Prediction of change in ALS disease state by tracking movement with wearable sensors

ALS progression is typically self-reported and evaluated only during clinic visits, which can occur months apart. This approach offers only a single snapshot of the person’s performance and is susceptible to daily fluctuations in personal factors such as stress, sleep, diet, and fatigue, which can influence the outcome. As such, tools that can continuously evaluate motor function are needed.

Wearable sensors are becoming common practice in helping people track their personal health and there have been a number of studies in recent years that have begun to evaluate their applicability to ALS. These devices usually include an accelerometer and gyroscope which can monitor a person’s movement during normal daily activities), and can connect to a computer via Wi-Fi. Thus, by placing one of these sensors on an arm or leg, researchers can capture and relay difficulties with limb movement due to ALS.

With this award, Dr. Gordon Jewett will utilize his undergraduate background in biomedical software engineering to monitor limb movement in people living with ALS using a wearable sensor and utilize machine learning techniques to develop an algorithm that can predict functional decline. The study will also utilize the Canadian Neuromuscular Disease Registry (CNDR) as a means of recruitment and comparison of wearable data with standard clinical data. Collaboration with the Canadian ALS Neuroimaging Consortium (CALSNIC), which is also supported by the ALS Canada Research Program, will help to validate his findings and provide an additional layer to his work by determining if the changes observed in MRI brain scans correlate with functional changes measured by the sensors.

The ability to accurately measure the functional status of someone living with ALS from data collected through a wearable sensor could significantly benefit the design of clinical trials. This approach could be implemented as a precise, reproducible, convenient and cost-effective outcome measure in ALS clinical trials. It would also make participation more convenient with fewer clinic visits required.

Dr. Jewett will accompany this work with additional training as a neurologist at the University of Calgary ALS clinic. The unique expertise he brings to the field, combined with his clinical duties will be a very valuable addition to the Canadian clinical and clinical research landscape.