JMIR Publications

ABSTRACT

Background:

Fatigue is a common, debilitating symptom across many chronic and post-acute conditions, yet it remains difficult to assess in routine care due to its subjective, fluctuating, and context-dependent nature. Conventional fatigue assessments rely primarily on retrospective self-report measures, which lack temporal resolution and ecological validity. Advances in digital health technologies create new opportunities to capture fatigue as it is experienced in daily life through continuous, remote, and patient-centred data collection.

Objective:

This study evaluates the feasibility and acceptability of a fully remote digital health platform that integrates wearable sensing, environmental monitoring, cardiorespiratory physiology, and ecological momentary assessment to capture the lived experience of fatigue in everyday life.

Methods:

The Understanding Patterns of Fatigue in Health and Disease study (NCT05622669) was a fully remote mixed-methods observational study. Participants with long COVID, myeloma, heart failure, and healthy controls completed either 2 or 4 weeks of monitoring. Data were collected using a wrist-worn wearable bracelet, in-home Bluetooth environmental beacons, a chest-worn ECG patch, and a smartphone application delivering ecological momentary assessments of fatigue. Data streams were integrated into unified visual representations combining activity, sleep, location, physiology, and self-reported symptoms. Feasibility was evaluated through recruitment, retention, adherence, and data completeness. Acceptability and interpretability were assessed through end-of-study interviews and optional participant feedback sessions.

Results:

Forty participants were enrolled and 37 completed study monitoring (retention rate 92.5%). Wearable bracelet data were available for 87% of study days, with adherence reaching 93% during periods of device operation. Ecological momentary assessments were completed on 83% of study days, whereas ECG patch data completeness averaged 72%. Twenty-two participants participated in feedback sessions. Participants reported high acceptability of the remote study procedures and considered the integrated visualisations to be plausible representations of their daily routines and symptom experiences. Contextual information derived from room-level location and environmental monitoring improved interpretation of activity and physiological data, enabling identification of behavioural patterns associated with work schedules, treatment cycles, and daily functioning that would not have been apparent from wearable-derived measures alone.

Conclusions:

A fully remote digital health platform integrating wearable, environmental, physiological, and self-reported data was feasible and acceptable across diverse populations experiencing fatigue. The integration of contextual information with behavioural and physiological monitoring enabled interpretable representations of daily life that participants recognised as meaningful reflections of their lived experience. These findings provide methodological guidance for future digital health studies and support the development of context-aware approaches to fatigue assessment and digital phenotyping in real-world settings. Clinical Trial: NCT05622669: Understanding Patterns of Fatigue in Health and Disease study (registered 17 November 2022)