NCT05271435

Digital Tools for Assessment of Motor Functions and Falls in ALS

• Status: Active Not Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 20 (estimated)
• Sponsor: Milton S. Hershey Medical Center · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

Summary

This is a 48-week single arm study that incorporates digital tools for assessing motor function as part of an ALS telemonitoring program. During the study, neck- and wrist-worn "activity sensors" (PAMSys, BioSensics, Newton, MA) that will be worn by subjects while performing tasks of daily living. Subjects will also complete a motor, speech, and handwriting assessment during site visits. Subjects will complete a digital home assessments of speech, handwriting, and pattern tracing tasks throughout the study, and report any falls which occur on the study tablet. The investigators will explore whether functional changes are sensitive to self-reported changes on the ALS Functional Rating Scale - Revised (ALFRS-R) over the length of the study.

Detailed description

Many of the recognized intrinsic factors for falls are commonly seen in ALS, including advanced age, muscle weakness, gait and balance problems, and previous falls. The American Academy of Neurology ALS Quality Standards Committee recommends querying patients for falls occurring in the past 12 months, indicating that prevention of falls is an important part of disease management. Despite this, the determinants and prevention of falls in this population is critically understudied. Among frail older adults, fallers (those who reported at least 1 fall in the last 6-months) spent more than twice as much time walking as non-fallers (those who reported no falls in the last 6-months). For these individuals, the best predictors of falling are measures related to activity exposure, such as time spent walking, average walking bout duration, or steps per day. Activity metrics of cadence variability, peak vertical acceleration variability, average duration of episodes of walking, frontal acceleration variability, average peak vertical acceleration, and average cadence have been shown to be associated with fall risk. During walking, individuals with ALS have increased and highly variable gait cycle time (time to complete a full walking cycle), along with reduced stride length with increased variability in stride length compared to healthy controls. The ability to observe changes in gait and posture has rapidly advanced around a revolution in mobile health technology. Inertial measurement units (IMUs), a standard inclusion of nearly all new smartphone/smartwatch devices, are small electronic chips that detect different aspects of inertial change, notably linear acceleration, angular velocity, and position relative to the magnetic field of the earth. Unlike their expansive use in movement disorders like Parkinson's disease, IMU-based gait assessment has been largely absent in ALS, despite the rapid changes to gait that may occur. The standard model for assessing and acting upon functional motor changes, including those impacting gait and falls, occurs roughly once every three months when patients are seen in the outpatient setting. Furthermore, self-reporting of falls has been shown to suffer from recall bias, resulting in low sensitivity and underreporting of fall events. In summary, patients with a rapidly progressing neurodegenerative disease, who in the standard care setting receive physical assessment motor function every three months, might stand to benefit from a home-based, objective biomarker for functional motor changes.

Conditions

• ALS
• PLS
• PMA

Interventions

Type	Name	Description
DEVICE	PAMSys Activity Monitoring System	This system is composed of a Study Tablet running custom fall detection and reporting software and PAMSys sensors. PAMSys provides clinical-grade physical activity monitoring, storing the raw accelerometer data that can be used for analyzing activity parameters such as those listed in Table 3. Sensor data will be downloaded manually upon receipt of the study device by Biosensics, the study sponsor. Sensors can be worn during all activities including while showering and sleeping. The rated battery life is 3-6 months for the fall sensor, and 4 weeks for the activity sensors. This system is not classified as a medical device. Reports of sensor use, step number, battery level, and memory availability are sent hourly to a secured and HIPAA compliant back-end server provided by BioSensics. The Study Tablet also contains modules for performing speech, handwriting, and pattern tracing tasks.
BEHAVIORAL	Motor, Speech, and Handwriting Assessment	These assessments occur at each study visit. After equipping the subject with 3 activity sensors (1 on pendant around neck and 2 on wrists). * 10-meter walk task (5 minutes) - The subject starts from a standing position and walks a length of 10 meters. The best time of three trials is used. * Timed Up and Go (TUG) test (5 minutes) - Subjects stand, walk to a marker on the floor 3 meters ahead, turn around the marker, walk back to the chair, and sit. The best time of three trials is used. * Handwriting Assessment Battery (HAB) (15 minutes) \[Faddy2008\] - The subject is seated at a table with a pencil and paper and performs a series of writing tasks. * Speech Assessment Battery (SAB)(10 minutes) - The participant will perform a set of audio recordings using the study tablet while sitting in a quiet room.

Timeline

• Start date: 2021-10-01
• Primary completion: 2026-06-30
• Completion: 2026-06-30
• First posted: 2022-03-09
• Last updated: 2026-02-13

Locations

1 site across 1 country: United States