A System Design About Health Assessment Of The Elderly Based On Embedded Hardware

With the improvement of the living standards of our people and the improvement of medical conditions,the average life expectancy of the elderly has been continuously extended.On the other hand,China’s birth rate has been declining and population growth has slowed down.This means that in the foreseeable time scale,China’s aging problem will gradually increase,and the health and service needs of the elderly will become larger and larger.With the development of new communication technologies,Internet of Things technologies,and microelectronic sensor technologies,the development trend of medical smart wearable devices is very rapid.This paper proposes a collaborative approach to medical health monitoring applications by integrating wearable health monitoring systems into smart home systems.The new smart wearable devices and systems need to be low-cost and small in size,and require a high-performance processor for data processing and analysis,while having lower power consumption and longer battery life.The system mainly consists of a wearable health monitoring system,a smart home system,a central control system and a wireless communication network.The wearable health monitoring system mainly monitors cardiac activities,questions and physical activities through various sensors,and is used for mobile phones with vital signs;the smart home system can change the living environment of the elderly according to different needs;the central control system integrates emergency detection.And cellular communication network,able to observe the activities of the elderly through the camera.By leveraging the synergies between each system and between the two systems,this paper demonstrates that it can improve the efficiency of healthcare while providing the added benefit of an optimal user-friendly environment,automatically adjusting smart homes based on the given medical conditions of the residents.The environment will increase the level of care by providing comfort and safety in the living environment,which further increases life expectant.The system developed herein uses biosensor integration to distinguish between multiple physical activities and to compare changes in physiological conditions based on the user’s physical activity.After that,system learning techniques were established to achieve the scalability of the health monitoring system.The resulting system is able to monitor different users without having to explicitly change the threshold for individual users.Further improve health monitoring through integration with smart home systems to take advantage of synergies between various physiological sensors and reduce system-generated false positives.A cellular mobile network interface was developed for transmitting collected data to remote caregivers to monitor the user’s health and activity data and its surroundings.