Cardio Robot
Rehabilitation technology has the potential to implement effective rehabilitation strategies to improve exercise capacity and facilitate motor recovery after stroke.
Factsheet
- Lead school School of Engineering and Computer Science
- Institute(s) Institute for Human Centered Engineering (HUCE)
- Funding organisation BFH
- Duration 01.01.2013 - 31.12.2014
- Project management Prof. Dr. Kenneth James Hunt
- Head of project Prof. Dr. Kenneth James Hunt
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Project staff
Lukas Michael Bichsel
Prof. Dr. Kenneth James Hunt
Corina Schuster-Amft
Prof. Dr. Lorenz Radlinger
Matthias Schindelholz
Prof. Dr. Heiner Baur
Oliver Stoller - Partner Reha Rheinfelden
- Keywords Robotics, Stroke, Cardiovascular Exercise, Treadmill Training, Clinical Routine
Situation
The aim of this project was to develop and evaluate novel rehabilitation robotics technologies and protocols for cardiopulmonary assessment and training after stroke.Feedback-controlled robotics-assisted treadmill technology was proposed to
Course of action
Feedback-controlled robotics-assisted treadmill technology was proposed to overcome motor limitations and facilitate task-specific training during stroke rehabilitation. Within a clinical trial, this project evaluated efficacy and feasibility of our novel concept for assessment of cardiovascular fitness and improvement of exercise capacity. Furthermore, a fast and easy-to-perform assessment for weight-bearing capacity on a single force platform was developed and evaluated.
Result
Feedback-controlled robotics-assisted treadmill exercise-based cardiopulmonary exercise testing demonstrated clinical feasibility, good to excellent test-retest reliability, and acceptable repeatability. The method provoked a substantial increase in exercise intensity and led to a significant improvement in cardiovascular fitness. Three dynamic repetitions of loading the hemiparetic leg are sufficient to assess weight-bearing capacity in non-ambulatory stroke survivors.
Looking ahead
The findings are an important step towards effective rehabilitation strategies early after stroke. Future research will focus on further development of appropriate algorithms within advanced robotic systems.
