Gait Characteristics Harvested During a Smartphone-Based Self-Administered 2-Minute Walk Test in People with Multiple...

Area of Science:

• Neurology
• Biomedical Engineering
• Rehabilitation Science

Background:

• Multiple sclerosis (MS) management requires sensitive measures of disease progression.
• Current clinician-administered 2-minute walk tests (2MWT) offer limited longitudinal data.
• Wearable sensors can capture high-density gait data during self-administered tests.

Purpose of the Study:

• To assess the test-retest reliability, standard error of measurement (SEM), and minimum detectable change (MDC) of gait characteristics.
• To evaluate a self-administered 2MWT using a waist-worn smartphone in persons with multiple sclerosis (PwMS) and healthy controls (HC).
• To determine the clinical utility of smartphone-based gait analysis for longitudinal monitoring in PwMS.

Main Methods:

• 51 PwMS and 11 HC underwent a self-administered 2MWT at home over 24 weeks using a smartphone-based inertial sensor.
• Gait characteristics including temporal, spatial, and spatiotemporal features were extracted.
• Test-retest reliability, SEM, and MDC were calculated for each gait feature.

Main Results:

• Excellent to good test-retest reliability was found for 58 out of 92 gait features in PwMS, with lower reliability in HC.
• Low SEM% and MDC% values indicated high precision for most gait characteristics in both PwMS and HC.
• The smartphone-based 2MWT demonstrated strong inter-session reliability in PwMS.

Conclusions:

• A self-administered, smartphone-based 2MWT provides reliable and precise measurements of gait characteristics in PwMS.
• This method offers clinically relevant estimates of change for longitudinal gait assessment in MS.
• The system supports the application of body-worn sensors for monitoring gait deficits and disease progression in PwMS.