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Enhancing Vibroarthrography by using Sensor Fusion

 
: Kraft, Dimitri; Bader, Rainer; Bieber, Gerald

:

Ansari, Nirwan (Ed.) ; Institute for Systems and Technologies of Information, Control and Communication -INSTICC-, Setubal:
SENSORNETS 2020, 9th International Conference on Sensor Networks. Proceedings : February 28-29, 2020, in Valletta, Malta
Setubal: SciTe Press, 2020
ISBN: 978-989-758-403-9
S.129-135
International Conference on Sensor Networks (SENSORNETS) <9, 2020, Valletta>
Bundesministerium fur Wirtschaft und Energie BMWi (Deutschland)
ZIM-16KN04913; MOREBA
Englisch
Konferenzbeitrag
Fraunhofer IGD ()
Mobile devices; Accelerometer; Microphone; Lead Topic- Individual Health; Research Line- Human computer interaction (HCI)

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.

: http://publica.fraunhofer.de/dokumente/N-586498.html