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<p>Daytime napping improves performance, which is maximized with a post-N2 9-min nap. We evaluated whether a system that enables optimal-time automatic awakening using blood flow parameters could improve performance, sleepiness, and fatigue compared to no-nap. Additionally, we investigated whether its performance was comparable to manual awakening based on polysomnography. Eighty-one healthy adults (33.6 ± 12.8 years) were randomly assigned to automatic- or manual-awakening or rest groups. A task bout comprising a digit-symbol substitution test (DSST), visual detection test, and sleepiness and fatigue questionnaires was performed three times per session before napping and for six sessions after napping. In all post-nap sessions, sleepiness and fatigue in the automatic awakening group decreased, compared to the rest group, and were comparable to those in the manual awakening group. The DSST improved in the sixth post-nap session for the manual awakening group compared to the rest group; no improvement was observed in the automatic awakening group. The system model was refined by adding training data and tested on 50 healthy adults (40.6 ± 13.1 years). The test results revealed that the N2 detection accuracy of the system improved. The optimal automatic awakening system improves subjective sleepiness and fatigue, and further improvements in its accuracy may enhance post-nap performance.</p>

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Effects of optimal timed automatic awakening from a short daytime nap on cognitive performance, alertness, and fatigue

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月24日

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  • Yoko Suzuki,
  • Chihiro Suzuki,
  • Yurina Suzuki,
  • Fusae Kawana,
  • Tomohiro Ohigashi,
  • Kazushi Maruo,
  • Takahiro Watanabe,
  • Takashi Abe

摘要

Daytime napping improves performance, which is maximized with a post-N2 9-min nap. We evaluated whether a system that enables optimal-time automatic awakening using blood flow parameters could improve performance, sleepiness, and fatigue compared to no-nap. Additionally, we investigated whether its performance was comparable to manual awakening based on polysomnography. Eighty-one healthy adults (33.6 ± 12.8 years) were randomly assigned to automatic- or manual-awakening or rest groups. A task bout comprising a digit-symbol substitution test (DSST), visual detection test, and sleepiness and fatigue questionnaires was performed three times per session before napping and for six sessions after napping. In all post-nap sessions, sleepiness and fatigue in the automatic awakening group decreased, compared to the rest group, and were comparable to those in the manual awakening group. The DSST improved in the sixth post-nap session for the manual awakening group compared to the rest group; no improvement was observed in the automatic awakening group. The system model was refined by adding training data and tested on 50 healthy adults (40.6 ± 13.1 years). The test results revealed that the N2 detection accuracy of the system improved. The optimal automatic awakening system improves subjective sleepiness and fatigue, and further improvements in its accuracy may enhance post-nap performance.