TY - JOUR
T1 - An evaluation of three kinematic methods for gait event detection compared to the kinetic-based ‘gold standard’
AU - Zahradka, Nicole
AU - Verma, Khushboo
AU - Behboodi, Ahad
AU - Bodt, Barry
AU - Wright, Henry
AU - Lee, Samuel C.K.
N1 - Funding Information:
Funding: This research was funded by Shriners Hospitals for Children, Philadelphia, grant #71011 and National Institute of Health, grant #P30 GM103333. APC funding is provided by the Graduate College and the Department of Physical Therapy, University of Delaware.
Publisher Copyright:
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2020/9/2
Y1 - 2020/9/2
N2 - 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.
AB - 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.
KW - Gait analysis
KW - Gait event detection
KW - Wearable sensors
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U2 - 10.3390/s20185272
DO - 10.3390/s20185272
M3 - Article
C2 - 32942645
AN - SCOPUS:85091192701
SN - 1424-8220
VL - 20
SP - 1
EP - 15
JO - Sensors (Switzerland)
JF - Sensors (Switzerland)
IS - 18
M1 - 5272
ER -