Literature DB >> 22019815

The effects of motion artifact on mechanomyography: A comparative study of microphones and accelerometers.

A O Posatskiy1, T Chau.   

Abstract

Mechanomyography (MMG) is an important kinesiological tool and potential communication pathway for individuals with disabilities. However, MMG is highly susceptible to contamination by motion artifact due to limb movement. A better understanding of the nature of this contamination and its effects on different sensing methods is required to inform robust MMG sensor design. Therefore, in this study, we recorded MMG from the extensor carpi ulnaris of six able-bodied participants using three different co-located condenser microphone and accelerometer pairings. Contractions at 30% MVC were recorded with and without a shaker-induced single-frequency forearm motion artifact delivered via a custom test rig. Using a signal-to-signal-plus-noise-ratio and the adaptive Neyman curve-based statistic, we found that microphone-derived MMG spectra were significantly less influenced by motion artifact than corresponding accelerometer-derived spectra (p⩽0.05). However, non-vanishing motion artifact harmonics were present in both spectra, suggesting that simple bandpass filtering may not remove artifact influences permeating into typical MMG bands of interest. Our results suggest that condenser microphones are preferred for MMG recordings when the mitigation of motion artifact effects is important. Copyright Â
© 2011. Published by Elsevier Ltd.

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Year:  2011        PMID: 22019815     DOI: 10.1016/j.jelekin.2011.09.004

Source DB:  PubMed          Journal:  J Electromyogr Kinesiol        ISSN: 1050-6411            Impact factor:   2.368


  9 in total

1.  Electromyography and Mechanomyography Signals During Swallowing in Healthy Adults and Head and Neck Cancer Survivors.

Authors:  Gabriela Constantinescu; William Hodgetts; Dylan Scott; Kristina Kuffel; Ben King; Chris Brodt; Jana Rieger
Journal:  Dysphagia       Date:  2016-08-26       Impact factor: 3.438

Review 2.  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

3.  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

4.  Ultrasound Measurement of Skeletal Muscle Contractile Parameters Using Flexible and Wearable Single-Element Ultrasonic Sensor.

Authors:  Ibrahim AlMohimeed; Yuu Ono
Journal:  Sensors (Basel)       Date:  2020-06-27       Impact factor: 3.576

5.  A systematic review of muscle activity assessment of the biceps brachii muscle using mechanomyography.

Authors:  Irsa Talib; Kenneth Sundaraj; Chee Kiang Lam; Sebastian Sundaraj
Journal:  J Musculoskelet Neuronal Interact       Date:  2018-12-01       Impact factor: 2.041

6.  Assisted Grasping in Individuals with Tetraplegia: Improving Control through Residual Muscle Contraction and Movement.

Authors:  Lucas Fonseca; Wafa Tigra; Benjamin Navarro; David Guiraud; Charles Fattal; Antônio Bó; Emerson Fachin-Martins; Violaine Leynaert; Anthony Gélis; Christine Azevedo-Coste
Journal:  Sensors (Basel)       Date:  2019-10-18       Impact factor: 3.576

Review 7.  Phonomyography on Perioperative Neuromuscular Monitoring: An Overview.

Authors:  Yanjie Dong; Qian Li
Journal:  Sensors (Basel)       Date:  2022-03-22       Impact factor: 3.576

Review 8.  Mechanomyogram for muscle function assessment: a review.

Authors:  Md Anamul Islam; Kenneth Sundaraj; R Badlishah Ahmad; Nizam Uddin Ahamed
Journal:  PLoS One       Date:  2013-03-11       Impact factor: 3.240

9.  A Piezoresistive Sensor to Measure Muscle Contraction and Mechanomyography.

Authors:  Daniele Esposito; Emilio Andreozzi; Antonio Fratini; Gaetano D Gargiulo; Sergio Savino; Vincenzo Niola; Paolo Bifulco
Journal:  Sensors (Basel)       Date:  2018-08-04       Impact factor: 3.576

  9 in total

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