Wearable Sensors May Identify MS Patients at Greater Risk of Falls

Those who fell walked slower and took smaller steps, study found

Lindsey Shapiro, PhD avatar

by Lindsey Shapiro, PhD |

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Using wearable sensors to monitor gait during daily life may be a promising way to identify people with multiple sclerosis (MS) who have a greater risk of falling, a study found.

The study identified a number of gait differences between those who fell in the year and those who didn’t, with a smaller pitch angle at toe-off – the angle of the foot when it’s being pushed off the ground – being the best predictor of a risk of fall.

“Our finding of the decreased foot pitch angle at toe-off as a most critical predictor of falls may assist in future fall prevention by developing optimal interventions for this impairment, as well as by identifying [people with MS] in need of treatment to avoid falls,” the researchers wrote.

The study, “Fall Prediction Based on Instrumented Measures of Gait and Turning in Daily Life in People with Multiple Sclerosis,” was published in Sensors.

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Impairments in balance and gait as a result of disease progression may leave patients at a high risk of falls. It’s estimated that more than half of MS patients have falls over the course of their disease and about one-third are considered “frequent fallers.”

Since falling represents an increased chance of injury and reduces a patient’s ability to participate in daily activities, monitoring for at-risk patients to provide appropriate interventions is important.

Also, most falls happen inside the home, so it’s especially important for patients to be monitored in their daily lives, and not just at short visits to the doctor’s office, the researchers noted.

“Passive monitoring of mobility during daily life could help better assess the risk of falling in [people with MS], allowing researchers and clinicians to gain insights about their patients both inside and outside of healthcare facilities,” they wrote.

Foot fall and falling

Researchers at the Oregon Health and Science University, in collaboration with APDM Wearable Technologies evaluated whether using wearable sensors to passively monitor gait and turning at home could help predict those at risk of future falls.

Their study included 26 MS patients with mild to moderate disability who had complaints about their mobility, but could still walk independently.

Passive monitoring was performed for up to one week with APDM’s Opal instrumented socks, a wearable device with sensors for assessing gait and balance. One sensor is placed on the waist while a pair of “socks” covering the feet and ankles also have sensors.

Daily life mobility data from the device were collected for an average of six days and a total duration of 52 hours per participant. After this monitoring period, participants were asked to report on new falls for one year, via twice weekly email surveys. Those who had more than one fall in that year of follow-up were considered fallers.

Overall, 13 patients were classified as fallers, while 13 were considered non-fallers. No differences were observed between the groups with regard to age, weight, height, disease duration, or disability level.

But fallers and non-fallers had differences in their gait and turning measurements. Specifically, fallers walked slower, took smaller steps, spent more time with both feet in contact with the ground during walking (double support period), and less time with a foot in the air (swing phase).

These patients also had significantly smaller turning angles during walking, “indicating that fallers may avoid or find it difficult to control large turns,” the researchers wrote.

Fallers also had a significantly smaller pitch angle of the foot at toe-off. A smaller angle means the muscles involved in the foot’s push-off from the ground don’t extend as much and the heel doesn’t come as far off the ground.

A ‘metabolic cost of walking’

In a final prediction model, the researchers found that a previous fall history was not a predictor of future falls. And, among the measures collected during passive monitoring, a smaller pitch angle at toe-off was the best predictor of future falls. Alone, this measure was able to distinguish future fallers from non-fallers with an 86% accuracy.

The smaller pitch angle might reflect weakness in the muscles — called plantar flexor muscles — needed to create the push-off from the ground. This could prevent the body from being propelled, prevent the feet from properly clearing the ground during the swing phase, and slow a person down, the research team suggested.

It could also come with an energetic cost, they added. The leg may bear a higher burden when not propelled enough, causing an increase in the “metabolic cost of walking.”

“Fall prevention programs aimed at improving strength and training of plantar flexor muscles … may prove beneficial in improving the dynamic stability and metabolic cost of walking in people with MS,” the researchers wrote, noting the small study sample was recognized as a limitation.

“However, the real-life mobility data collected from this study represent an important starting point to improve our knowledge on remote monitoring of gait in patients with MS,” they said, noting that the current findings should be considered pilot data for the design of a larger study.