Proceedings of the 12th EAI International Conference on Pervasive Computing Technologies for Healthcare – Demos, Posters, Doctoral Colloquium

Research Article

Recognizing Digital Biomarkers for Fatigue Assessment in Patients with Multiple Sclerosis

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  • @INPROCEEDINGS{10.4108/eai.20-4-2018.2276340,
        author={Liliana Barrios and Pietro Oldrati and Silvia Santini and Andreas Lutterotti},
        title={Recognizing Digital Biomarkers for Fatigue Assessment in Patients with Multiple Sclerosis},
        proceedings={Proceedings of the 12th EAI International Conference on Pervasive Computing Technologies for Healthcare -- Demos, Posters, Doctoral Colloquium},
        publisher={EAI},
        proceedings_a={PERVASIVEHEALTH - EAI},
        year={2018},
        month={8},
        keywords={mobile health; multiple sclerosis; fatigue assessment using physiological sensors},
        doi={10.4108/eai.20-4-2018.2276340}
    }
    
  • Liliana Barrios
    Pietro Oldrati
    Silvia Santini
    Andreas Lutterotti
    Year: 2018
    Recognizing Digital Biomarkers for Fatigue Assessment in Patients with Multiple Sclerosis
    PERVASIVEHEALTH - EAI
    EAI
    DOI: 10.4108/eai.20-4-2018.2276340
Liliana Barrios1,*, Pietro Oldrati1, Silvia Santini2, Andreas Lutterotti3
  • 1: ETH Zurich
  • 2: Universita della Svizzera Italiana
  • 3: University of Zurich
*Contact email: liliana.barrios@inf.ethz.ch

Abstract

We describe our ongoing work on the design and implementation of a system to continuously monitor different physiological parameters in patients with multiple sclerosis (MS). We focus specifically on monitoring functions of the autonomous nervous system and activities of daily life using wearable and mobile sensors and to correlate these with important symptoms of MS, in particular, fatigue. Fatigue is a highly prevalent and debilitating symptom in MS patients. However, the underlying cause and pathogenetic mechanisms are poorly understood and consequently therapeutic interventions limited. As the first step in our research effort, we evaluate the feasibility of off-the-shelf devices to record several physiological parameters in MS patients continuously.