Effect of feedback on foot strike angle and forward propulsion in people with stroke

Citation Author(s):
Carmen
Ensink
Submitted by:
Carmen Ensink
Last updated:
Fri, 01/03/2025 - 09:55
DOI:
10.21227/dn2j-5e57
Data Format:
License:
0
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Abstract 

Background

Effective retraining of foot elevation and forward propulsion is essential in stroke survivors’ gait rehabilitation. However, home-based training often lacks valuable feedback. eHealth solutions based on inertial measurement units (IMUs) could offer real-time feedback on fundamental gait characteristics. This study aimed to investigate the effect of providing real-time feedback through an eHealth solution on foot strike angle (FSA) and forward propulsion in people with stroke.

Methods

Twelve stroke survivors completed five walking trials on an instrumented treadmill: A) regular walking (1), B) feedback on FSA, C) feedback on propulsion, D) feedback on both FSA and propulsion, and E) regular walking (2). Visual feedback was presented through a green-to-red vertical slide bar on a screen in front of the participants. Linear mixed models evaluated the impact of feedback on FSA and propulsion, considering the sequence of feedback delivery, and potential learning or fatigue effects over the trials. Post-hoc pairwise comparisons were performed to assess the effect of different feedback types.

Results

Linear mixed models revealed a main effect on FSA and propulsion by feedback on FSA and propulsion, respectively. FSA significantly increased from 16.6⁰ in the initial regular walking trial to 24.0⁰ during FSA feedback and 23.6⁰ during combined FSA and propulsion feedback trials (p<0.001). Forward propulsion significantly improved by one third in the feedback on propulsion and combined feedback on both FSA and propulsion conditions compared to the first regular walking trial (p<0.001).

Conclusions

The positive effect of real-time feedback on FSA and forward propulsion highlight the potential of eHealth solutions in tailoring rehabilitation strategies in stroke survivors.

Instructions: 

# Movin(g)Reality

Code and data used for the Moving Reality project (internal study ID: 1019).

 

FULL ARTICLE OF THE VALIDATION STUDY: Ensink, C.J.; Hofstad, C.; Theunissen, T.; Keijsers, N.L.W. Assessment of Foot Strike Angle and Forward Propulsion with Wearable Sensors in People with Stroke. Sensors 2024, 24, 710. https://doi.org/10.3390/s24020710 

 

 

Run the **1019_MovingReality_validation.py** code to analyze the data used in this study.

- The file **MovingReality_functions.py** contains the functions the main script requires to run the validation.

- The folder **data** contains the data used in this study.

 

Explanation of the code is commented through the scripts.

Explanation of the data is provided in the ReadMe file

 

** FULL ARTICLE OF THE EFFECT OF FEEDBACK IS UNDER SUBMISSION **

Run the **1019_MovingReality_effect_feedback.py** code to analyze the data used in this study.

- The file **MovingReality_functions.py** contains the functions the main script requires to run the validation.

- The folder **data** contains the data used in this study.

 

Explanation of the code is commented through the scripts.

Explanation of the data is provided in the ReadMe file.

Documentation

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