Problem Statement
Traditional health monitoring systems often lack personalization and real-time insights. Wearable devices have the potential to provide continuous health data, but the challenge lies in creating a system that interprets and presents this data in a personalized and actionable manner.
Abstract
This project aims to develop a personalized health monitoring system utilizing wearable devices. The system will collect real-time health data from wearables, employ AI algorithms to interpret the data, and provide personalized insights. Users will receive actionable recommendations for maintaining or improving their health based on individualized trends and patterns.
Outcome
A personalized health monitoring system that leverages wearable devices to provide real-time insights, empowering users to make informed decisions about their health and well-being.
Reference
Wearable health monitoring system gain a lot of attraction from the wearable health technology community. Among wearable health devices, smart wrist band is one of the branches that the market invested most of money and there exist varies products aiming at different custom target group such as users who have cardiovascular diseases. However, there has few products that can monitoring heart rate continuously with low power consumption and able to detect the abnormal movement of body which may lead to the diagnosis of early Parkinson’s diseases(PD).This project propose a low-power consumption, customized wrist band with small size and pattern matching ability which help to analysis the abnormal behaviour that many early PD patients have, together with a user end program for data transferring, demonstration and further analysis. Results of the wrist band and user end program are tested, verified and compared, which shows that the wrist band is able to detect heart rate, counting steps and detecting abnormal hand movement, and user end program can properly receive the information from the wrist band and present to the user.