP2009199319A (en) | Cane and communication method | |
| CN106777888A (en) | The accurate monitoring method and device of a kind of user's growth data | |
| CN106020624A (en) | Method and device for temperature information processing | |
| JP6277582B2 (en) | Electronics |
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|---|---|---|---|
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| RJ01 | Rejection of invention patent application after publication | Application publication date:20170524 | |
| RJ01 | Rejection of invention patent application after publication |