Literature DB >> 16213256

A self-contained, mechanomyography-driven externally powered prosthesis.

Jorge Silva1, Winfried Heim, Tom Chau.   

Abstract

The measurement of the low-frequency (5-50 Hz) "sounds" or vibrations produced by contracting muscles is termed mechanomyography (MMG). As a control signal for powered prostheses, MMG offers several advantages over conventional myoelectric control, including, nonspecific sensor placement, distal signal measurement, robustness to changing skin impedance, and reduced sensor costs. The objectives of this study were to demonstrate 2-function prosthesis control based on a triplet of distally recorded, normalized root mean square MMG signals and to identify necessary future research toward full clinical implementation of MMG signals in upper-limb externally powered prostheses. A novel self-contained MMG-driven prosthesis for below-elbow amputees was designed, implemented, and preliminarily tested on 2 subjects. This prosthesis was composed of specialized software and hardware modules that emulate a 2-site electromyography sensing system. Although the use of MMG signals for prosthesis control has been shown previously, we report, for the first time, successful control within a self-contained unit in unconstrained environments. Specifically, essential requirements for practical use, such as standardized sensor attachment, basic noise elimination, and miniaturization of the system, have been achieved. Both subjects were able to voluntarily open and close the prosthesis hand with no significant delays from intention to action (approximately 120 ms). Quantitative analyses revealed 88% and 71% control accuracy for subjects 1 and 2, respectively.

Mesh:

Year:  2005        PMID: 16213256     DOI: 10.1016/j.apmr.2005.03.034

Source DB:  PubMed          Journal:  Arch Phys Med Rehabil        ISSN: 0003-9993            Impact factor:   3.966


  20 in total

1.  Estimation of elbow flexion force during isometric muscle contraction from mechanomyography and electromyography.

Authors:  Wonkeun Youn; Jung Kim
Journal:  Med Biol Eng Comput       Date:  2010-06-04       Impact factor: 2.602

2.  Comparative study of a muscle stiffness sensor and electromyography and mechanomyography under fatigue conditions.

Authors:  Hyonyoung Han; Sungho Jo; Jung Kim
Journal:  Med Biol Eng Comput       Date:  2015-03-10       Impact factor: 2.602

3.  Effects of age and stimulus on submental mechanomyography signals during swallowing.

Authors:  Joon Lee; Tom Chau; Catriona M Steele
Journal:  Dysphagia       Date:  2009-01-14       Impact factor: 3.438

4.  The design and testing of a novel mechanomyogram-driven switch controlled by small eyebrow movements.

Authors:  Natasha Alves; Tom Chau
Journal:  J Neuroeng Rehabil       Date:  2010-05-21       Impact factor: 4.262

5.  Mechanomyography-based muscle fatigue detection during electrically elicited cycling in patients with spinal cord injury.

Authors:  Jannatul Naeem; Nur Azah Hamzaid; Md Anamul Islam; Amelia Wong Azman; Manfred Bijak
Journal:  Med Biol Eng Comput       Date:  2019-01-28       Impact factor: 2.602

6.  The effect of accelerometer location on the classification of single-site forearm mechanomyograms.

Authors:  Natasha Alves; Ervin Sejdić; Bhupinder Sahota; Tom Chau
Journal:  Biomed Eng Online       Date:  2010-06-10       Impact factor: 2.819

Review 7.  Non-invasive control interfaces for intention detection in active movement-assistive devices.

Authors:  Joan Lobo-Prat; Peter N Kooren; Arno H A Stienen; Just L Herder; Bart F J M Koopman; Peter H Veltink
Journal:  J Neuroeng Rehabil       Date:  2014-12-17       Impact factor: 4.262

8.  Mechanomyographic parameter extraction methods: an appraisal for clinical applications.

Authors:  Morufu Olusola Ibitoye; Nur Azah Hamzaid; Jorge M Zuniga; Nazirah Hasnan; Ahmad Khairi Abdul Wahab
Journal:  Sensors (Basel)       Date:  2014-12-03       Impact factor: 3.576

9.  Toward attenuating the impact of arm positions on electromyography pattern-recognition based motion classification in transradial amputees.

Authors:  Yanjuan Geng; Ping Zhou; Guanglin Li
Journal:  J Neuroeng Rehabil       Date:  2012-10-05       Impact factor: 4.262

10.  Novel pseudo-wavelet function for MMG signal extraction during dynamic fatiguing contractions.

Authors:  Mohammed Rashid Al-Mulla; Francisco Sepulveda
Journal:  Sensors (Basel)       Date:  2014-05-28       Impact factor: 3.576

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