Real-time gait metric estimation for everyday gait training with wearable devices in people poststroke.

Autor:	Arens P; John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA.; Wyss Institute for Biologically Inspired Engineering, Harvard University, Cambridge, Massachusetts, USA., Siviy C; John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA.; Wyss Institute for Biologically Inspired Engineering, Harvard University, Cambridge, Massachusetts, USA., Bae J; John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA.; Wyss Institute for Biologically Inspired Engineering, Harvard University, Cambridge, Massachusetts, USA., Choe DK; John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA.; Wyss Institute for Biologically Inspired Engineering, Harvard University, Cambridge, Massachusetts, USA., Karavas N; John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA.; Wyss Institute for Biologically Inspired Engineering, Harvard University, Cambridge, Massachusetts, USA., Baker T; Department of Physical Therapy and Athletic Training, Boston University, Boston, Massachusetts, USA., Ellis TD; Department of Physical Therapy and Athletic Training, Boston University, Boston, Massachusetts, USA., Awad LN; John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA.; Wyss Institute for Biologically Inspired Engineering, Harvard University, Cambridge, Massachusetts, USA.; Department of Physical Therapy and Athletic Training, Boston University, Boston, Massachusetts, USA., Walsh CJ; John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA.; Wyss Institute for Biologically Inspired Engineering, Harvard University, Cambridge, Massachusetts, USA.
Jazyk:	angličtina
Zdroj:	Wearable technologies [Wearable Technol] 2021; Vol. 2. Date of Electronic Publication: 2021 Mar 25.
DOI:	10.1017/wtc.2020.11
Abstrakt:	Hemiparetic walking after stroke is typically slow, asymmetric, and inefficient, significantly impacting activities of daily living. Extensive research shows that functional, intensive, and task-specific gait training is instrumental for effective gait rehabilitation, characteristics that our group aims to encourage with soft robotic exosuits. However, standard clinical assessments may lack the precision and frequency to detect subtle changes in intervention efficacy during both conventional and exosuit-assisted gait training, potentially impeding targeted therapy regimes. In this paper, we use exosuit-integrated inertial sensors to reconstruct three clinically meaningful gait metrics related to circumduction, foot clearance, and stride length. Our method corrects sensor drift using instantaneous information from both sides of the body. This approach makes our method robust to irregular walking conditions poststroke as well as usable in real-time applications, such as real-time movement monitoring, exosuit assistance control, and biofeedback. We validate our algorithm in eight people poststroke in comparison to lab-based optical motion capture. Mean errors were below 0.2 cm (9.9%) for circumduction, -0.6 cm (-3.5%) for foot clearance, and 3.8 cm (3.6%) for stride length. A single-participant case study shows our technique's promise in daily-living environments by detecting exosuit-induced changes in gait while walking in a busy outdoor plaza. Competing Interests: Competing Interests. Patents describing the exosuit components documented in this article have been filed with the U.S. Patent Office. C.S., J.B, N.K., and C.J.W. are authors on one or more of those patents or patent applications. Harvard University has entered into a licensing and collaboration agreement with ReWalk Robotics. C.J.W. is a paid consultant for ReWalk Robotics. The other authors declare that they have no competing interests.
Databáze:	MEDLINE
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