Previously submitted to: JMIR mHealth and uHealth (no longer under consideration since Aug 11, 2025)
Date Submitted: Dec 29, 2024
Open Peer Review Period: Jan 2, 2025 - Feb 27, 2025
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Predicting Sleep Efficiency Based on Interpretable AI Using Smart Wearable Device
ABSTRACT
Background:
Sleep plays a crucial role in the immune system, memory, and emotional control, which in turn affects overall quality of life. Although several studies have used wearable devices to measure sleep efficiency, these tools primarily monitor sleep patterns without offering strategies to improve sleep efficiency.
Objective:
In response, our study introduced a framework that not only measures sleep efficiency using wearable technology but also suggests lifestyle changes to enhance sleep quality, using explainable artificial intelligence.
Methods:
Lifelog data was measured using a smartwatch and only features that can be controlled by the user, such as the number of steps, were extracted from the lifelog data. A light gradient-boosted machine was utilized as a classifier to predict whether sleep efficiency was low or high. Using Shapley additive explanation, important features related to sleep efficiency, such as walking speed were identified and lifestyles were recommended to improve sleep efficiency. We also investigated the relationship between sleep efficiency and sleep stages, which were excluded from the features extracted as uncontrolled factors from wearable devices.
Results:
Results show that, following a 10-fold leave-one-subject-out cross-validation evaluation, an accuracy rate of 80% was achieved in measuring sleep efficiency. In a scenario where lifestyle was adjusted according to the feature importance derived from the model output, an improvement from bad to good sleep efficiency was observed. In addition, the sleep stage variables were found to be statistically higher for the cases exhibiting good sleep efficiency.
Conclusions:
This framework provides insights into developing technologies that suggest lifestyle changes to enhance sleep efficiency, potentially leading to better health outcomes through improved sleep quality.
Citation
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