A Method for Napping Time Recommendation Using Electrical Brain Activity

Sheng Fu Liang, Yu Hsuan Shih, Yu Han Hu, Chih En Kuo

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


Napping in the workplace has become popular. Knowing how to nap for brain benefits is important. We designed a nap experiment to investigate how napping after different sleep stages impacts procedural memory and sleepiness. In total, 45 nonhabitual nappers were randomly assigned to the Wake group (no napping), N2 group (napping and being woken after enough N2 sleep), and slow-wave sleep (SWS) group (napping and being woken after the end of the first cycle of slow-wave sleep). The results show that the N2 group produces benefits in procedural memory consolidation and sleepiness reduction. In contrast, the SWS group had a lower behavioral performance than the N2 group and their sleepiness. The Wake group had lower performance and higher sleepiness score than the other groups. The results suggest that the ideal napping time is 10-20 min of N2 sleep. Considering that people's sleep-onset time might be different, we developed a napping time suggestion system using a single-channel electroencephalogram signal. The testing results show that the difference between a 10-min nap of N2 sleep calculated by our system and by an expert is only 0.45 min on average, which demonstrates the feasibility of waking people up at the right time.

Original languageEnglish
Article number9082002
Pages (from-to)645-657
Number of pages13
JournalIEEE Transactions on Cognitive and Developmental Systems
Issue number3
Publication statusPublished - 2020 Sep

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence


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