4 papers
Establishing the Minimal Clinically Important Difference (MCID) for Smartphone-Derived Gait Measures in Multiple Sclerosis
Mike D Rinderknecht, Bernhard Fehlmann, Dimitar Stanev +7
Background: Digital health technologies allow for frequent, remote gait monitoring in people with multiple sclerosis (MS). However, to differentiate daily variability from actual d…
Analytical and Cross-Sectional Clinical Validity of a Smartphone-Based U-Turn Test in Multiple Sclerosis
Marta PÅonka, RafaÅ Klimas, Dimitar Stanev +12
Background: Gait and balance impairment can profoundly impact people with multiple sclerosis (PwMS). Objectives: To evaluate the analytical and clinical validity of the U-Turn Test…
Adaptive and robust smartphone-based step detection in multiple sclerosis
Lorenza Angelini, Dimitar Stanev, Marta PÅonka +12
Background: Many attempts to validate gait pipelines that process sensor data to detect gait events have focused on the detection of initial contacts only in supervised settings us…
Human Activity Recognition from Smartphone Sensor Data for Clinical Trials
Stefania Russo, RafaÅ Klimas, Marta PÅonka +6
We developed a ResNet-based human activity recognition (HAR) model with minimal overhead to detect gait versus non-gait activities and everyday activities (walking, running, stairs…