Assessing fatigue and sleep in chronic diseases using physiological signals from wearables: A pilot study

Emmi Antikainen (Corresponding Author), Haneen Njoum, Jennifer Kudelka, Diogo Branco, Rana Zia Ur Rehman, Victoria Macrae, Kristen Davies, Hanna Hildesheim, Kirsten Emmert, Ralf Reilmann, C. Janneke van der Woude, Walter Maetzler, Wan Fai Ng, Patricio O’Donnell, Geert Van Gassen, Frédéric Baribaud, Ioannis Pandis, Nikolay V. Manyakov, Mark van Gils, Teemu AhmaniemiMeenakshi Chatterjee (Corresponding Author)

Research output: Contribution to journalArticleScientificpeer-review

4 Citations (Scopus)
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Problems with fatigue and sleep are highly prevalent in patients with chronic diseases and often rated among the most disabling symptoms, impairing their activities of daily living and the health-related quality of life (HRQoL). Currently, they are evaluated primarily via Patient Reported Outcomes (PROs), which can suffer from recall biases and have limited sensitivity to temporal variations. Objective measurements from wearable sensors allow to reliably quantify disease state, changes in the HRQoL, and evaluate therapeutic outcomes. This work investigates the feasibility of capturing continuous physiological signals from an electrocardiography-based wearable device for remote monitoring of fatigue and sleep and quantifies the relationship of objective digital measures to self-reported fatigue and sleep disturbances. 136 individuals were followed for a total of 1,297 recording days in a longitudinal multi-site study conducted in free-living settings and registered with the German Clinical Trial Registry (DRKS00021693). Participants comprised healthy individuals (N = 39) and patients with neurodegenerative disorders (NDD, N = 31) and immune mediated inflammatory diseases (IMID, N = 66). Objective physiological measures correlated with fatigue and sleep PROs, while demonstrating reasonable signal quality. Furthermore, analysis of heart rate recovery estimated during activities of daily living showed significant differences between healthy and patient groups. This work underscores the promise and sensitivity of novel digital measures from multimodal sensor time-series to differentiate chronic patients from healthy individuals and monitor their HRQoL. The presented work provides clinicians with realistic insights of continuous at home patient monitoring and its practical value in quantitative assessment of fatigue and sleep, an area of unmet need.

Original languageEnglish
Article number968185
Number of pages17
JournalFrontiers in Physiology
Publication statusPublished - 14 Nov 2022
MoE publication typeA1 Journal article-refereed


  • biomedical signal analysis
  • chronic disease
  • continuous monitoring
  • fatigue
  • immune-mediated inflammatory disease
  • neurodegenerative diseases
  • sleep disturbance
  • wearabe sensors


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