Research On Smart Clothing With Functions Of Fall Detection And Early Warning For The Elderly

Nowdays,the problem of an aging population is becoming increasingly severe.The elderly will occur reduced physical functional as the growth of the age,such as decreased function of various body systems,weakened balance and coordination,and poor visual function,which will lead to a series of diseases and endanger human body health.Fall is the main health problem facing the elderly worldwide in the above question.If the elderly cannot get effective treatment in time after falling,it will cause more harm to the elderly.Therefore,it is necessary to carry out research on fall detection and early warning for the elderly.At the same time,it is of great significance to develop a smart intelligent clothing with fall detection and early warning function.The main purpose of this paper is to develop a smart clothing with funcions of fall detection and early warning for the elderly,which mainly includes three aspects.Firstly,we have proposed a smart clothing design framework based on the design model of protective clothing.The core of smart clothing is to make the clothing have the dual ability of perception and reaction.Therefore,the design framework is built around these two core capabilities.It determines which aspect of perception the smart clothing has,and then determine the method of achieving the perception and reaction ability.Combining the design of the garment,it need consider organically integrating the above devices,and complete the development of a smart garment.Secondly,under the guidance of the design framework of smart clothing,we analyze the causes of falls and the fall process of the elderly according to the physiological characteristics of the elderly,and determine to research the work of smart clothing for the fall detection and early warning of the elderly through the perception of the human behavior state.We use inertial sensors to sense human state and obtain human behavior data.Then we have established a fall detection and early warning model based on BP neural network.The fall detection module is used to detect the occurrence of human falling behavior,and the fall warning module is used to detect the occurrence of human abnormal gait.The constructed model is evaluated by two indicators of sensitivity and specificity.The evaluation results show that the numerical values of the two indicators are all around 98%,which proves that the model is feasible.Finally,with the clothing as the carrier,the fall detection and early warning module is integrated with the clothing to develop a smart clothing with functions of the fall detection and early warning for the elderly.A core problem in the integration process is the influence of clothing on the detection module during human activities.We studied the influence of clothing material and looseness on the model through experiments.The results show that the sensitivity and specificity of the two indicators of the integrated model and the model before integration with the garment are both around 98%.The data shows that the material and looseness of clothing in a certain range have little effect on the model.Based on,we have determined the final smart clothing design.