Detecting fatigue in multiple sclerosis through automatic speech analysis

Jahr

2024

Autoren

Dias M, Dörr F, Garthof S, Schäfer S, Elmers J, Schwed L, Linz N, Overell J, Hayward-Koennecke H, Tröger J, König A, Dillenseger A, Tackenberg B, Ziemssen T.

Verlag

Front Hum Neurosci. 2024 Sep 13;18:1449388.

Link

https://doi.org/10.3389/fnhum.2024.1449388

Detecting fatigue in multiple sclerosis through automatic speech analysis

A longitudinal analysis of real world symptom tracking and patient-reported outcomes in Brisa, a German Digital Health App for multiple sclerosis

User-centered design and formative evaluation of a gait dashboard for multidimensional walking assessment in multiple sclerosis

Delivering high-quality multiple sclerosis care in Germany: challenges and regional models

MSPEECH (multiple sclerosis monitoring through speech interaction in clinic and at home): a Living Lab study protocol for co-created, speech-based digital biomarkers in multiple sclerosis

Assessing Progression Independent of Relapse Activity in Multiple Sclerosis Using a Patient-Reported Disability Measure and Self-Administered Neuroperformance Outcomes