An Easily Implemented Wearable Remote Data Capture Solution for Home-Based Gait Assessment in Multiple Sclerosis
Abstract
One of the most disruptive problems from multiple sclerosis (MS) is the impairment in a person s ability to walk. Changes in walking ability can restrict independence and result in a reduction in quality of life, which often leads to workplace disability. However, despite the importance of walking ability, most people with MS have very brief and limited options for a walking test, and these tests are only provided during outpatient visits with an MS provider. Newly available technology offers a significantly improved option for tests of walking in MS. Using wearable motion sensors, walking can be tested in a much more accurate and reliable manner than the current clinical tests (e.g., the use a handheld stopwatch to measure walking time or distance). These devices with computer-analyzed measures allow us to precisely capture walking speed as well as other important information like step length. This walking analysis can provide better insight into factors responsible for how walking is affected, and allow us to target rehabilitation more specifically to the problem. Further, higher sensitivity of this device allows changes in walking ability that can be detected much earlier to identify when rehabilitation is needed to prevent further decline. Another major advantage of this technology is that walking can be measured at home, and at any time. With this remote system, these wearable sensors can be easily placed on a shoe and capture walking measures in real-time. This allows for more frequent monitoring of walking abilities, and the earliest possible detection of change in walking. Studies have shown that this technology can be easily used at home by people living with MS, however, no study yet has used this technology to measure and monitor walking from home. Therefore, I propose to validate an MS Gait Remote Capture and Analysis (MS-GRCA) system based on wearable motion sensors for home-based and repeatable assessment of walking ability for people with MS. Importantly, this solution incorporates a commercially available, user-friendly technology that would be, once validated, available for immediate use by people with MS and their MS care providers. My objective is to carefully validate MS-GRCA system for home-based and self-administered use for people with MS. I will recruit n=30 people with MS to complete a three-step validation study. Using the MS-GRCA system, participants will complete the following gait assessments: (1) at clinic along with standard clinical measures (Baseline Capture), (2) repeated assessment at home by the participant and guided through a live video telehealth visit (Remote Capture 1), and then (3) self-administered by the participant at home (Remote Capture 2 and 3). The MS-GRCA system includes a study iPad and two wearable shoe-based motion sensors (Runscribe, Scribelabs, CA). The study iPad will be used for enabling the video visits through the secure NYU Virtual Health app and for recording the gait accelerations from the wearable shoe-based motion sensors during the remote walking assessments through the app RunScribe. The short-term goal of this study is to establish and demonstrate feasibility and validity of the proposed remote capture system against a gold standard clinical assessment, showing also its usability by the end-users (people living with MS). The immediate impact for people living with MS will be the opportunity to have access to an easy-to-use instrument, and the data from this study will deepen our understanding of motor disability associated with MS. The results will further improve our understanding of treatment response and to monitor fluctuations in their motor symptoms under the supervision of expert clinician. The long-term goal will be building live platforms to enable true remote continuous monitoring in real-time providing a comprehensive map of the patients with MS mobility functions and their changes over the time. In conclusion, th
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Dec 28, 2022
- Source ID
- W81XWH2210812
Entities
People
- Giuseppina Pilloni
Organizations
- Grossman School of Medicine
- United States Army