價格：免費
更新日期：2017-07-06
檔案大小：7.4M
目前版本：2.2
版本需求：Android 4.3 以上版本
官方網站：mailto:wmt.utcc@gmail.com
The main objective of this project is to develop an innovative software
system that can dynamically perform spatial-temporal gait analysis and
physical activity classification in order to assess the mobility and falls of
elderly people remotely in real-time. The system is designed to be utilized
as a tool that can precisely identify changes in gait parameters (e.g. stride
length) and recognize types of physical activities of the elderly based on the patterns of acceleration data. In our system, a mobile phone equipped with
motion sensors (an accelerometer and a gyroscope) has to be worn on the
waist of elderly people when they perform physical activities. It then
continuously submits sensor measurements (e.g. acceleration force angular
velocity and calculated stride length) to our remote monitoring system. The
system then processes the sensor measurements dynamically as they
arrive, performs gait analysis and activity classification with low latency,
and finally graphically displays certain gait parameters and types of
mobility-related activities of the elderly in real-time to support medical
staffs in diagnosing diseases and planning the treatment. In the case of fall
risk is identified or a fall event is detected, an instant notification will be
sent to caregivers who provide care and support for the elderly via a
dedicated mobile application. Furthermore, in case that immobility is
detected (elderly people sit or lie in bed for long periods of time), the
system will notify caregivers immediately as well.
