title: A noncontact capacitive sensing system for recognizing locomotion modes of transtibial amputees.
abstract: This paper presents a noncontact capacitive sensing system (C-Sens) for locomotion mode recognition of transtibial amputees. C-Sens detects changes in physical distance between the residual limb and the prosthesis. The sensing front ends are built into the prosthetic socket without contacting the skin. This novel signal source improves the usability of locomotion mode recognition systems based on electromyography (EMG) signals and systems based on capacitance signals obtained from skin contact. To evaluate the performance of C-Sens, we carried out experiments among six transtibial amputees with varying levels of amputation when they engaged in six common locomotive activities. The capacitance signals were consistent and stereotypical for different locomotion modes. Importantly, we were able to obtain sufficiently informative signals even for amputees with severe muscle atrophy (i.e., amputees lacking of quality EMG from shank muscles for mode classification). With phase-dependent quadratic classifier and selected feature set, the proposed system was capable of making continuous judgments about locomotion modes with an average accuracy of 96.3% and 94.8% for swing phase and stance phase, respectively (Experiment 1). Furthermore, the system was able to achieve satisfactory recognition performance after the subjects redonned the socket (Experiment 2). We also validated that C-Sens was robust to load bearing changes when amputees carried 5-kg weights during activities (Experiment 3). These results suggest that noncontact capacitive sensing is capable of circumventing practical problems of EMG systems without sacrificing performance and it is, thus, promising for automatic recognition of human motion intent for controlling powered prostheses.
authors.forename: Enhao
authors.initials: E
authors.lastname: Zheng
authors.forename: Long
authors.initials: L
authors.lastname: Wang
authors.forename: Kunlin
authors.initials: K
authors.lastname: Wei
authors.forename: Qining
authors.initials: Q
authors.lastname: Wang
mesh_terms: D000672:Amputation Stumps / Q000503:physiopathology*; D000674:Amputees / Q000534:rehabilitation*; D001186:Artificial Limbs; D025802:Electric Capacitance; D004867:Equipment Design; D019544:Equipment Failure Analysis; D005684:Gait; D006801:Humans; D018670:Monitoring, Ambulatory / Q000295:instrumentation*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013977:Tibia / Q000503:physiopathology* / Q000601:surgery