Intensity control of robot-assisted gait training based on biometric data: Preliminary study
Kim Jiae1, Min Ho Chun1, Junekyung Lee2
1Department of Rehabilitation Medicine, Asan Medical Center, University of Ulsan College of Medicine, Republic of Korea.
Medicine
|October 5, 2022
Summary
Robot-assisted gait training intensity adjusted by patient biometrics showed no significant difference in outcomes compared to therapist judgment. This finding suggests flexibility in controlling robotic rehabilitation intensity for stroke patients.
Area of Science:
- Rehabilitation Medicine
- Robotics in Healthcare
- Neurological Rehabilitation
Background:
- Robot-assisted gait training (RAGT) is a promising intervention for stroke recovery.
- Optimizing training intensity is crucial for maximizing therapeutic effects.
- Current RAGT intensity control often relies on therapist's subjective assessment.
Purpose of the Study:
- To compare the efficacy of RAGT intensity controlled by patient biometric data (heart rate, RPE) versus therapist's subjective judgment.
- To evaluate functional ambulation category (FAC) and secondary outcomes.
Main Methods:
- A non-blinded, prospective, randomized controlled study involving 55 stroke patients.
- Two groups: biometric data control (HR/RPE) and therapist control.
- 3-week RAGT (Morning Walk®), 5 sessions/week, 20 minutes/session.
- Outcomes assessed at baseline and post-intervention.
Main Results:
- Significant improvements in FAC, MBI, BBS, TUG, and 10MWT were observed in both groups post-intervention (P < .05).
- No statistically significant differences were found between the biometric and therapist control groups for primary (FAC) or secondary outcomes.
- This indicates comparable treatment effects regardless of the intensity control method.
Conclusions:
- Adjusting RAGT intensity using patient's heart rate or rating of perceived exertion (RPE) yields similar functional outcomes to therapist-guided adjustments.
- Biometric data offers an objective method for intensity control in RAGT.
- These findings support the use of patient-centered intensity modulation in robotic gait training for stroke survivors.
