Sakr, Maram Gamal Ismail Elmetwally - Feasibility of using force myography (FMG) for estimating hand force and wrist torque...

This thesis has been approved for inclusion in the SFU Library.
Publication of this thesis has been postponed at the author's request until 2019-01-03.
Spring 2018
Degree type: 
School of Engineering Science
Applied Sciences
Senior supervisor: 
Carlo Menon
Publishing Documentation
Postponement release date: 
Thu, 2019-01-03
Thesis title: 
Feasibility of using force myography (FMG) for estimating hand force and wrist torque
Given Names: 
Maram Gamal Ismail Elmetwally
Hand force estimation is critical for applications that involve physical human-machine interactions for force monitoring and machine control. Force Myography (FMG) is a potential technique to be used for estimating hand force/torque. The FMG signals represent the volumetric changes in the arm muscles due to muscle contraction or expansion during force/torque exertion. The aim of this thesis is to explore the suitability of FMG for hand force/torque estimation. Studying the feasibility of using FMG for torque estimation was preliminary investigated by using 1-DOF torque sensor for labeling the FMG during torque exertion. A custom designed force-sensing resistors (FSRs) band was donned on the forearm for measuring FMG signals, while the participants exerted torque around three axes. A regression model was created for each torque axis. The average R2 was 0.89 for pronation-supination, flexion-extension, and radial-ulnar deviations. Using 1-DOF torque sensor for labeling the data needs a new custom-rig for capturing each torque axis. To overcome this limitation, a 6-DOF force/torque load cell was used for labeling the FMG data during force/torque exertion in any direction. In addition, 60 FSRs were embedded into four bands to be worn on the arm for measuring FMG signals during force/torque exertion. Healthy participants were recruited in this study and were asked to exert isometric force along three perpendicular axes, torque about the same three axes, and force and torque freely in any direction. Three cases were considered to explore the performance of the FMG bands in estimating force/torque in single- and multi- axis. These cases are: (1) 6 axes force/torque individually; (2) 3-DOF force and 3-DOF torque; and (3) 6-DOF force and torque simultaneously. In addition, a comparison between all possible combinations of the four bands was held to provide guidelines about the best placement of the FMG measurements in each case. The results show a promising potential of FMG to estimate isometric force/torque. Specifically, the average R2 accuracies using the four bands on the arm are 0.97 when the 6 force/torque axes were considered individually; 0.98 and 0.96 for the 3-DOF force and torque, respectively; and 0.95 for 6-DOF force/torque estimation.
Hand Force/Torque Estimation; Human-machine Interface; Force Myography; Wearable Sensors
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