REEV SENSE IMUs for Gait Analysis in Stroke: A Clinical Study on Lower Limb Kinematics

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.

Authors

Institutions

Publication Details

Journal
Sensors
Published
2025-08-18
DOI
https://doi.org/10.3390/s25165123
Citations
1
Primary Topic
Cerebral Palsy and Movement Disorders
Type
article
Field-Weighted Citation Impact
1.47

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

REEV SENSE IMUs for Gait Analysis in Stroke: A Clinical Study on Lower Limb Kinematics

Thibault Marsan, Ingy Elsayed-Aly, Catherine Ricciardi, Tatiana Urman et al.
1 citations
Sensors
Cerebral Palsy and Movement Disorders
1.47
article

REEV SENSE IMUs for Gait Analysis in Stroke: A Clinical Study on Lower Limb Kinematics

Thibault Marsan, Ingy Elsayed-Aly, Catherine Ricciardi, Tatiana Urman, Xiang Zhang, Sacha Clauzade, Nicolas Grandin, Evan Linton, Robin Temporelli
article en
1 citations

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.

SensorsVol. 25(16)
Systématique, adaptation, évolution (FR), Massachusetts Institute of Technology (US)
National Center for Advancing Translational Sciences
Openalex Percentile: Top 16%
Cerebral Palsy and Movement Disorders
1.47
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

REEV SENSE IMUs for Gait Analysis in Stroke: A Clinical Study on Lower Limb Kinematics — Thibault Marsan, Ingy Elsayed-Aly, et al. · Sensors (2025) | TGRS Research Map | TGRS