DocumentCode
1600550
Title
Poster abstract: MARS: A muscle activity recognition system using inertial sensors
Author
Mokaya, Frank ; Kuo, Chia-Chen ; Pei Zhang
Author_Institution
Carnegie Mellon Univ., Pittsburgh, PA, USA
fYear
2012
Firstpage
97
Lastpage
98
Abstract
We present MARS, a muscle activity recognition system that uses inertial sensors to capture the vibrations of active mus-cles. Specifically, we show how accelerometer data capturing these vibrations in the quadriceps, hamstrings and calf muscles of the human leg, can be leveraged to create muscle vibration signatures. We finally show that these vibration signatures can be used to distinguish these muscles from each other with greater than 85% precision and recall.
Keywords
body sensor networks; electromyography; feature extraction; medical signal processing; signal classification; vibrations; MARS; accelerometer data capturing; active muscles; calf muscles; electromyography; feature extraction; hamstrings; human leg; inertial sensors; muscle activity recognition system; muscle vibration signatures; quadriceps; vibration capturing; Magnetic sensors; Mars; Muscles; Sensor phenomena and characterization; Sensor systems; Vibrations; Muscle activity recognition; body sensors; inertial sensors;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Processing in Sensor Networks (IPSN), 2012 ACM/IEEE 11th International Conference on
Conference_Location
Beijing
Type
conf
DOI
10.1109/IPSN.2012.6920973
Filename
6920973
Link To Document