title: Locomotion mode classification using a wearable capacitive sensing system.
abstract: Locomotion mode classification is one of the most important aspects for the control of powered lower-limb prostheses. We propose a wearable capacitive sensing system for recognizing locomotion modes as an alternative solution to popular electromyography (EMG)-based systems, aiming to overcome drawbacks of the latter. Eight able-bodied subjects and five transtibial amputees were recruited for automatic classification of six common locomotion modes. The system measured ten channels of capacitance signals from the shank, the thigh, or both. With a phase-dependent linear discriminant analysis classifier and selected time-domain features, the system can achieve a satisfactory classification accuracy of 93.6% ±0.9% and 93.4% ±0.8% for able-bodied subjects and amputee subjects, respectively. The classification accuracy is comparable with that of EMG-based systems. More importantly, we verify that neuro-mechanical delay inherent in capacitive sensing does not affect the timeliness of classification decisions as the system, similar to EMG-based systems, can make multiple judgments during a gait cycle. Experimental results also indicate that capacitance signals from the thigh alone are sufficient for mode classification for both able-bodied and transtibial subjects. Our investigations demonstrate that capacitive sensing is a promising alternative to myoelectric sensing for real-time control of powered lower-limb prostheses.
authors.forename: Baojun
authors.initials: B
authors.lastname: Chen
authors.forename: Enhao
authors.initials: E
authors.lastname: Zheng
authors.forename: Xiaodan
authors.initials: X
authors.lastname: Fan
authors.forename: Tong
authors.initials: T
authors.lastname: Liang
authors.forename: Qining
authors.initials: Q
authors.lastname: Wang
authors.forename: Kunlin
authors.initials: K
authors.lastname: Wei
authors.forename: Long
authors.initials: L
authors.lastname: Wang
mesh_terms: D000328:Adult; D000671:Amputation, Surgical / Q000534:rehabilitation*; D000673:Amputation, Traumatic / Q000534:rehabilitation*; D001186:Artificial Limbs; D001696:Biomechanical Phenomena / Q000502:physiology; D016002:Discriminant Analysis; D025802:Electric Capacitance; D004566:Electrodes; D004576:Electromyography / Q000145:classification* / Q000295:instrumentation / Q000379:methods; D005260:Female; D007839:Functional Laterality / Q000502:physiology; D006801:Humans; D008124:Locomotion / Q000502:physiology*; D035002:Lower Extremity / Q000294:innervation / Q000502:physiology*; D008297:Male; D011474:Prosthesis Design / Q000145:classification* / Q000379:methods; D011597:Psychomotor Performance / Q000502:physiology; D013546:Sweating / Q000502:physiology; D016138:Walking / Q000502:physiology; D055815:Young Adult