Research on Elderly Assistance Detection Algorithm Based on Mobile Phone Gyroscope
With the intensification of population aging,falls among the elderly have become a focus of social attention.This study is based on the background of population aging,aiming to improve the quality of life of the elderly,especially to prevent and handle falls among the elderly.This article designs a gyroscope based elderly assistance detection algorithm and applies it to related apps.The algorithm aims to detect falls in a timely manner and prevent accidents by monitoring the body posture and movement status of elderly people in real time.Technically,the algorithm in this article uses gyroscope sensors to obtain attitude information,utilizes deep learning models such as convolutional neural networks for feature learning,repairs damaged images through models such as long short-term memory networks,and optimizes the repair effect through threshold detection technology.This comprehensive technical solution aims to compensate for the shortcomings of traditional elderly care and improve the safety of elderly people's lives.Algorithms have the advantages of lightweight embedding,high sensitivity,high accuracy,and fast response,which can provide timely assistance to the elderly and reduce the incidence of falls.
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维普
