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

Posatskiy, A.O.; Chau, Tom

doi:10.1016/j.jelekin.2011.09.004

Cited by 56 publications

(43 citation statements)

References 24 publications

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“…These applications include, for example, the characterization of neuromuscular disorders [40]- [42], the development of prosthesis and/or switch control [28], [43], studying MU activity [21], [44], [45], examining mechanical properties during exercises [46]- [48], and in investigating rehabilitation systems [49], [50]. In addition, we have found several studies which conducted research on MMG sensor development [7], [26], [51], simultaneously testing multiple sensors and comparing their effects on muscles [52], [53]. We also have summarized studies regarding the sensor placement effect on muscles [30], [54].…”

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confidence: 99%

Mechanomyography Sensor Development, Related Signal Processing, and Applications: A Systematic Review

et al. 2013

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Mechanomyography (MMG) is extensively used in the research of sensor development, signal processing, characterization of muscle activity, development of prosthesis and/or switch control, diagnosis of neuromuscular disorders, and as a medical rehabilitation tool. Despite much existing MMG research, there has been no systematic review of these. This paper aims to determine the current status of MMG in sensor development, related signal processing, and applications. Six electronic databases were extensively searched for potentially eligible studies published between 2003 and 2012. From a total of 175 citations, 119 were selected for full-text evaluation and 86 potential studies were identified for further analysis. This systematic review initially reveals that the development of accelerometers for MMG is still in the initial stage. Another important finding of this paper is that sensor placement location on muscles may influence the MMG signal. In addition, we observe that the majority of research processes MMG signals using wavelet transform. Time/frequency domain analysis of MMG signals provides useful information to examine muscle. In addition, we find that MMG may be applied to diagnose muscle conditions, to control prosthesis and/or switch devices, to assess muscle activities during exercises, to study motor unit activity, and to identify the type of muscle fiber. Finally, we find that the majority of the studies use accelerometers as sensors for MMG measurements. We also observe that currently MMG-based rehabilitation is still in a nascent stage. In conclusion, we recommend further improvements of MMG in the areas of sensor development, particularly on accelerometers, and signal processing aspects, as well as increasing future applications of the technique in prosthesis and/or switch control, clinical practices, and rehabilitation.

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Mechanomyography Sensor Development, Related Signal Processing, and Applications: A Systematic Review

et al. 2013

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“…-structure of the tissues transmitting the vibrations (though skinfold thickness seems to have no or limited impact on the time and frequency domain parameters of the MMG) [22][23][24]; -motion artefacts originating from movements of the patient [25]; -not constant force pressing the sensor to the patient's skin [26].…”

Section: Trial Measurementsmentioning

confidence: 99%

Verification of the functionality of device for monitoring human tremor

Szumilas

Lewenstein

Ślubowska

2015

Biocybernetics and Biomedical Engineering

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“…This work uses microphone collection, due to its accurate results in detecting muscle activity, and benefits of rejecting motion noise better than the other collection methods, specifically accelerometers [10].…”

Section: A Mechanomyographymentioning

confidence: 99%

Pervasive Motion Tracking and Muscle Activity Monitor

Woodward¹,

Shefelbine²,

Vaidyanathan³

2014

2014 IEEE 27th International Symposium on Computer-Based Medical Systems

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This paper introduces a novel human activity monitoring system combining Inertial Measurement Units (IMU) and Mechanomyographic (MMG) muscle sensing technology. While other work has recognised and implemented systems for combined muscle activity and motion recording, they have focused on muscle activity through EMG sensors, which have limited use outside controlled environments. MMG is a low frequency vibration emitted by skeletal muscle whose measurement does not require gel or adhesive electrodes, potentially offering much more efficient implementation for pervasive use. We have developed a combined IMU and MMG sensor the fusion of which provides a new dimension in human activity monitoring and bridges the gap between human dynamics and muscle activity. Results show that synergy between motion and muscle detection is not only viable, but straightforward, inexpensive, and can be packaged in a lightweight wearable package.

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

Cited by 56 publications

References 24 publications

Mechanomyography Sensor Development, Related Signal Processing, and Applications: A Systematic Review

Mechanomyography Sensor Development, Related Signal Processing, and Applications: A Systematic Review

Verification of the functionality of device for monitoring human tremor

Pervasive Motion Tracking and Muscle Activity Monitor

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