The frailty of elderly people is a big risk, when living independently. Frailty often leads to falls and injuries resulting from a fall. Hence, the level of frailty is an important indicator to assess the risk of falling and provide countermeasures already at an early stage.
The goal of this work is the assessment of the frailty level based on 3D tracking data, obtained from a 3D sensor (e.g. Kinect) within private homes. Based on the tracking data, the level of frailty should be estimated, e.g. by analyzing the movement patterns over time (amount of movement, speed, mobility etc.). The assessment of frailty need to be based on research results, allowing to identify adequate measurements.
Literature Review – getting to know the algorithms
Code Review – review the current implementation
Porting and Integrating to the existing C++ project
Evaluation – comparison with previous implementation
Matlab, or C++ and OpenCV