Analysis of force myography based locomotion patterns

• Published in: Measurement : journal of the International Measurement Confederation 2019-07, Vol.140, p.497-503
• Main Authors: Godiyal, Anoop Kant, Singh, Upinderpal, Anand, Sneh, Joshi, Deepak
• Format: Article
• Language: English
• Subjects: Ascent; Classification; Correlation coefficients; Descent; Electromyography; Feasibility studies; Force myography; Gait; Locomotion; Locomotion identification; Medical technology; Prostheses; Rehabilitation; Resistors; Sensor array; Switches; Walking; Wearable computers; Wearable system
• ISSN: 0263-2241; 1873-412X
• DOI: 10.1016/j.measurement.2019.04.009

•The variation of FMG pattern across various locomotion modes is presented.•Consistency of FMG signals within locomotion mode is shown.•FMG-based locomotion characterization is presented.•An application to lower limb prosthesis control is discussed. Investigation of locomotion patterns provides a useful scenario for many applications like locomotion classification in the prosthesis, gait rehabilitation, and pathological gait analysis. Locomotion classification for prosthesis use has been of great importance for the development of intelligent prosthesis. Electromyography (EMG) has shown promising results in the past as a sensing modality to represent the locomotion patterns in different terrain. However, EMG suffers from various limitations to be widely accepted. A force myography (FMG) system has been developed to analyze its feasibility as an alternate sensing modality to EMG. Data from eight force sensitive resistors (FSR) along with foot switches were collected from six healthy subjects for five different locomotion modes i.e. level walk (LW), ramp ascent (RA), ramp descent (RD), stair ascent (SA) and stair descent (SD). To estimate the characteristics of FMG, the variance ratio and correlation coefficient were calculated for intra and inter-class locomotion respectively. A lower variance ratio in anterior FMG in all locomotion modes was observed, indicating the high repeatability of FMG signal. Further, the lower correlation coefficient between level walking (LW) and other locomotion modes SA & SD, promises FMG to be a potential information source for future application in locomotion classification. Results of the present study demonstrate the prospective of FMG in the representation of different locomotion and its possible application in lower limb prosthetic control.