Systematic characterisation of silicon-embedded accelerometers for mechanomyography

The effects of accelerometer placement on mechanomyographic amplitude and mean power frequency during cycle ergometry

The purposes of this study were threefold: (1) to compare the power output related patterns of absolute and normalized MMG amplitude and MPF responses for proximal and distal accelerometer placements on the vastus lateralis (VL) muscle during incremental cycle ergometry; (2) to examine the influence of accelerometer placements on mean absolute MMG amplitude and MPF values; and (3) to determine the effects of normalization on mean MMG amplitude and MPF values from proximal and distal accelerometer placements. Fifteen adults (10 men and 5 women; mean+/-SD age=23.9+/-3.1 years) performed incremental cycle ergometry tests to exhaustion. Two accelerometers were placed proximal and distal on the VL muscle. Paired t-tests indicated that absolute MMG amplitude values for the proximal accelerometer were greater (p<0.05) than the distal accelerometer at all power outputs. The normalized MMG amplitude also had greater values for the proximal accelerometer at all power outputs, except 50W. There were no differences, however, between proximal and distal accelerometers for absolute MMG MPF, except at 75W, and normalization eliminated this difference. Twenty-seven percent of the subjects exhibited different power output related patterns of responses between accelerometer placements for MMG amplitude and 47% exhibited different patterns for MPF. These findings indicated that normalization did not eliminate the influence of accelerometer placement on MMG amplitude and highlighted the importance of standardizing accelerometer placements to compare MMG values during cycle ergometry.

MMG-based classification of muscle activity for prosthesis control

We have previously proposed the use of "muscle sounds" or mechanomyography (MMG) as a reliable alternative measure of muscle activity with the main objective of facilitating the use of more comfortable and functional soft silicone sockets with below-elbow externally powered prosthesis. This work describes an integrated strategy where data and sensor fusion algorithms are combined to provide MMG-based detection, estimation and classification of muscle activity. The proposed strategy represents the first ever attempt to generate multiple output signals for practical prosthesis control using a MMG multisensor array embedded distally within a silicon soft socket. This multisensor fusion strategy consists of two stages. The first is the detection stage which determines the presence or absence of muscle contractions in the acquired signals. Upon detection of a contraction, the second stage, that of classification, specifies the nature of the contraction and determines the corresponding control output. Tests with real amputees indicate that with the simple detection and classification algorithms proposed, MMG is indeed comparable to and may exceed EMG functionally.

A Mathematical Model for Source Separation of MMG Signals Recorded With a Coupled Microphone-Accelerometer Sensor Pair

Recent advances in sensor technology for muscle activity monitoring have resulted in the development of a coupled microphone-accelerometer sensor pair for physiological acousti signal recording. This sensor can be used to eliminate interfering sources in practical settings where the contamination of an acoustic signal by ambient noise confounds detection but cannot be easily removed [e.g., mechanomyography (MMG), swallowing sounds, respiration, and heart sounds]. This paper presents a mathematical model for the coupled microphone-accelerometer vibration sensor pair, specifically applied to muscle activity monitoring (i.e., MMG) and noise discrimination in externally powered prostheses for below-elbow amputees. While the model provides a simple and reliable source separation technique for MMG signals, it can also be easily adapted to other aplications where the recording of low-frequency (< 1 kHz) physiological vibration signals is required.

Validation of an accelerometer for determination of muscle belly radial displacement

A commercial variable-capacitance micromachined accelerometer was validated for muscle belly radial displacement measurement. The displacement was calculated by the acceleration data being integrated twice and was compared with the results obtained simultaneously by an accurate mechanical displacement sensor based on an optical encoder. The aim of the investigation was to evaluate the accuracy and precision of an accelerometer for tensiomyography, which is a method for the detection of skeletal muscle contractile properties on the basis of muscle belly radial displacement. A hundred measurements at a bandwidth of 2300 Hz were performed. It was shown that the accuracy and precision in determination of the maximum displacement and the time of the maximum displacement from the calculated curve were satisfactory, in spite of the standard deviation of the twice-integrated acceleration growing approximately linearly with time. The results were accurate enough since the elapsed time from the beginning of the integration was small (less than 75 ms). The measured maximum displacement ranges were between 9.2 and 10.2 mm. The mean relative error was less than 1% (SD = 0.02mm) for the maximum displacement and about 1% (SD = 0.6 ms) for the time to maximum displacement. The accuracy of the half-relaxation time determination was more uncertain because of the relatively high relative error of -2.4% (SD = 3 ms). Results showed that a commercial micromachined accelerometer could be suitable for the measurement of muscle belly radial displacement and used for development of a future miniaturised and flexible system for the measurement of similar displacements.