Real-Time Gait Event Detection Based on Kinematic Data Coupled to a Biomechanical Model.
Real-time detection of multiple stance events, more specifically initial contact (IC), foot flat (FF), heel off (HO), and toe off (TO), could greatly benefit neurorobotic (NR) and neuroprosthetic (NP) control. Three real-time threshold-based algorithms have been developed, detecting the aforementioned events based on kinematic data in combination with a biomechanical model. Data from seven subjects walking at three speeds on an instrumented treadmill were used to validate the presented algorithms, accumulating to a total of 558 steps. The reference for the gait events was obtained using marker and force plate data. All algorithms had excellent precision and no false positives were observed. Timing delays of the presented algorithms were similar to current state-of-the-art algorithms for the detection of IC and TO, whereas smaller delays were achieved for the detection of FF. Our results indicate that, based on their high precision and low delays, these algorithms can be used for the control of an NR/NP, with the exception of the HO event. Kinematic data is used in most NR/NP control schemes and is thus available at no additional cost, resulting in a minimal computational burden. The presented methods can also be applied for screening pathological gait or gait analysis in general in/outside of the laboratory.
Division PMA, Department of Mechanical Engineering, Katholieke Universiteit Leuven, 3000 Leuven, Belgium. stefan.lambrecht@kuleuven.be.|Department of Biomedical Kinesiology, Katholieke Universiteit Leuven, 3000 Leuven, Belgium. stefan.lambrecht@kuleuven.be.
Stefan
S
Lambrecht
AI Laboratory, Vrije Universiteit Brussel, 1050 Ixelles, Belgium. anna.harutyunyan@vub.ac.be.
Anna
A
Harutyunyan
Division PMA, Department of Mechanical Engineering, Katholieke Universiteit Leuven, 3000 Leuven, Belgium. kevin.tanghe@kuleuven.be.
Kevin
K
Tanghe
Department of Biomedical Kinesiology, Katholieke Universiteit Leuven, 3000 Leuven, Belgium. Maarten.afschrift@kuleuven.be.
Maarten
M
Afschrift
Division PMA, Department of Mechanical Engineering, Katholieke Universiteit Leuven, 3000 Leuven, Belgium. joris.deschutter@kuleuven.be.
Joris
J
De Schutter
Department of Biomedical Kinesiology, Katholieke Universiteit Leuven, 3000 Leuven, Belgium. ilse.jonkers@kuleuven.be.
Ilse
I
Jonkers
D000465:Algorithms; D001696:Biomechanical Phenomena; D005528:Foot; D005684:Gait; D006801:Humans
adaptive thresholds; gait segmentation; kinematics; modeling; neuroprostheses; neurorobotics; real-time event detection