Digital Health for Tracking Long-Covid Symptoms with Data Insights from Mobile App Questionnaires and Wearable Devices
Year: 2025
Type: book-chapter
Study design: Observational Study
Abstract: With the ongoing mutations of COVID-19 leaving many survivors with debilitating symptoms known as Long-Covid, countless individuals are struggling with persistent fatigue, cognitive impairments, and respiratory issues that can last for months or even years, profoundly disrupting their daily lives and rendering them unable to return to work or engage in social activities. Thus, this paper develops a comprehensive methodology that integrates wearable biometric data and patient-reported outcomes to enhance the monitoring and management of Long-Covid symptoms, desgined to support patient care and quality of life. The methodology involved collecting biometric data from wearable devices and psychometric assessments through mobile app questionnaires, and modeling them using mixed linear regression. Results indicated that variations in heart rate and physical activity levels were significant predictors of fatigue, stress, and pain, with lower morning activity linked to increased anxiety and pain. Additionally, participant feedback highlighted the mobile app's user-friendliness and effectiveness in tracking symptoms. Integrating wearable technology with psychological assessments in clinical practice can facilitate accurate symptom tracking and personalized interventions for individuals suffering from Long-Covid, ultimately improving patient outcomes and overall health management.
DOI: 10.3233/shti250127
Language: English
Subfield: Neurology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4409265987