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Vinti, M., Couillandre, A., Hausselle, J., Bayle, N., Primerano, A., Merlo, A., Hutin, E. and Gracies, J.M. (2013) Influence of Effort Intensity and Gastrocnemius Stretch on Co-Contraction and Torque Production in the Healthy and Paretic Ankle. Clinical Neurophysiology, 124, 528-535. https://doi.org/10.1016/j.clinph.2012.08.010

has been cited by the following article:

• TITLE: Longitudinal Evaluation of Hemiplegic Ankle Rehabilitation Efficacy by Wearable Inertial Sensor Systems with an Assortment of Machine Learning Algorithms

  AUTHORS: Robert LeMoyne, Timothy Mastroianni

  KEYWORDS: Smartphone, Gyroscope, Machine Learning, Hemiparesis, Rehabilitation, Ankle, Longitudinal Evaluation

  JOURNAL NAME: Journal of Biomedical Science and Engineering, Vol.16 No.9, September 30, 2023

  ABSTRACT: With the amalgamation of wearable systems equipped with inertial sensors, such as a gyroscope, and machine learning a therapy regimen can be objectively quantified, and then the initial phase and final phase of a one year therapy regimen can be distinguished through machine learning. In the context of rehabilitation of a hemiplegic ankle, a longitudinal therapy regimen incorporating stretching and then a series of repetitions for raising and lowering the foot of the hemiplegic ankle can be applied over the course of a year. Using a smartphone equipped with an application to function as a wearable and wireless gyroscope platform mounted to the dorsum of the foot by an armband, the initial phase and final phase of a one year longitudinally applied therapy regimen can be objectively quantified and recorded for subsequent machine learning. Considerable classification accuracy is attained to distinguish between the initial phase and final phase by a support vector machine for a one year longitudinally applied hemiplegic ankle therapy regimen based on the gyroscope signal data obtained by a smartphone functioning as a wearable and wireless inertial sensor system.