Device for non-inductively detecting weakness risk of old people

Abstract

The utility model provides a device for non-inductively detecting the weakness risk of old people, which comprises a face recognition module for automatically recognizing facial feature information of the old people, and a data recognizer for outputting basic information corresponding to the old people and monitored data related to weakness according to the recognized facial feature information of the old people, the gait acquisition module is arranged lower than the face recognition module and is suitable for acquiring gait feature information of the passing old people; the weight detection module is arranged underground and is suitable for detecting weight information of the passing old people; the data processing module is respectively connected with the data recognizer, the gait acquisition module and the weight detection module and is used for screening by comparing a standard Fried weakness risk assessment scale according to the output basic information of the corresponding old people, the monitored data related to weakness, the gait feature information of the old people and the weight information of the old people; and the data processor is used for outputting a weakness risk screening result to remind medical personnel. The device can quickly, accurately and timely complete weakness risk detection in a non-perception state of the old.

Description

Technical Field

[0001] The utility model relates to the technical field of elderly care, and in particular to a device for detecting the risk of frailty in the elderly without any sense. Background Art

[0002] Frailty refers to a nonspecific condition in the elderly characterized by decreased physiological reserves, leading to increased vulnerability and reduced stress resistance. Frail elderly individuals may present with one or more of the following clinical manifestations: 1. Nonspecific manifestations; 2. Falls; 3. Delirium; 4. Fluctuating disability. It is recommended that all people aged 70 years and older, or those who have experienced weight loss (≥5 kg) without intentional dieting within the past year, should undergo screening and assessment for frailty. Currently, the main method for assessing frailty risk is the use of various frailty assessment scales (such as the Fried Frailty Risk Assessment Scale).

[0003] However, the inventors of this application have found through clinical research that the existing frailty risk assessment methods have the following problems: 1. Manual assessment is time-consuming: there are many assessment items and the hearing and comprehension of the elderly are reduced, so the assessment process takes a long time. In the assessment content, some assessment items are repeated with routine test data, and there are repeated measurements or manual inquiries of measured data; 2. Low accuracy: when the elderly are told that a certain assessment is being conducted, some elderly people will deliberately show their best state during the assessment, rather than their true state, in order to prove that they are still capable; 3. Lag in assessment results: when using a scale to assess frailty risk, it is generally assessed regularly for half a year or a year, but the elderly may begin to have the risk of frailty in the period between two assessments; 4. Many elderly people are missed in the assessment: the elderly have their own daily routines. When the elderly are required to complete a certain assessment specifically, some elderly people will not cooperate or are unwilling to complete it, or the elderly are unable to complete the assessment due to physical condition or other reasons during the assessment, thus being missed. Utility Model Content

[0004] In view of the technical problems of existing frailty risk assessment methods, such as time-consuming manual assessment, low accuracy, delayed assessment results, and many missed assessments of elderly people, the utility model provides a device for non-sensing detection of frailty risk in the elderly.

[0005] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0006] A device for non-sensingly detecting the risk of frailty in the elderly comprises a face recognition module suitable for automatically identifying facial feature information of a passing elderly person, a data identifier connected to the face recognition module for outputting basic information of the elderly person and frailty-related monitored data based on the identified facial feature information of the elderly person, a gait acquisition module disposed below the face recognition module for collecting gait feature information of a passing elderly person, a weight detection module disposed under the ground for detecting weight information of a passing elderly person, and a data processor connected to the data identifier, the gait acquisition module and the weight detection module respectively for screening against a standard Fried frailty risk assessment scale based on the basic information of the elderly person and frailty-related monitored data output by the data identifier, the gait feature information of the elderly person collected by the gait acquisition module and the weight information of the elderly person detected by the weight detection module, and outputting the frailty risk screening results to alert medical personnel.

[0007] The present invention provides a device for detecting frailty risk in the elderly without any sense of the elderly. By realizing facial recognition, basic information integration, frailty risk feature data collection, and data analysis and comparison without the elderly being aware of the situation, the device provides risk warnings to elderly people at risk of frailty, achieving the purpose of quickly, accurately, and timely reminding medical personnel of the elderly's frailty risk, thereby enabling early intervention for frailty. Compared with the existing technology, the device for detecting frailty risk in the elderly without any sense of the elderly has the following advantages: 1. It automatically retrieves routine detection data, i.e., frailty-related monitored data, avoiding duplication of work. The device can be used for a long time after installation without the need for manual measurement and evaluation. 2. During the evaluation, the elderly do not know the actual location of the detection device and cannot deliberately adjust their state, thereby better collecting the elderly's real data and achieving high accuracy. 3. The evaluation results can promptly identify elderly people at risk of frailty. 4. The evaluation data is more comprehensive and complete: the elderly do not need to set aside time to participate in the evaluation. The evaluation can be completed during daily walking, and more elderly data can be collected. In addition, the device can collect not only walking speed but also other gait characteristics of the elderly. After comparing these gait characteristic data before and after, it can provide a certain reference.

[0008] Furthermore, the face recognition module uses a face recognition camera, and the gait collection module uses a gait collection camera.

[0009] Furthermore, the weight detection module adopts a pressure sensor.

[0010] Furthermore, the data identifier and data processor adopt MSP430 single chip microcomputer.

[0011] Furthermore, the device also includes a liquid crystal touch screen connected to the data processor and suitable for displaying and outputting frailty risk screening results, and a speaker connected to the data processor and suitable for voice reminders to medical personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 This is a principle block diagram of a device for non-sensing detection of frailty risk in the elderly provided by the utility model.

[0013] In the figure, 1. Face recognition module; 2. Data identifier; 3. Gait acquisition module; 4. Weight detection module; 5. Data processor; 6. LCD touch screen; 7. Speaker. DETAILED DESCRIPTION

[0014] In order to make the technical means, creative features, objectives and effects achieved by the present invention easier to understand, the present invention is further described below with reference to specific illustrations.

[0015] In the description of this utility model, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integral connections; mechanical connections, electrical connections; direct connections, indirect connections through an intermediate medium, and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in this utility model based on the specific circumstances.

[0016] Please refer to Figure 1As shown, the present invention provides a device for detecting the risk of frailty of the elderly without any sense, comprising a face recognition module 1 suitable for automatically recognizing the facial feature information of the elderly passing by. The face recognition module 1 can be specifically set on the wall of the corridor of a hospital, a nursing home, or a community elderly activity center, so that the elderly can be recognized without any sense when passing through the corridor; a data identifier 2 connected to the face recognition module 1 is used to output the basic information of the elderly and the monitored data related to frailty according to the recognized facial feature information of the elderly, that is, the data identifier 2 can compare the facial feature information recognized by the face recognition module 1 with the pre-stored facial feature information of the elderly. The facial recognition module 1 is used to compare the facial feature information of the elderly, and after the comparison, the basic information of the elderly and the frailty-related monitored data are output. The basic information of the elderly includes name, gender, age, etc. The frailty-related monitored data includes underlying diseases, weight changes in the past three months, vital signs, etc. These frailty-related monitored data are detected and stored in the data identifier 2 when the elderly receive daily services; a gait acquisition module 3 is set below the face recognition module 1 for collecting gait feature information of the elderly passing by. The gait acquisition module 3 can also be set in hospitals, nursing homes, community elderly activity centers, etc. The face recognition module 1 is mounted on the wall of the passage, but its position is lower than that of the face recognition module 1, so as to facilitate the non-sensing collection of the gait feature information of the elderly, which includes walking speed, step length, gait cycle, step width, etc.; a weight detection module 4 is arranged under the ground and is suitable for detecting the weight information of the elderly passing by. The weight detection module 4 is arranged below the ground and is also convenient for non-sensing detection of the weight of the elderly; and the data identifier 2, the gait acquisition module 3 and the weight detection module 4 are respectively connected to the data identifier 2, the gait acquisition module 3 and the weight detection module 4 for collecting the corresponding basic information of the elderly and the monitored data related to weakness, the gait acquisition data and the weight detection module 4 according to the output of the data identifier 2. The data processor 5 collects the gait feature information of the elderly collected by the collection module 3 and the weight information of the elderly detected by the weight detection module 4, and screens them against the standard Fried frailty risk assessment scale, and outputs the frailty risk screening results to remind medical staff. The data processor 5 is the data information processing center of the entire device. After receiving the data information of the data identifier 2, the gait collection module 3 and the weight detection module 4 and classifying and integrating them, it screens them against the existing standard Fried frailty risk assessment scale, and finally outputs the frailty risk screening results to remind medical staff to carry out frailty intervention as soon as possible for the elderly who are at risk of frailty.

[0017] The utility model provides a device for non-sensing detection of frailty risks in the elderly. It realizes facial recognition of the elderly, integration of basic information, collection of frailty risk characteristic data, and data analysis and comparison without the elderly being aware of it. It provides risk warnings to the elderly at risk of frailty, so as to quickly, accurately and timely remind medical personnel of the risk of frailty in the elderly and thus intervene in the frailty as early as possible. Compared with the existing technology, the device provided by the present invention for non-sensing detection of frailty risk in the elderly has the following advantages: 1. It automatically retrieves routine detection data, i.e., frailty-related monitored data, to avoid duplication of work. The device can be used for a long time after installation without manual measurement and evaluation; 2. During the evaluation period, the elderly do not know the actual location of the detection device and cannot deliberately adjust their own state, so that the elderly's real data can be better collected with high accuracy; 3. The evaluation results can promptly identify the elderly at risk of frailty; 4. The evaluation data is more comprehensive and complete: the elderly do not need to deliberately set aside time to participate in the evaluation, and the evaluation can be completed during daily walking, and more data on the elderly can be collected. At the same time, in addition to collecting walking speed, the device can also collect other gait characteristics of the elderly. After comparing these gait characteristic data before and after, it has a certain reference role (Fried's indicators for evaluating frailty are very simple, but some studies believe that some changes in gait characteristics may indicate frailty).

[0018] As a specific embodiment, the face recognition module 1 is implemented by a face recognition camera, and the gait collection module 3 is implemented by a gait collection camera, that is, the face and gait features of the elderly are recognized and collected by the camera, and such operation can be completed without the elderly's perception. The specific structure and working principle of the face recognition camera and gait collection camera are existing technologies well known to technicians in this field, and therefore will not be repeated here.

[0019] As a specific embodiment, the weight detection module 4 is implemented using an existing pressure sensor, the specific structure and working principle of the pressure sensor are well known to those skilled in the art; of course, those skilled in the art can also use an existing weighing sensor to achieve non-sensing detection of the elderly's weight.

[0020] As a specific embodiment, the data identifier 2 and the data processor 5 are implemented using the existing MSP430 single-chip microcomputer. The MSP430 single-chip microcomputer is a 16-bit ultra-low power mixed signal processor with a reduced instruction set. In response to actual application needs, it integrates multiple analog circuits, digital circuit modules and microprocessors with different functions on one chip to provide a single-chip microcomputer solution, which is very suitable for application in this device.

[0021] As a specific embodiment, the device also includes a liquid crystal touch screen 6 connected to the data processor 5 and suitable for displaying and outputting the frailty risk screening results, and a speaker 7 connected to the data processor 5 and suitable for voice reminders to medical personnel, thereby making it possible to display the frailty risk screening results more intuitively and remind medical personnel more timely.

[0022] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the utility model and are not limiting. Although the utility model is described in detail with reference to the preferred embodiments, ordinary technicians in this field should understand that the technical solution of the utility model can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution of the utility model, which should be included in the scope of the claims of the utility model.

Claims

1. A device for detecting the risk of frailty in the elderly without any sense of touch, characterized by: The system comprises a face recognition module suitable for automatically identifying facial feature information of a passing elderly person, a data identifier connected to the face recognition module for outputting basic information of the elderly person and frailty-related monitored data according to the identified facial feature information of the elderly person, a gait acquisition module arranged below the face recognition module for collecting gait feature information of a passing elderly person, a weight detection module arranged under the ground for detecting weight information of a passing elderly person, and a data processor connected to the data identifier, the gait acquisition module and the weight detection module respectively for screening according to the basic information of the elderly person and frailty-related monitored data output by the data identifier, the gait feature information of the elderly person collected by the gait acquisition module and the weight information of the elderly person detected by the weight detection module, against the standard Fried frailty risk assessment scale, and outputting the frailty risk screening results to alert medical personnel.

2. The device for detecting frailty risk in the elderly according to claim 1, characterized in that: The face recognition module adopts a face recognition camera, and the gait collection module adopts a gait collection camera.

3. The device for detecting frailty risk in the elderly according to claim 1, characterized in that: The weight detection module adopts a pressure sensor.

4. The device for detecting frailty risk in the elderly according to claim 1, characterized in that: The data identifier and data processor adopt MSP430 single chip microcomputer.

5. The device for detecting frailty risk in the elderly without any sense of touch according to claim 1, characterized in that: The device also includes a liquid crystal touch screen connected to the data processor and suitable for displaying and outputting frailty risk screening results, and a speaker connected to the data processor and suitable for voice reminders to medical personnel.

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