Cancer Survivorship & Digital Biomarkers
Wearable-derived HRV, sleep, and physical activity in longitudinal cancer survivorship cohorts
Cancer survivorship research examines the long-term physical, cognitive, and psychosocial consequences of cancer and its treatment. My work in this area focuses on objectively measuring survivorship outcomes through wearable sensor technology.
Approach
Rather than relying solely on self-reported outcomes, this research stream uses commercially available wearable devices to derive continuous, passive digital biomarkers:
- Heart-rate variability (HRV) — an autonomic nervous system index sensitive to physiological stress and recovery
- Sleep architecture — duration, efficiency, and fragmentation patterns
- Physical activity — step counts, intensity distributions, and sedentary time
These signals are analyzed in a longitudinal framework using mixed-effects models to estimate trajectories and identify modifiable risk factors that predict cognitive and functional outcomes in cancer survivors.
Methods
- Repeated-measures and mixed-effects models for correlated longitudinal data
- Wearable data cleaning, epoch aggregation, and feature extraction pipelines
- Cognitive screening instrument integration (e.g., standardized neuropsychological batteries)
- Collaboration within the FIU Stempel College of Public Health & Social Work, under Dr. Shanna L. Burke
Why it matters
Approximately 18 million cancer survivors live in the United States. Identifying early, scalable biomarkers of cognitive and functional decline offers pathways to timely intervention and improved quality of life — without the burden of invasive testing.