A Physical Strength Measurement and Analysis System for Elderly People Using Motion Sensors The fiscal burden of increasing social security expenses for the elderly is a major issue in Japan. The elderly lose physical fitness as they age. In particular, degradation in walking ability leads to falling accidents which pose a risk of serious wounds such as fractures that may resign one to a life in bed. In this study, we propose a system that is capable of measuring and analyzing an elderly personu0027s walking ability. The proposed system, using Kinect motion sensor and written in the programming language Scratch, can measure an elderly personu0027s gait accurately and be operated simply without specialist knowledge. Through real experiments with 16 subjects, some potential problems in walking were easily found by analyzing the measured data.

RealTime Rehabilitation and Fitness System using Depth Sensor This paper presents an action verification system for rehabilitation of patients with limited mobility. In this regard, a kinect sensor is used to capture the imagesequences of patients for identification of different actions in real time during rehabilitation exercisers at home. Then, a set of most discriminating features is extracted from a human skeleton. These features are fed to the classifier for action recognition. In order to evaluate the performance of the proposed system, we build a data set for patients with frozen shoulders and Overhead shoulder issues. The results confirm an excellent performance of the proposed system. In this paper, our contribution is three fold. 1) we have constructed a data set of overhead shoulder exercise performed by 8 different actors. 2) A novel set of features has been proposed for verification of these two exercises in real time. 3) we have employed 5 different classifiers for classification and presented a comparative analysis.