Millimeter wave radar-based housebound elderly behavior monitoring method and system

Abstract

The invention discloses a millimeter wave radar-based housebound elderly behavior monitoring method and system. The method comprises the following steps that: a user sets background information in a customized manner; a millimeter wave radar module collects heartbeat information, respiratory frequency, position information and posture information of a person and sends the information to a gateway; the gateway compares the received information with a preset threshold value, and when it is judged that fluctuation abnormity occurs, positioning and posture detection functions are started; the millimeter wave radar module carries out person positioning again and collects person posture information; image information is generated by utilizing the background information, the positioning information, the heartbeat information, the respiratory frequency and the posture information; machine learning model parameters are selected based on the person posture information; and the image information is imported into the selected machine learning model parameters, and feature information is extracted so as to be used for discrimination and classification . According to the method and system, health state monitoring requirements of the housebound elderly, personalized customization and non-contact monitoring can be achieved, and timeliness, reliability, accuracy and effectiveness are high.

Description

technical field [0001] The invention relates to a method and system for monitoring the behavior of the elderly at home based on a millimeter wave radar, belonging to the field of behavior monitoring of the Internet of Things. Background technique [0002] Aging has become an unavoidable trend in society. The number of elderly people who are alone at home is gradually increasing. On the other hand, in nursing homes, the number of elderly people is also significantly more than the number of nursing staff. It is difficult for nursing staff to pay attention to the status of the elderly in real time. Failure to intervene in time when a disease occurs can easily lead to serious consequences. Although advanced wearable devices or video monitoring equipment can pay attention to the real-time status of the elderly, they also face insurmountable problems, including expensive and inconvenient wearing of contact devices, the elderly are prone to resistance, and privacy issues caused by ...

AI Technical Summary

Problems solved by technology

[0002] Aging has become an unavoidable trend in society. The number of elderly people who are alone at home is gradually increasing. On the other hand, in nursing homes, the number of elderly people is also significantly more than the number of nursing staff. It is difficult for nursing staff to pay attention to the status of the elderly in real time. Failure to intervene in time when a disease occurs can easily lead to serious consequences

Although advanced wearable devices or video monitoring equipment can pay attention to the real-time status of the elderly, they also face insurmountable problems, including expensive and inconvenient wearing of contact devices, the elderly are prone to resistance, and privacy issues caused by video monitoring equipment, resulting in Such schemes are difficult to implement

In addition, the health problems faced by different elderly people are also different, and the judgments of different health states have different processing of the detection information. The classification and judgment based on a single model also leads to a single application scenario of the traditional non-contact detection scheme.

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