Actuation Timing Perception of a Powered Ankle Exoskeleton and Its Associated Ankle Angle Changes During Walking
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2022/03/25
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Description:Robotic ankle exoskeletons have the potential to extend human ability, and actuation timing serves as one of the critical parameters in its controller design. While many experiments have investigated the optimal actuation timing values to achieve different objective functions (e.g. minimizing metabolic cost), studies on users' perception of control parameters are gaining interest as it gives information on people's comfort, coordination, and trust in using devices, as well as providing foundations on how the sensorimotor system detects the exoskeleton behavior changes. The purpose of this study was to evaluate people's sensitivity to changes in exoskeleton actuation timing and its associated exoskeleton ankle angle changes during walking. Participants (n =15) with little or no prior experience with ankle exoskeletons were recruited and performed a psychophysical experiment to characterize their just-noticeable difference (JND) thresholds for actuation timing. Participants wore a bilateral active ankle exoskeleton and compared pairs of torque profiles with different actuation timings and low peak torque (0.225 Nm/kg) while walking on the treadmill. The mean timing JND across participants was 2.8 +/- 0.6% stride period. Individuals exhibited different sensitivity towards actuation timing, and their associated exoskeleton ankle angle changes also varied. The variance in ankle angle changes might be explained by their differences in ankle stiffness and different ankle torques provided during walking. The results provide insights into how people perceive the changes in exoskeleton control parameters and show individual differences in exoskeleton usage. The actuation timing JND found in this study can also help determine the necessary controller precision. [Description provided by NIOSH]
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ISSN:1534-4320
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Volume:30
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NIOSHTIC Number:nn:20067032
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Citation:IEEE Trans Neural Syst Rehabil Eng 2022 Mar; 30:869-877
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Contact Point Address:Xiangyu Peng, Robotics Institute, University of Michigan, Ann Arbor, MI 48109 USA
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Email:xypeng@umich.edu
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Federal Fiscal Year:2022
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Performing Organization:University of Alabama at Birmingham
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Peer Reviewed:True
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Start Date:20050701
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Source Full Name:IEEE Transactions on Neural Systems and Rehabilitation Engineering
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End Date:20270630
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Main Document Checksum:urn:sha-512:f8081c451ce8ae59eb474ef8d44eac68cc8b1a66a8075c800f5e5afbbb859de25a3b6577cff8ba2c4d57b70472cf53984ddba885fc0546ac060947b49374e06d
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