Research On Mental And Physical Health Evaluation Method Based On Wearable Bracelet Multi-Feature Perception

With the rapid development of sensor technology,wearable devices have been used in many research fields,and social signals and emotional computing are one of them.People's living conditions are constantly improving,and the pressure of work and life is also increasing.Most people have only been concerned about their physical health before,and now they have paid more attention to their mental,physical,and mental conditions.In previous surveys and evaluations of physical and mental health,most of the methods adopted were carried out by specific experimental methods,questionnaire methods,and interview methods,and these methods were inevitably affected by subjective factors during the evaluation process,making the results not objective.When people have physical and mental health problems,they rarely actively seek treatment in a timely manner,resulting in irreparable consequences.Therefore,it is of certain significance to establish an objective and timely physical and mental health monitoring system.This article uses wearable devices and based on the Internet of Things technology to build a full-link system that includes device terminals to the cloud server for processing,computing,storage,and visualization.It does not affect the normal work and life of individuals,and conducts long-term monitoring experiments.Collect various physical and environmental data of the learner,and construct a physical and mental health assessment system based on multi-sensor characteristics by mining the mapping relationship between multiple types of sensory data and mental state.The main research work of this paper is as follows: 1)Design a multi-sensory bracelet and cloud server,build a wearable physical and mental health monitoring system for the Internet of Things,and conduct a one-month physical and mental health monitoring experiment.Participants objectively collect the wearer's Physical information.2)Through the feature extraction of the experimental data,a total of 136 acceleration features,136 angular velocity features,288 environmental sign features,and 104 voice features were obtained.3)Compare the scores of autism,enthusiasm,and anxiety,and explore the nuances of the sensing characteristics of the opposite characteristics population under the long-term trend.4)Based on the fusion of various types of sensory features,the differences in the physical and mental health assessment of positive and negative emotions by different fusion feature methods are explored,and the voice and behavior characteristics are integrated to establish the physical and mental health assessments of positive and negative emotions.system.