Markerless Behavior Monitoring System for Diagnosis Support of Developmental Disorder Symptoms in Children

Background: The elderly are prone to do some abnormal behaviors, such as tumbling or stepping out of the guardians’ monitoring area. These abnormal behaviors bring enormous hidden dangers to the health of the elderly, which need to be monitored effectively in order to be dealt with in time. Objective: Provide an approach based on Wireless Sensor Network (WSN) and Multi-Layer Perceptron (MLP) to establish the behaviors monitoring system for the elderly. Methods: A behavior monitoring system based on wireless sensor network and neural network is proposed in this paper, according to the behavior characteristics of the elderly. The system collects real-time behavior data of the elderly by wearing a bracelet with acceleration sensors wore on their hands. And then a behavior recognition model of the elderly is established through the MLP and the collected behavior data. The established behavior recognition model is used to classify and identify the five typical behavior characteristics of the elderly, such as walking, sitting, lying, standing and tumbling. At the same time, the location information of the elderly is estimated by the centroid localization technology based on Received Signal Strength Indication (RSSI) ranging. Results: The experiment results show that the designed system can timely acquire the behavior characteristic parameters of the elderly, and it can accurately identify the five typical behaviors with a 100% recognition accuracy rate. And also, it can timely give the warning of the abnormal behaviors of the elderly, such as tumbling or walking out of the active area. Conclusion: The proposed system in this paper can accurately identify the abnormal behaviors of elderly and timely inform the guardians. The proposed monitoring method can effectively reduce the hurt injury elderly, and can improve the work efficiency of guardians. And it has its theoretical and practical value.

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Computer Vision Based Privacy Protected Fall Detection and Behavior Monitoring System for the Care of the Elderly

10.1109/etfa45728.2021.9613448 ◽

2021 ◽

Author(s):

Yugma P.N. Fernando ◽

Kasun D.B. Gunasekara ◽

Kumary P. Sirikumara ◽

Upeksha E. Galappaththi ◽

Thusithanjana Thilakarathna ◽

...

Keyword(s):

Computer Vision ◽

Monitoring System ◽

Fall Detection ◽

The Elderly ◽

Behavior Monitoring ◽

And Behavior

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Implementation of Lightweight BHO Hijack Technology for Online Behavior Monitoring

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.539.390 ◽

2014 ◽

Vol 539 ◽

pp. 390-394

Author(s):

Jin Wang ◽

He Yin ◽

Yan Ling

Keyword(s):

Monitoring System ◽

Modular Design ◽

Design Strategy ◽

Online Behavior ◽

Web Page ◽

Internet Applications ◽

Behavior Monitoring ◽

Internet Behavior ◽

Wide Range ◽

Communication Efficiency

With the increasingly wide range of Internet applications, Internet behavior monitoring aroused widespread concern. With BHO hijacking techniques to build an efficient monitoring system, not only can achieve real-time monitoring online behavior, but also has a lightweight characteristics, not only that, but also be able to effectively shield the site or filtered, to avoid unauthorized users from bad web , but also effectively prevent the illegal intrusion of the Web page. In the system design process, the application, the application of advanced signal report have both modular design strategy, so that the system has relatively broad applicability and can be private users, the user unit may be, in addition, the system In the communication efficiency is relatively good. In short, the Internet behavior of the monitoring system has won the people's widespread recognition.

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