Exploring the Feasibility of Monitoring of Gait and Falls in the Homes of Persons with Multiple Sclerosis

Background:  Due to the progressive nature of the disease, persons with MS (pwMS) experience worsening symptoms and gait instability, which places this population at high risk for falls. Studies have shown that gait characteristics may be analyzed to assess fall risk in addition to being a diagnostic marker of progression. The use of a continuous monitoring system in the homes of pwMS may allow for targeted symptom management, fall prevention strategies, and early treatment for progression.

Objectives: To determine the feasibility and validity of gait monitoring and falls in the homes of pwMS.

Methods: A pilot study was conducted to determine the feasibility of monitoring gait using in-home gait parameters measured by mounted depth sensors and how well these measures correlated with in-laboratory measures of gait. The sensors were placed in the home and collected gait parameters on a daily basis for 6 months. Sensor gait parameters (average number of walks, stride time, stride length, velocity and a predicted timed up and go (TUG)) were calculated by averaging daily walks in their home for 7 consecutive days. In-laboratory measures collected at baseline were the TUG, Timed 25-foot Walk Test, and a 16-foot GAIT Rite electronic pathway. The GAIT Rite was used to calculate spatiotemporal parameters of gait.

Results: A total of 7 participants, with all types of MS, participated in the study. Participants varied in age from 41-67 years (M=50.7, SD=9.2) included 4 females and 3 males with the average (SD) time from disease onset of 12.24 years (SD=8.2) years.  Median (IQR) SR-EDSS score was 5 (M=4.5, SD=6) indicating a high level of disability. Barriers to in-home sensor data collection included installation problems, internet connectivity issues, and recruitment due to privacy concerns. Four participants had data collected for 50% or more of the days in the first 3 months. Sensor predicted-TUG was within 2.5 seconds of the clinic TUG for most subjects. The relationships between the sensor and clinic data will be examined at baseline and at month 3 to examine the validity of the sensor system in pwMS.

Conclusions: The use of a monitoring system in the homes of pwMS may allow for targeted symptom management, fall prevention strategies, and early treatment for progression.