The need to assess muscle activation and intention recognition in the design of prosthetic or exoskeleton robots has recently increased in rehabilitation medical research. Assessment of the muscle activation has an important role in the control of wearable devices. Such application requires estimating a patient's intention through the detection of their muscle activation. Previously developed techniques, namely, bioelectrical impedance analysis, electrical impedance myography, electrical impedance tomography, and a surface electromyogram, have been used in the detection of muscle activation. However, these techniques tend to have difficulty in assessing the muscle activation. A biopsy needle can be used to sense the muscle activation in an invasive manner. We propose a new method for detecting the muscle activation using multi-electrode sensing with electrical stimulation, but without a biopsy needle. Electrical stimulation is applied to the skin of a subjects forearm. The signals reflected from their muscles are then measured using multiple electrodes placed on the skin. The forearm skin and its muscles can be modeled as muscle tissue circuits depending on the signal frequency. We verified the proposed method experimentally through isometric muscle contraction, isotonic muscle action, and a frequency response test using various frequencies of the electric stimulation signals. Experiments with eight healthy subjects showed promising results in the detection of muscle activation, which can be applied to prosthetic or exoskeleton robots.
All Science Journal Classification (ASJC) codes
- Electronic, Optical and Magnetic Materials
- Condensed Matter Physics
- Surfaces, Coatings and Films
- Metals and Alloys
- Electrical and Electronic Engineering