Influences of the biofeedback content on robotic post-stroke gait rehabilitation: electromyographic vs joint torque biofeedback

Journal of NeuroEngineering and Rehabilitation, 2019 · DOI: https://doi.org/10.1186/s12984-019-0558-0 · Published: June 25, 2019

Assistive Technology Neurorehabilitation

Simple Explanation

This study explores how different types of biofeedback affect the recovery process for stroke patients using robotic-assisted gait training. It compares electromyographic biofeedback (EMGb), which uses muscle activity data, to joint torque biofeedback (Rb), which uses robot-generated force data. The research investigates whether providing different biofeedback information during Lokomat training can improve patient performance and their experience with the rehabilitation process after a stroke. The study found that while both types of biofeedback improved gait and daily living activities, EMGb was more effective in reducing spasticity and improving muscle force, while Rb led to better adaptation to the robotic movements.

Study Duration

Not specified

Participants

12 sub-acute non ambulatory stroke patients

Evidence Level

Randomized cross-over pilot trial

Key Findings

1
EMGb was more effective in reducing spasticity and improving muscle force at the ankle, knee, and hip joints compared to Rb.
2
Rb induces more adaptation to robotic movements than EMGb.
3
Patients found Rb less demanding than EMGb, but their motivation was higher with EMGb.

Research Summary

This study compares two biofeedback methods, EMGb and Rb, during Lokomat gait training for sub-acute stroke patients. The aim was to determine how different biofeedback content impacts patient performance and experience. The results indicate that both methods improve gait and daily living activities, but EMGb is more effective at reducing spasticity and improving muscle force, while Rb leads to better adaptation to robotic movements. Patients also found Rb less demanding, but were more motivated by EMGb. The study concludes that biofeedback content has specific effects, with muscle-based information (EMGb) directly impacting muscle activity and joint torque data (Rb) improving patient compliance with robot movements.

Practical Implications

Personalized Rehabilitation

Tailoring biofeedback content to address specific patient needs and preferences could optimize rehabilitation outcomes.

Spasticity Management

EMGb may be a more effective approach for reducing spasticity and improving muscle strength in stroke patients undergoing robotic gait training.

Improved Robot-Patient Interaction

Understanding how different biofeedback methods influence patient adaptation to robotic movements can improve the design and implementation of robotic rehabilitation programs.

Influences of the biofeedback content on robotic post-stroke gait rehabilitation: electromyographic vs joint torque biofeedback

Simple Explanation

Key Findings

Research Summary

Practical Implications

Personalized Rehabilitation

Spasticity Management

Improved Robot-Patient Interaction

Study Limitations

Your Feedback

Was this summary helpful?

Influences of the biofeedback content on robotic post-stroke gait rehabilitation: electromyographic vs joint torque biofeedback

Simple Explanation

Key Findings

Research Summary

Practical Implications

Personalized Rehabilitation

Spasticity Management

Improved Robot-Patient Interaction

Study Limitations

Your Feedback

Was this summary helpful?