Ishu Arpan, PhD, senior research associate at Oregon Health & Science University, also discussed further studies she would like to see conducted in MS falls.
Data from a recent study suggest that a quick and simple postural sway test may be an important tool in identifying patients with mild to moderate multiple sclerosis (MS) at risk of falling. The study was presented virtually at the Americas Committee for Treatment and Research in Multiple Sclerosis (ACTRIMS) Forum 2021, February 25-27.1
Senior author Ishu Arpan, PT, PhD, senior research associate, neurology department, Oregon Health & Science University, and colleagues conducted postural sway tests in which the participants stood on a firm surface for 30 seconds with open eyes while wearing a wireless inertial sensor (Opan by APDM Wearable Technologies) on the lumbar spine. They found that sway measures that differentiate people with MS from healthy controls (HC) could also be used to differentiate fallers from non-fallers in people with MS.
Arpan and colleagues found that increased jerk, range, and the root mean square of sway were especially sensitive to MS and used these measures to successfully differentiate fallers from non-fallers in the MS group. The sway measures were significantly higher in people with MS that reported falls in the last 6 months compared to those who did not.
NeurologyLive reached out to Arpan to learn more about how identifying people with MS at risk for falling can be important to patient care. She also discussed further studies she would like to see conducted.
Ishu Arpan, PhD: Early detection of those at risk for falls is critical for preventing falls. Currently, in the clinical settings, fall risk is investigated using simple walking tests, which may not be sensitive enough for mild to moderate MS. A study by our colleagues, Rebecca Spain, MD, MPH, and colleagues showed that body-worn motion sensors detected large body sway in standing with eyes closed, as well as large trunk motion and slow turning velocity in people with mild MS who have normal walking speed.2 Hence, a major advantage of using these body-worn sensors is the increased sensitivity of the balance and gait measures to document mild disability and change with rehabilitation. The knowledge obtained from these objective measures of balance and gait can help therapists characterize how and why functional performance is impaired. Therapy can then be focused on the specific physiological reasons for difficulty in walking or balancing during specific tasks.
Our next step would be to investigate if these instrumented sway and gait measures are sensitive and specific to predict prospective/future falls in people with MS. Early detection of those at risk is critical to facilitate preventive means. Another direction is using body-worn, inertial sensors to measure mobility impairments during daily life. Fay Horak, PhD, PT, a co-investigator in this study, is comparing the benefits of continuous monitoring of movement using wireless inertial sensors in the home-settings in people with MS and comparing it to the gait metrics collected in the laboratory.3 It is believed that mobility testing as short walks in a research setting do not always reflect the actual functional mobility of patients in their everyday lives. In a research setting, people pay attention to their walking and tend to do their best, whereas in everyday life, people need to attend to other things while they walk, meaning that their automatic walking patterns are often more affected by their impairments. In addition, mobility can fluctuate over time due to many different factors, such as a patient’s fatigue (as observed in our preliminary findings). Therefore, continuous monitoring of gait-related metrics on a daily basis could help to better assess the risk of falling in people with MS, allowing clinicians to gain insight about their patients both inside and outside of healthcare facilities.
The body-worn, wireless, inertial sensors use sophisticated software algorithms to calculate balance and gait measures by combining the information from three-dimensional (3D) accelerometers, 3D gyroscopes, and magnetometer signals. Hence, these movement monitors are able to measure the quality of body motion by characterizing the kinematics and spatiotemporal aspects of mobility, both in the clinic and in real-life conditions, replacing more expensive, time-consuming, and nonportable motion analysis systems in laboratories. The use of this sophisticated technology can help clinicians identify balance impairments and therefore, fall risk, early, prior to any impairment in clinical assessments of balance and gait.
Transcript edited for clarity. For more coverage of ACTRIMS 2021, click here.