Improving Physical Movement During Stroke Rehabilitation: Investigating Associations Between Sleep Measured by Wearable Actigraphy Technology, Fatigue, and Key Biomarkers

Abstract

Background Sleep disturbances and fatigue are common in individuals undergoing inpatient rehabilitation following stroke. Understanding the relationships between sleep, fatigue, motor performance, and key biomarkers of inflammation and neuroplasticity could provide valuable insight into stroke recovery, possibly leading to personalized rehabilitation strategies. This study aimed to investigate the influence of sleep quality on stroke recovery by utilizing wearable technology to obtain objective sleep measurements. Additionally, we explored the relationships between sleep, fatigue, and motor performance. Lastly, the study aimed to determine if salivary biomarkers of stress, inflammation, and neuroplasticity were associated with fatigue or motor function post-stroke. Methods Eighteen individuals who experienced a stroke and were undergoing inpatient rehabilitation participated in a cross-sectional observational study. Following consent, participants completed questionnaires to assess sleep patterns, fatigue, and quality of life. Objective sleep was measured throughout one night using the wearable Philips Actiwatch. Upper limb motor performance was assessed on the following day and saliva was collected for biomarker analysis. Correlation analyses were performed to assess the relationships between variables. Results Participants reported poor sleep quality, frequent awakenings, and difficulties falling asleep following stroke. We identified a significant negative relationship between fatigue severity and both sleep quality (r=-0.539, p = 0.021) and participants experience of awakening from sleep (r=-0.656, p = 0.003). A significant positive relationship was found between grip strength on the non-hemiplegic limb and salivary gene expression of Brain-derived Neurotrophic Factor (r = 0.606, p = 0.028), as well as a significant negative relationship between grip strength on the hemiplegic side and salivary gene expression of C-reactive Protein (r=-0.556, p = 0.048). Additionally, there was a positive relationship between gene expression of Interleukin-1beta and stroke severity (r = 0.78, p = 0.003) as well as between days since stroke and gene expression of C-reactive Protein (r = 0.615, p = 0.025). Conclusion The findings of this study emphasize the importance of considering sleep quality, fatigue, and biomarkers in stroke rehabilitation to optimize recovery and that interventions may need to be tailored to the individual. Future longitudinal studies are required to explore these relationships over time. Integrating wearable technology for sleep monitoring and biomarker analysis can enhance monitoring and prediction of outcomes following stroke, ultimately improving rehabilitation strategies and patient outcomes.