REEV SENSE IMUs for Gait Analysis in Stroke: A Clinical Study on Lower Limb Kinematics
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sensors-25-05123-v2.pdf
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Author(s)
Marsan, Thibault
Clauzade, Sacha
Zhang, Xiang
Grandin, Nicolas
Urman, Tatiana
Linton, Evan
Elsayed-Aly, Ingy
Ricciardi, Catherine E.
Temporelli, Robin
Date Issued
August 18, 2025
Journal
Sensors
Publisher
Multidisciplinary Digital Publishing Institute
Citation
Marsan, T.; Clauzade, S.; Zhang, X.; Grandin, N.; Urman, T.; Linton, E.; Elsayed-Aly, I.; Ricciardi, C.E.; Temporelli, R. REEV SENSE IMUs for Gait Analysis in Stroke: A Clinical Study on Lower Limb Kinematics. Sensors 2025, 25, 5123.
Version
Final published version
Abstract
Human gait analysis is essential for clinical evaluation and rehabilitation monitoring, particularly in post-stroke individuals, where joint kinematics provide valuable insights into motor recovery. While optical motion capture (OMC) is the gold standard, its high cost and restricted use in laboratory settings limit its accessibility. This study aimed to evaluate the accuracy of REEV SENSE, a novel magnetometer-free inertial measurement unit (IMU), in capturing knee and ankle joint angles during overground walking in post-stroke individuals using assistive devices. Twenty participants with chronic stroke walked along a 10-m walkway with their usual assistive device (cane or walker), while joint kinematics were simultaneously recorded using OMC and IMUs. Agreement between the systems was assessed using the mean absolute error, root mean square error, 95% confidence intervals, and Pearson’s correlation coefficient. Knee angles measured with the IMUs showed a strong correlation with the OMC (r > 0.9) and low errors (MAE < 5°), consistent with clinical acceptability. Ankle angle accuracy was lower for participants using walkers, while knee measurements remained stable regardless of the assistive device. These findings demonstrate that REEV SENSE IMUs provide clinically relevant kinematic data and support their use as a practical wearable tool for gait analysis in real-world or remote clinical settings.
MIT Department
Massachusetts Institute of Technology. Center for Clinical and Translational Research
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DOI of Published Version
https://doi.org/10.3390/s25165123
