Multiple Sclerosis (MS) is a chronic disease affecting the central nervous system, in which individuals' immune systems attack the protective covering of nerve fibers (called myelin) that supports the conduction of nerve signals. When myelin is attacked and damaged, this can cause communication problems from the brain to other parts of the body. The cause of MS is unknown and there is no cure, and current treatments focus on helping symptom management and recovery from attacks.
Symptoms of MS can vary from person to person depending on the nerves affected, but a common symptom experienced by people with MS is unsteady gait and lack of coordination. Gait deficits are highly prevalent in MS and often get worse over time, and it’s estimated that 50-80% of people with MS experience balance problems1. Regular walking assessments can help track disease progression and severity, inform the impact MS has on quality of life, and assess the effectiveness of new treatments and rehabilitation therapies.
Walking performance scales and tests widely used in research and clinical care measure deviations from normal gait patterns and how they change over time, but they do not provide information on the underlying gait pattern. Gait pattern information is important because rehabilitation therapies focus on adjusting these types of specific impairments to gait.
Computerized motion analysis systems can provide this level of detail on gait pattern; however, these systems can be expensive and require adequate space and expertise to operate. Moreover, these systems are confined to laboratory space and not suitable for real-world applications. Therefore, a gap exists in clinical research for an affordable, widely accessible tool that can provide reliable and accurate measures of underlying gait patterns in patients with MS.
ActiGraph launched the Digital Endpoint Accelerator Research “DEAR” Grant to help address these evidence gaps by partnering with clinical researchers on projects that examine the validity of digital measures derived from wearable digital health technology as compared to established ground truth measures. One of the researchers receiving this grant is Alon Kalron, PhD, PT, Associate Professor and Chair of the Department of Physical Therapy at Faculty of Medicine and Health Sciences, Tel-Aviv University.
Prof. Kalron’s main area of research focus has been physical activity, cognition, gait, and balance in the neurological population, particularly people with multiple sclerosis (MS). With the DEAR Grant, Prof. Kalron and his research team will validate spatiotemporal gait output data from the ActiGraph GT9X worn by people with MS by comparing this data to GaitRite, a gold standard for gait analyses. The team will use a test-retest design to further examine the reliability of the digital gait measures. They will also look at the relationship between digital gait measures and the level of disability, fear and history of falling, and perceived impact of MS on mobility.
“The ActiGraph devices offer a unique opportunity to measure various mobility metrics beyond physical activity. The simplicity of usage makes it a very attractive option for clinical research and practice. However, first the psychometric properties of the measurement tool should be clarified,” commented Prof. Kalron.
This research project is one of five that have been selected to receive the DEAR Grant, all of which will progress over the course of 2023. Evidence generated from these studies will accelerate the adoption of wearable data as patient-centered outcomes, which will ultimately improve clinical trial efficiency.
To learn more about digital measures of gait collected from wearable digital health technologies, watch the on-demand webinar, “Advancing ALS Research with DHTs: Where Are We Now?”
References
- Michelle H. Cameron, Ylva Nilsagard. Chapter 15 - Balance, gait, and falls in multiple sclerosis. Editor(s): Brian L. Day, Stephen R. Lord. Handbook of Clinical Neurology, Elsevier,
Volume 159, 2018, Pages 237-250, https://doi.org/10.1016/B978-0-444-63916-5.00015-X.
