Quantifying The Signal-To-Noise Ratio of Silicon- Embedded Sensors for Mechanomyography
Abstract
Experiments consisted of systematic measurements of the signal-to-noise ratio (SNR) of signals acquired from a mechanical stimulator, using silicon-embedded accelerometers. The objective of using the latter was to determine the combination of embedding properties which provide the highest SNR for mechanomyography (MMG) signal recording. Variations in silicon hardness and geometry were tested. Two important conclusions can be derived from the experiments: (1) It is possible to acquire MMG signals using silicon-embedded sensors; and (2) The embedded sensor's performance is affected by changes in the geometry of the embedding. The intended application of this study is the use of soft silicon suction sockets with embedded sensors as a more comfortable and functional alternative to current hard-socket powered prostheses for below-elbow amputees currently using electromyography as the control signal(s).