Exercise programs, including cycling, are known to be an effective non-invasive treatment for a multitude of cardiovascular and musculoskeletal rehabilitation programs. About 19% of the Canadian population with lower limb injuries could benefit from rehabilitation programs. Accordingly, cycling devices form a major part of this market, presenting a huge opportunity for innovative devices that can help end users in monitoring and analyzing critical information related to their rehabilitation program. The cycle ergometer introduced in this proposal is designed to develop, validate, and test a new technology platform as a unique solution for custom-designed rehabilitation interventions, and real-time patient performance data collection and interpretation.
The Solution
At iHADLab we developed a cycling ergometer that provides adaptive training programs. This technology could be a solution to designing personalized training and rehabilitation programs for lower limb injuries. The proposed cycling device is instrumented with several biomedical sensors, enabling its use in telerehabilitation programs. The biomechanics of the training exercise, including pedal forces, moment, saddle force, handlebar forces/moments, and more, are collected and analyzed in real-time.
Outcomes
The outcome of the project are developing: (i) a motorized stationary cycle ergometer equipped with different biosensors for comprehensive data acquisition and analysis. (ii) a framework to unify data collection through a single interface to a Cloud-based AI-engine, where advanced computational algorithms are used to analyze, classify, and interpret the data. (iii) a website and mobile application to connect the patient to clinicians remotely.
The clinical outcomes : the physiological and biomechanical results obtained from the healthy participants will provide a robust data bank for researchers and clinicians who aim to compare their clients’ results with a well-established data set from a large sample size of the same status. From the industry perspective, the development of APAD and the integration of different biosensors applied to this cycle ergometer as well as its cloud platform for sharing data, are novel and unique achievements in the rehabilitation cycle ergometer industry. These novel technologies in relation to the design and manufacturing of APAD will propel the knowledge of rehabilitation ergometers forward and ultimately will reduce the costs associated with travelling to visit the clinic incurred by patients and the Canada Health system.