Mechanomyographic Analysis with 0.2 S and 1.0 S Time Delay after Onset of Contraction

Resumo: Muscle contractions generate lateral oscillations and motion artifacts that can be detected by MMG sensors placed in the inner and outer sides of the forearm. These artifacts can significantly affect signal processing and eventually it is necessary to eliminate their influence in order to detect movements reliably. One approach is to respect a time delay after the onset of contraction. This study aimed to evaluate the correlation of 0.2 s and 1.0 s time delays after the onset of contraction during wrist movements. This work respected two different time delays before initiating the signal analysis. Two analysis window lengths were evaluated (0.25 s and 0.50 s). The results showed that there are strong correlations between the acquired signals with both time delays, mainly the devised RZ feature (0.81– 0.95). This study was a first approach to determine whether triaxial MMG features can be used for motor prosthesis control. The axial moduli presented strong correlations for all movements and can be productive in future applications. Palavras-chave: accelerometer, prosthesis control, upper limb, time delay, onset of contraction, motion artifact.

[1]  Y. Nolan,et al.  The mechanomyogram as a channel of communication and control for the disabled , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[2]  Tom Chau,et al.  Coupled microphone-accelerometer sensor pair for dynamic noise reduction in MMG signal recording , 2003 .

[3]  Joseph J. Cipriano Photographic Manual of Regional Orthopaedic and Neurological Tests , 1991 .

[4]  Travis W. Beck,et al.  Mechanomyographic and electromyographic time and frequency domain responses during submaximal to maximal isokinetic muscle actions of the biceps brachii , 2004, European Journal of Applied Physiology.

[5]  Joaquim Filipe,et al.  Identification of Hand Movements based on MMG and EMG Signals , 2008, BIOSIGNALS.

[6]  Kevin B. Englehart,et al.  A robust, real-time control scheme for multifunction myoelectric control , 2003, IEEE Transactions on Biomedical Engineering.

[7]  A. Fourment,et al.  Summation of elementary phonomyograms during isometric twitches in humans , 1998, European Journal of Applied Physiology and Occupational Physiology.

[8]  Maria Andrew Photographic Manual of Regional Orthopaedic and Neurological Tests , 1999 .

[9]  Percy Nohama,et al.  Mechanomyographic Sensor - a Triaxial Accelerometry Approach , 2008, BIODEVICES.

[10]  T. Housh,et al.  Mechanomyographic and electromyographic responses to eccentric and concentric isokinetic muscle actions of the biceps brachii , 1998, Muscle & nerve.

[11]  Marek Kurzynski,et al.  Hand movement recognition based on biosignal analysis , 2009, Eng. Appl. Artif. Intell..

[12]  Tom Chau,et al.  Stationarity distributions of mechanomyogram signals from isometric contractions of extrinsic hand muscles during functional grasping. , 2008, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.