A monitoring system for home-based physiotherapy exercises

Loading...
Thumbnail Image

Date

2013

Authors

Ar, İlktan
Akgül, Yusuf Sinan

Journal Title

Journal ISSN

Volume Title

Publisher

Open Access Color

OpenAIRE Downloads

OpenAIRE Views

Research Projects

Organizational Units

Journal Issue

Abstract

This paper describes a robust low-cost vision based monitoring system for home-based physical therapy exercises (HPTE). Our system contains two different modules. The first module achieves exercise recognition by building representations of motion patterns stance knowledge and object usage information in gray-level and depth video sequences and then combines these representations in a generative Bayesian network. The second module estimates the repetition count in an exercise session by a novel approach. We created a dataset that contains 240 exercise sessions and tested our system on this dataset. At the end we achieved very favourable recognition rates and encouraging results on the estimation of repetition counts. © 2013 Springer-Verlag London.

Description

Keywords

Turkish CoHE Thesis Center URL

Fields of Science

Citation

7

WoS Q

N/A

Scopus Q

N/A

Source

Volume

Issue

Start Page

487

End Page

494