Upper-limb prosthetic control using wearable multichannel mechanomyography

In this paper we introduce a robust multi-channel wearable sensor system for capturing user intent to control robotic hands. The interface is based on a fusion of inertial measurement and mechanomyography (MMG), which measures the vibrations of muscle fibres during motion. MMG is immune to issues su...

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Veröffentlicht in:IEEE International Conference on Rehabilitation Robotics Jg. 2017; S. 1293 - 1298
Hauptverfasser: Wilson, Samuel, Vaidyanathan, Ravi
Format: Tagungsbericht Journal Article
Sprache:Englisch
Veröffentlicht: United States IEEE 01.07.2017
Schlagworte:
Adult
Amputees - rehabilitation
Arm - physiology
Artificial Limbs
Control systems
Electromyography
Female
Gestures
Humans
Male
Middle Aged
Muscles
Myography - instrumentation
Myography - methods
Prosthetics
Robots
Signal Processing, Computer-Assisted - instrumentation
Skin
Vibrations
Young Adult
ISSN:1945-7901, 1945-7901
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Zusammenfassung:In this paper we introduce a robust multi-channel wearable sensor system for capturing user intent to control robotic hands. The interface is based on a fusion of inertial measurement and mechanomyography (MMG), which measures the vibrations of muscle fibres during motion. MMG is immune to issues such as sweat, skin impedance, and the need for a reference signal that is common to electromyography (EMG). The main contributions of this work are: 1) the hardware design of a fused inertial and MMG measurement system that can be worn on the arm, 2) a unified algorithm for detection, segmentation, and classification of muscle movement corresponding to hand gestures, and 3) experiments demonstrating the real-time control of a commercial prosthetic hand (Bebionic Version 2). Results show recognition of seven gestures, achieving an offline classification accuracy of 83.5% performed on five healthy subjects and one transradial amputee. The gesture recognition was then tested in real time on subsets of two and five gestures, with an average accuracy of 93.3% and 62.2% respectively. To our knowledge this is the first applied MMG based control system for practical prosthetic control.
Bibliographie:ObjectType-Article-1
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ISSN:1945-7901
1945-7901
DOI:10.1109/ICORR.2017.8009427