Evaluating smartwatch-based sleep quality indicators of fitness to work
Rizqi Permana Sari, Khoirul Muslim (Faculty of Engineering, Universitas Indonesia, 2017)
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The study sought to evaluate smartwatch-based sleep quality indicators of fitness to work. Eighteen males (aged 20–26 years) were assigned to three randomized daytime sleep conditions (bad/moderate/good), which varied in terms of lighting, noise, and temperature, for a six-hour period. After this daytime sleep, participants completed simulated computer tasks during a 12-hour nighttime waking period. Prior to those tasks, participants’ fitness to work was determined by subjective measures that included the Sleep Quality Index-Karolinska Sleep Diary (SQI-KSD)), the Psychomotor Vigilance Task (PVT)), and the Karolinska Sleepiness Scale (KSS) to measure drowsiness. Total sleep time (TST), light sleep quantity (LSQ), deep sleep quantity (DSQ), and REM sleep quantity (REMSQ) were recorded using a smartwatch. The results confirmed that TST, LSQ, and SQI-KSD can be used as measures of sleep quality and fitness to work (p < 0.05). |
No. Panggil : | UI-IJTECH 8:2 (2017) |
Entri utama-Nama orang : | |
Subjek : | |
Penerbitan : | Depok: Faculty of Engineering, Universitas Indonesia, 2017 |
Sumber Pengatalogan : | LibUI eng rda |
ISSN : | 20869614 |
Majalah/Jurnal : | International Journal of Technology |
Volume : | Vol. 8, No. 2, April 2017: Hal. 329-337 |
Tipe Konten : | text |
Tipe Media : | unmediated |
Tipe Carrier : | volume |
Akses Elektronik : | https://doi.org/10.14716/ijtech.v8i2.6118 |
Institusi Pemilik : | Universitas Indonesia |
Lokasi : | Perpustakaan UI, Lantai 4 R. Koleksi Jurnal |
No. Panggil | No. Barkod | Ketersediaan |
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UI-IJTECH 8:2 (2017) | 08-23-28398439 | TERSEDIA |
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