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Effect of Sleep and Biobehavioral Patterns on Multidimensional Cognitive Performance: Longitudinal, In-the-Wild Study
Manasa Kalanadhabhatta1, Tauhidur Rahman1, Deepak Ganesan1
1College of Information and Computer Sciences, University of Massachusetts Amherst, Amherst, MA, United States.
Journal of Medical Internet Research
|February 18, 2021
Summary
Fitness trackers offer insights into workplace performance, but real-world studies are lacking. This research links sleep duration and quality to alertness, and sleep timing to cognitive throughput, using wearable data.
Area of Science:
- Physiological monitoring and cognitive performance assessment.
- Wearable technology and real-world data analysis.
- Workplace productivity and human factors research.
Background:
- Fitness trackers are widely used, yet their ability to provide actionable workplace performance insights is under-explored.
- Existing research on physiological metrics and cognitive performance is largely based on controlled settings, limiting real-world applicability.
- There's a need for in-the-wild studies to validate theories linking wearable-derived physiological data to diverse cognitive performance outcomes.
Purpose of the Study:
- To evaluate theories on how sleep, activity, and heart rate parameters affect cognitive performance.
- To bridge the gap between controlled lab studies and real-world data from fitness trackers.
- To investigate the correlation between physiological metrics and cognitive performance in a diverse population.
Main Methods:
- A 6-week in-the-wild study using a Fitbit Charge 3 for physiological data and a smartphone app for cognitive tasks.
- Collected data from 24 participants across different work/study groups (shift workers, regular workers, graduate students).
- Analyzed sleep, heart rate, and physical activity data against measures of vigilant attention and cognitive throughput using repeated measures correlation.
Main Results:
- Daytime alertness significantly correlated with previous night's total sleep duration, REM, and light sleep duration.
- Cognitive throughput correlated with sleep timing (later sleep associated with lower throughput), not sleep duration.
- Both heart rate and physical activity positively correlated with alertness and cognitive throughput; alertness declined with homeostatic pressure.
Conclusions:
- Specific sleep-related physiological metrics differentially influence distinct cognitive performance measures.
- Findings highlight the need for targeted in-the-wild studies to understand how self-tracking data can predict cognitive performance.
- Real-world data from wearables can offer valuable, nuanced insights into the relationship between physiological state and cognitive function.
Keywords:
activityalertnesscircadian rhythmscognitive performancecognitive throughputfitness trackerssleepMore Related Videos
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