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Open AccessArticle

An Evaluation of Three Kinematic Methods for Gait Event Detection Compared to the Kinetic-Based ‘Gold Standard’

1
Biomechanics and Movement Science Program, University of Delaware, Newark, DE 19713, USA
2
Department of Physical Therapy, University of Delaware, Newark, DE 19713, USA
3
Biostatistics Core Facility, College of Health Sciences, University of Delaware, Newark, DE 19713, USA
4
Shriners Hospitals for Children, Philadelphia, PA 19140, USA
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(18), 5272; https://doi.org/10.3390/s20185272
Received: 15 August 2020 / Revised: 5 September 2020 / Accepted: 12 September 2020 / Published: 15 September 2020
(This article belongs to the Special Issue Sensor-Based Systems for Kinematics and Kinetics)
Video- and sensor-based gait analysis systems are rapidly emerging for use in ‘real world’ scenarios outside of typical instrumented motion analysis laboratories. Unlike laboratory systems, such systems do not use kinetic data from force plates, rather, gait events such as initial contact (IC) and terminal contact (TC) are estimated from video and sensor signals. There are, however, detection errors inherent in kinematic gait event detection methods (GEDM) and comparative study between classic laboratory and video/sensor-based systems is warranted. For this study, three kinematic methods: coordinate based treadmill algorithm (CBTA), shank angular velocity (SK), and foot velocity algorithm (FVA) were compared to ‘gold standard’ force plate methods (GS) for determining IC and TC in adults (n = 6), typically developing children (n = 5) and children with cerebral palsy (n = 6). The root mean square error (RMSE) values for CBTA, SK, and FVA were 27.22, 47.33, and 78.41 ms, respectively. On average, GED was detected earlier in CBTA and SK (CBTA: −9.54 ± 0.66 ms, SK: −33.41 ± 0.86 ms) and delayed in FVA (21.00 ± 1.96 ms). The statistical model demonstrated insensitivity to variations in group, side, and individuals. Out of three kinematic GEDMs, SK GEDM can best be used for sensor-based gait event detection. View Full-Text
Keywords: gait event detection; wearable sensors; gait analysis gait event detection; wearable sensors; gait analysis
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MDPI and ACS Style

Zahradka, N.; Verma, K.; Behboodi, A.; Bodt, B.; Wright, H.; Lee, S.C.K. An Evaluation of Three Kinematic Methods for Gait Event Detection Compared to the Kinetic-Based ‘Gold Standard’. Sensors 2020, 20, 5272. https://doi.org/10.3390/s20185272

AMA Style

Zahradka N, Verma K, Behboodi A, Bodt B, Wright H, Lee SCK. An Evaluation of Three Kinematic Methods for Gait Event Detection Compared to the Kinetic-Based ‘Gold Standard’. Sensors. 2020; 20(18):5272. https://doi.org/10.3390/s20185272

Chicago/Turabian Style

Zahradka, Nicole; Verma, Khushboo; Behboodi, Ahad; Bodt, Barry; Wright, Henry; Lee, Samuel C.K. 2020. "An Evaluation of Three Kinematic Methods for Gait Event Detection Compared to the Kinetic-Based ‘Gold Standard’" Sensors 20, no. 18: 5272. https://doi.org/10.3390/s20185272

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