Enhancing Vibroarthrography by using Sensor Fusion

Dimitri Kraft, Rainer Bader, Gerald Bieber

2020

Abstract

Natural and artificial joints of a human body are emitting vibration and sound during the movement. The sound and vibration pattern of a joint is characteristic and changes due to damage, uneven tread wear, injuries, or other influences. Hence, the vibration and sound analysis enables an estimation of the joint condition. This kind of analysis, vibroarthrography (VAG), allows the analysis of diseases like arthritis or osteoporosis and might determine trauma, inflammation, or misalignment. The classification of the vibration and sound data is very challenging and needs a comprehensive annotated data base. Current existing data bases are very limited and insufficient for deep learning or artificial intelligent approaches. In this paper, we describe a new concept of the design of a vibroarthrography system using a sensor network. We discuss the possible improvements and we give an outlook for the future work and application fields of VAG.

Paper Citation

in Harvard Style

Kraft D., Bader R. and Bieber G. (2020). Enhancing Vibroarthrography by using Sensor Fusion. In Proceedings of the 9th International Conference on Sensor Networks - Volume 1: SENSORNETS, ISBN 978-989-758-403-9, pages 129-135. DOI: 10.5220/0009098701290135

in Bibtex Style

@conference{sensornets20,
author={Dimitri Kraft and Rainer Bader and Gerald Bieber},
title={Enhancing Vibroarthrography by using Sensor Fusion},
booktitle={Proceedings of the 9th International Conference on Sensor Networks - Volume 1: SENSORNETS,},
year={2020},
pages={129-135},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009098701290135},
isbn={978-989-758-403-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Conference on Sensor Networks - Volume 1: SENSORNETS,
TI - Enhancing Vibroarthrography by using Sensor Fusion
SN - 978-989-758-403-9
AU - Kraft D.
AU - Bader R.
AU - Bieber G.
PY - 2020
SP - 129
EP - 135
DO - 10.5220/0009098701290135