CN113080859A - Alzheimer's disease early warning system based on daily behavior analysis - Google Patents
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Abstract
The invention discloses an Alzheimer's disease early warning system based on daily behavior analysis, relates to the technical field of disease prevention, and solves the technical problems of high cost, small application range and low accuracy in the process of capturing and analyzing abnormal behaviors related to amnesic mild cognitive impairment symptoms in the existing scheme; the system comprises a processor, a system diagnosis module, a data acquisition module, a data analysis module, a result generation module, a monitoring display module and a data storage module; the data analysis module is arranged, so that the popularization is high, the comprehensiveness of data analysis is ensured, and the accuracy of AD early warning is improved; the early-stage AD early-warning system is provided with the result generation module, and the behavior characteristics of the symptoms related to the forgetful mild cognitive impairment can be accurately captured, so that the early-stage AD early-warning effect is achieved.
Description
Technical Field
The invention belongs to the field of disease prevention, relates to a daily behavior analysis technology, and particularly relates to an Alzheimer's disease early warning system based on daily behavior analysis.
Background
Dementia is a clinical Disease characterized by cognitive and emotional disorders, and the common symptoms are decreased memory, reasoning ability, language ability and perception ability, affecting daily functions and quality of life, among which Alzheimer Disease (AD) is the most common type affecting the elderly.
Studies have shown that when longitudinal observations are made on amnesic mild cognitive impairment patients, they progress to clinically probable AD at a considerably faster rate than healthy age-matched individuals and that diagnosis of AD is often difficult, especially in the early stages, because many of the symptoms of the disease are similar to those of natural aging; therefore, the method can accurately and efficiently detect the abnormal behaviors of the forgetful cognitive impairment patients in daily life, realize disease detection and play an important role in AD early warning.
At present, a plurality of related technologies and means are used in a home-based and old-age care intelligent system (such as a radio frequency identification device, an acceleration sensor, a pulse sensor, a GPS (global positioning system) positioning and temperature sensor and the like), and a user wears the device on the body to monitor the physical condition, the emergency and the position information of the wearer in daily life activities. However, these measures cannot accurately detect the specific behavior change of a person in daily life, and meanwhile, the above methods all require the user to wear related equipment on the trunk part, which has the disadvantages of affecting daily behavior and activity, small application range, high cost and the like. Therefore, a technology with low cost, strong applicability and high accuracy is needed to capture and analyze the abnormal behaviors related to the symptoms of the amnesic mild cognitive impairment in daily life activities.
Disclosure of Invention
In order to solve the problems existing in the scheme, the invention provides an Alzheimer's disease early warning system based on daily behavior analysis, which is used for solving the technical problems of high cost, small application range and low accuracy in the process of capturing and analyzing abnormal behaviors related to amnesic mild cognitive impairment symptoms in the existing scheme.
The purpose of the invention can be realized by the following technical scheme: an Alzheimer disease early warning system based on daily behavior analysis comprises a processor, a system diagnosis module, a data acquisition module, a data analysis module, a result generation module, a monitoring display module and a data storage module;
the data acquisition module is used for acquiring communication test duration and high-definition video data, sending the communication test duration to the system diagnosis module, and respectively sending the high-definition video data to the data analysis module and the data storage module;
the data analysis module is used for analyzing the high-definition video data, and comprises:
after the data analysis module receives the high-definition video data, decomposing the high-definition video data into images frame by frame and marking the images as video images;
establishing a two-dimensional coordinate system according to the resolution of the video image, establishing a three-dimensional coordinate system by taking a high-definition camera corresponding to the high-definition video data as an original point, and acquiring three-dimensional coordinates of 19 joint skeleton points in the video image; generating a joint coordinate linked list from the three-dimensional coordinates of the same joint skeleton point according to the time sequence; respectively sending the joint coordinate linked list to a result generation module and a data storage module;
the result generation module generates an output result according to the joint coordinate linked list and in combination with the position set by the high-definition camera group; and carrying out early warning analysis on the AD patient according to the output result.
Preferably, the early warning analysis of AD patients comprises:
acquiring forgetting times, gait abnormal labels, sleep abnormal times, dressing scores and dressing scores through output results, and respectively marking the forgetting times, the gait abnormal labels, the sleep abnormal times, the dressing scores and the dressing scores as YC, BYB, SYC, SP and CP;
obtaining an AD evaluation coefficient ADP by a formula ADP ═ SP + CP × ln (1+ α 1 × YC × SYC + α 2 × BYB); wherein both alpha 1 and alpha 2 are proportionality coefficients, and both alpha 1 and alpha 2 are real numbers greater than 0;
when ADP is greater than L1, generating and sending an AD early warning signal to a monitoring display module; otherwise, no signal is generated; where L1 is the evaluation threshold and L1 was obtained by mass data simulation.
Preferably, the monitoring display module is used for receiving the AD early warning signal and reminding a guardian.
Preferably, the forgetting times are the occurrence times of forgetting events, wherein the forgetting events comprise forgetting to turn off water, forgetting to turn off power and forgetting to close a door; the sleep disorder comprises wandering at home at night and drowsiness during the day; the gait abnormal label is comprehensively judged through stride, speed and frequency, values of the gait abnormal label are 0 and 1, when the gait abnormal label is 0, the gait is normal, and when the gait abnormal label is 1, the gait is abnormal.
Preferably, the output result comprises a synthetic tracking video, and a motion trail graph, a motion hot spot graph, a trunk joint point coordinate, a skeleton length and a skeleton direction angle are generated; the trunk joint point coordinates are three-dimensional coordinates of joint skeleton points, and the length of the skeleton is the length between connected skeletons; the range of the direction angle of the framework is 0-360 degrees.
Preferably, the 19 joint bone points are composed of head, eyes, neck, shoulders, elbows, hands, spine, arms, streams, toes and heels.
Preferably, the collecting of the communication test duration specifically includes:
sending a first test signal to a high-definition camera through a data acquisition module according to a set period, and immediately sending a second test signal to the data acquisition module when the high-definition camera receives the first test signal; the set period includes one second, one minute, and one quarter hour;
and the time difference between the receiving of the second test signal and the sending of the first test signal by the data acquisition module is acquired, and the time difference is marked as the communication test duration.
Preferably, the system diagnosis module judges the fault of the high definition camera according to the communication test duration, and the method includes:
after the system diagnosis module receives the communication test time length, marking the communication test time length as TCS;
when the TCS is more than 0 and less than L1, judging that the high-definition camera corresponding to the communication test time length TCS is normal; when the TCS is larger than or equal to L1, judging that the high-definition camera corresponding to the communication test time length TCS is abnormal, and marking the corresponding high-definition camera as a suspected camera; wherein L1 is a duration threshold, and L1 is obtained by mass data simulation;
when all the high-definition cameras in the high-definition camera group where the suspected camera is located are abnormal, generating and sending a communication abnormal signal to the monitoring display module; otherwise, generating and sending abnormal signals of the camera to the monitoring display module.
Preferably, the data acquisition module is electrically connected with the high-definition camera group; the high-definition camera group at least comprises three high-definition cameras.
Preferably, the processor is respectively in communication and/or electrical connection with the system diagnosis module, the data acquisition module, the data analysis module, the result generation module, the monitoring display module and the data storage module; the data acquisition module is respectively in communication and/or electrical connection with the system diagnosis module and the data analysis module, the monitoring display module is respectively in communication and/or electrical connection with the data storage module and the result generation module, and the result generation module is in communication and/or electrical connection with the data analysis module.
Compared with the prior art, the invention has the beneficial effects that:
1. the data analysis module is arranged for comprehensively analyzing the high-definition video data, the three-dimensional coordinate system is established by using the high-definition cameras in the high-definition camera group as the original points, and the joint coordinate linked list is generated according to the three-dimensional coordinate system of the joint skeleton points, so that the cost is low, the popularization is high, the comprehensiveness of data analysis is ensured, and the accuracy of AD early warning is improved.
2. The early warning system is provided with a result generation module, an output result is generated by combining the positions set by the high-definition camera group according to the joint coordinate linked list, early warning analysis is carried out on an AD patient according to the output result, and behavior characteristics of symptoms related to amnesic mild cognitive impairment symptoms can be accurately captured by carrying out recognition tracking and skeleton analysis on 19 joint skeleton points of a trunk, so that the early warning effect of AD is achieved.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic diagram of the principle of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The first embodiment is as follows:
referring to fig. 1, the present invention provides an alzheimer's disease early warning system based on daily behavior analysis, which includes a processor, a system diagnosis module, a data acquisition module, a data analysis module, a result generation module, a monitoring display module, and a data storage module;
the data acquisition module is used for acquiring communication test duration and high-definition video data, sending the communication test duration to the system diagnosis module, and respectively sending the high-definition video data to the data analysis module and the data storage module;
the data analysis module is used for analyzing the high-definition video data, and comprises:
after the data analysis module receives the high-definition video data, decomposing the high-definition video data into images frame by frame and marking the images as video images;
establishing a two-dimensional coordinate system according to the resolution of the video image, establishing a three-dimensional coordinate system by taking a high-definition camera corresponding to the high-definition video data as an original point, and acquiring three-dimensional coordinates of 19 joint skeleton points in the video image; generating a joint coordinate linked list from the three-dimensional coordinates of the same joint skeleton point according to the time sequence; respectively sending the joint coordinate linked list to a result generation module and a data storage module;
the result generation module generates an output result according to the joint coordinate linked list and in combination with the position set by the high-definition camera group; and carrying out early warning analysis on the AD patient according to the output result.
Further, the early warning analysis of AD patients includes:
acquiring forgetting times, gait abnormal labels, sleep abnormal times, dressing scores and dressing scores through output results, and respectively marking the forgetting times, the gait abnormal labels, the sleep abnormal times, the dressing scores and the dressing scores as YC, BYB, SYC, SP and CP;
obtaining an AD evaluation coefficient ADP by a formula ADP ═ SP + CP × ln (1+ α 1 × YC × SYC + α 2 × BYB); wherein both alpha 1 and alpha 2 are proportionality coefficients, and both alpha 1 and alpha 2 are real numbers greater than 0;
when ADP is greater than L1, generating and sending an AD early warning signal to a monitoring display module; otherwise, no signal is generated; where L1 is the evaluation threshold and L1 was obtained by mass data simulation.
Furthermore, the monitoring display module is used for receiving the AD early warning signal and reminding a guardian.
Further, the forgetting times are the occurrence times of forgetting events, wherein the forgetting events comprise forgetting to turn off water, forgetting to turn off power and forgetting to close the door; sleep disorders include wandering at home at night and daytime sleepiness; the gait abnormal label is comprehensively judged through the stride, the speed and the frequency, the value of the gait abnormal label is 0 and 1, when the gait abnormal label is 0, the gait is normal, and when the gait abnormal label is 1, the gait is abnormal.
Further, outputting a result comprising synthesizing a tracking video, and generating a motion trail graph, a motion hotspot graph, the coordinates of the trunk joint points, the length of the skeleton and the direction angle of the skeleton; the trunk joint point coordinates are three-dimensional coordinates of joint skeleton points, the skeleton length is the length between connected skeletons, such as a head-neck skeleton, and pixel points are taken as units; the range of the direction angle of the framework is 0-360 degrees, taking a head-neck framework as an example, a two-dimensional coordinate system is established by taking the nose tip as an original point, the included angle formed by the nose tip-tail root vector and the positive direction of the X axis is 0 degree if the nose tip-tail root vector is superposed with the positive direction of the X axis, the clockwise rotation angle is continuously increased, and the anticlockwise rotation angle is continuously reduced.
Further, 19 joint bone spots consist of head, eyes, neck, shoulders, elbows, hands, spine, arms, streams, toes, and heels.
Further, the collecting of the communication test duration specifically includes:
sending a first test signal to a high-definition camera through a data acquisition module according to a set period, and immediately sending a second test signal to the data acquisition module when the high-definition camera receives the first test signal; the set period includes one second, one minute, and one quarter hour;
and the time difference between the receiving of the second test signal and the sending of the first test signal by the data acquisition module is acquired, and the time difference is marked as the communication test duration.
Further, the system diagnosis module judges the fault of high definition digtal camera according to the duration of communication test, including:
after the system diagnosis module receives the communication test time length, marking the communication test time length as TCS;
when the TCS is more than 0 and less than L1, judging that the high-definition camera corresponding to the communication test time length TCS is normal; when the TCS is larger than or equal to L1, judging that the high-definition camera corresponding to the communication test time length TCS is abnormal, and marking the corresponding high-definition camera as a suspected camera; wherein L1 is a duration threshold, and L1 is obtained by mass data simulation;
when all the high-definition cameras in the high-definition camera group where the suspected camera is located are abnormal, generating and sending a communication abnormal signal to the monitoring display module; otherwise, generating and sending abnormal signals of the camera to the monitoring display module.
Further, the data acquisition module is electrically connected with the high-definition camera group; the high-definition camera group at least comprises three high-definition cameras.
Further, the processor is respectively in communication and/or electrical connection with the system diagnosis module, the data acquisition module, the data analysis module, the result generation module, the monitoring display module and the data storage module; the data acquisition module is respectively in communication and/or electrical connection with the system diagnosis module and the data analysis module, the monitoring display module is respectively in communication and/or electrical connection with the data storage module and the result generation module, and the result generation module is in communication and/or electrical connection with the data analysis module.
Example two:
referring to fig. 1, the present invention provides an alzheimer's disease early warning system based on daily behavior analysis, which includes a processor, a system diagnosis module, a data acquisition module, a data analysis module, a result generation module, a monitoring display module, and a data storage module;
the data analysis module is used for analyzing the high-definition video data to obtain an output result; acquiring forgetting times, gait abnormal labels, abnormal sleep times, dressing scores and dressing scores through output results;
further, the dressing score is 11 points, the toothpaste cover is taken down, the toothpaste is squeezed on a toothbrush, the water is opened, the teeth are brushed, the handkerchief is washed by soaking, the face is washed and the water is closed, the hair is combed, the overcoat is worn, the button is buckled, the tie is tied and the zipper is pulled, and the dressing score is 11 points when the 11 steps are completely finished.
Further, the dressing score was 10 points in total, the upper limbs were inserted into the sleeves, the sleeves were pulled up through the elbow joint, the sleeves were pulled up through the shoulder joint, the shirt was pulled up through the back to the contralateral shoulder joint, the intact upper limbs were inserted into the other sleeves, the collar was arranged, the first button was fastened, the second button was fastened, the third button was fastened, the fourth button was fastened, and the dressing score was 10 points when all of the 10 steps were completed.
Furthermore, the motor dysfunction and abnormal activities can be judged through the output result; wherein the abnormal activity comprises excessive behavior and repetitive behavior; excessive behavior is the level of excessive activity of the relevant person in the home, which, according to empirical studies, is believed to mean that if there is too much activity in a short period of time, the person may exhibit symptoms of excessive activity with mild cognitive impairment in the activity; if an elderly person has repetitive behaviors, such as walking between locations to find their goals or repeating the same actions, we consider such activities as repetitive behaviors.
The above formulas are all calculated by removing dimensions and taking numerical values thereof, the formula is a formula which is obtained by acquiring a large amount of data and performing software simulation to obtain the closest real situation, and the preset parameters and the preset threshold value in the formula are set by the technical personnel in the field according to the actual situation or obtained by simulating a large amount of data.
The working principle of the invention is as follows:
the invention adopts a multi-azimuth high spatial resolution camera, utilizes computer vision and deep academic technology, does not need other hardware equipment, and accurately captures the behavior characteristics of the symptoms related to the forgetting mild cognitive impairment symptoms by carrying out identification tracking and skeleton analysis on 19 joint skeleton points of a human trunk, such as: everyday amnestic events, sleep disorders, cognitive dysfunction (impaired fine performance: wearing clothes), motor dysfunction (abnormal gait); and obtaining an AD evaluation coefficient according to the behavior characteristics, and realizing AD early warning according to a comparison result of the AD evaluation coefficient and an evaluation threshold value.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (6)
1. An Alzheimer disease early warning system based on daily behavior analysis is characterized by comprising a processor, a system diagnosis module, a data acquisition module, a data analysis module, a result generation module, a monitoring display module and a data storage module;
the data acquisition module is used for acquiring communication test duration and high-definition video data, sending the communication test duration to the system diagnosis module, and respectively sending the high-definition video data to the data analysis module and the data storage module;
the data analysis module is used for analyzing the high-definition video data, and comprises:
after the data analysis module receives the high-definition video data, decomposing the high-definition video data into images frame by frame and marking the images as video images;
establishing a two-dimensional coordinate system according to the resolution of the video image, establishing a three-dimensional coordinate system by taking a high-definition camera corresponding to the high-definition video data as an original point, and acquiring three-dimensional coordinates of 19 joint skeleton points in the video image; generating a joint coordinate linked list from the three-dimensional coordinates of the same joint skeleton point according to the time sequence; respectively sending the joint coordinate linked list to a result generation module and a data storage module;
the result generation module generates an output result according to the joint coordinate linked list and in combination with the position set by the high-definition camera group; and carrying out early warning analysis on the AD patient according to the output result.
2. The Alzheimer's disease warning system based on daily behavior analysis of claim 1, wherein the warning analysis of AD patients comprises:
acquiring forgetting times, gait abnormal labels, sleep abnormal times, dressing scores and dressing scores through output results, and respectively marking the forgetting times, the gait abnormal labels, the sleep abnormal times, the dressing scores and the dressing scores as YC, BYB, SYC, SP and CP;
obtaining an AD evaluation coefficient ADP by a formula ADP ═ SP + CP × ln (1+ α 1 × YC × SYC + α 2 × BYB); wherein both alpha 1 and alpha 2 are proportionality coefficients, and both alpha 1 and alpha 2 are real numbers greater than 0;
when ADP is greater than L1, generating and sending an AD early warning signal to a monitoring display module; otherwise, no signal is generated; where L1 is the evaluation threshold and L1 was obtained by mass data simulation.
3. The Alzheimer's disease early warning system based on daily behavior analysis of claim 1, wherein the monitoring display module is used for receiving AD early warning signals and reminding a guardian.
4. The Alzheimer's disease early warning system based on daily behavior analysis of claim 2, wherein the forgetting times are the occurrence times of forgetting events; the gait abnormity label is comprehensively judged through the stride, the speed and the frequency.
5. The alzheimer's disease warning system based on analysis of daily behavior of claim 1 wherein 19 of said arthroscopic bone points are comprised of head, eyes, neck, shoulders, elbows, hands, spine, arms, streams, toes and heels.
6. The Alzheimer's disease early warning system based on daily behavior analysis of claim 2, wherein the output result comprises a synthetic tracking video and generates a motion trail map, a motion heat point map, trunk joint point coordinates, a skeleton length and a skeleton direction angle; the trunk joint point coordinates are three-dimensional coordinates of joint skeleton points, and the length of the skeleton is the length between connected skeletons; the range of the direction angle of the framework is 0-360 degrees.
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| CN113827869A (en) * | 2021-11-12 | 2021-12-24 | 江西希尔康泰制药有限公司 | High-potential ultrashort wave signal regulation control system for Alzheimer disease therapeutic instrument |
| CN113827869B (en) * | 2021-11-12 | 2023-05-16 | 江西希尔康泰制药有限公司 | High-potential ultrashort wave signal regulation control system for Alzheimer disease therapeutic instrument |
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Application publication date: 20210709 |