Abstract
Nap is an effective way to reduce daily-level fatigue after several hours of work. However, no alarm clock, which intelligently manages the nap duration with good autonomic nervous recovery (ANR) from fatigue, has been reported in literature. In this work, an intelligent biological alarm clock algorithm was designed on the basis of electrocardiogram (ECG) and electroencephalogram (EEG) data acquisition and analysis. ECG data samples were collected from 31 subjects in 278 times of nap experiments and categorized into good, moderate, and poor ANR datasets according to the degree of sympathetic withdrawal and parasympathetic activation during the nap. In practice, the alarm clock automatically classified the new-coming ECG data as good, moderate, or poor ANR with a classifier trained by the abovementioned ANR datasets. A prototype system of the intelligent alarm clock algorithm was implemented and validated in real-scene naps. The prototype system detected falling asleep during the closed-eye naps with a true positive rate of 93.55% and a true negative rate of 100%.
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References
T.L. Rupp, Concepts of fatigue, sleepiness, and alertness, in: Encyclopedia of Sleep, 2013, pp. 24–26.
R.O. Phillips, A review of definitions of fatigue – and a step towards a whole definition, Transp. Res. Part F: Traffic Psychol. Behav. 29 (2015), 48–56
M. Cella, T. Chalder, Measuring fatigue in clinical and community settings, J. Psychosom. Res. 69(1) (2010), 17–22.
M. Tanaka, K. Mizuno, S. Tajima, T. Sasabe, Y. Watanabe, Central nervous system fatigue alters autonomic nerve activity, Life Sci. 84(7–8) (2009), 235–239.
K. Mizuno, K. Tajima, Y. Watanabe, H. Kuratsune, Fatigue correlates with the decrease in parasympathetic sinus modulation induced by a cognitive challenge, Behav. Brain Funct. 10(1) (2014), 25–32.
M. Tanaka, K. Mizuno, K. Yamaguti, H. Kuratsune, A. Fujii, H. Baba, K. Matsuda, A. Nishimae, T. Takesaka, Y. Watanabe, Autonomic nervous alterations associated with daily level of fatigue, Behav. Brain Funct. 7 (2011), 46–51
L. Wulsin, J. Herman, J.F. Thayer, Stress, autonomic imbalance, and the prediction of metabolic risk: a model and a proposal for research, Neurosci. Biobehav. Rev. 86 (2018), 12–20
S.S.H. Nazari, A. Moradi, K. Rahmani, A systematic review of the effect of various interventions on reducing fatigue and sleepiness while driving, Chin. J. Traumatol. 5 (2017), 249–258
D. Darwent, D. Dawson, J.L. Paterson, G.D. Roach, S.A. Ferguson, Managing fatigue: it really is about sleep, Accid. Anal. Prev. 82 (2015), 20–26
G. Calandra-Buonaura, F. Provini, P. Guaraldi, G. Plazzi, P. Cortelli, Cardiovascular autonomic dysfunctions and sleep disorders, Sleep Med. Rev. 26 (2016), 43–56
E. Tobaldini, G. Costantino, M. Solbiati, C. Cogliati, T. Kara, L. Nobili, N. Montano, Sleep, sleep deprivation, autonomic nervous system and cardiovascular diseases, Neurosci. Biobehav. Rev. 74 (2017), 321–329
S.L. Staton, S.S. Smith, C. Hurst, C.L. Pattinson, K.J. Thorpe, Mandatory nap times and group napping patterns in child care: an observational study, Behav. Sleep Med. 15(2) (2017), 129–143.
M. Zaregarizi, B.E. Edwards, K. George, Y. Harrison, H. Jones, G. Atkinson, Acute changes in cardiovascular function during the onset period of daytime sleep: comparison to lying awake and standing, J. Appl. Physiol. 103(4) (2007), 1332–1338.
D.R. Samson, G.M. Yetish, A.N. Crittenden, I.A. Mabulla, A.Z.P. Mabulla, C.L. Nunn, What is segmented sleep? Actigraphy field validation for daytime sleep and nighttime wake, Sleep Health. 2 (2016), 341–347
F.Z. Hou, F.W. Li, J. Wang, F.R. Yan, Visibility graph analysis of very short-term heart rate variability during sleep, Physica A. 458 (2016), 140–145
P.K. Stein, Y. Pu, Heart rate variability, sleep and sleep disorders, Sleep Med. Rev. 16(1) (2012), 47.
J. Werth, X. Long, E. Zwartkruispelgrim, H. Niemarkt, W. Chen, R.M. Aarts, P. Andriessen, Unobtrusive assessment of neonatal sleep state based on heart rate variability retrieved from electrocardiography used for regular patient monitoring, Early Hum. Dev. 113 (2017), 104–113
M. Pawlowski, M. Gazea, B. Wollweber, M. Dresler, F. Holsboer, M.E. Keck, A. Steiger, M. Adamczyk, T. Mikoteit, Heart rate variability and cordance in rapid eye movement sleep as biomarkers of depression and treatment response, J. Psychiatr. Res. 92 (2017), 64–73
W. Wen, G. Liu, Z.H. Mao, W. Huang, X. Zhang, H. Hu, J. Yang, W. Jia, Toward constructing a real-time social anxiety evaluation system: exploring effective heart rate features, IEEE Trans. Affect. Comput. 99 (2018), 1.
S. Havlin, L.A. Amaral, Y. Ashkenazy, A.L. Goldberger, P.Ch. Ivanov, C.-K. Peng, H.E. Stanley, Application of statistical physics to heartbeat diagnosis, Physica A. 274 (1999), 99–110
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Xie, J., Wen, W., Liu, G. et al. Intelligent Biological Alarm Clock for Monitoring Autonomic Nervous Recovery During Nap. Int J Comput Intell Syst 12, 453–459 (2019). https://doi.org/10.2991/ijcis.d.190304.001
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DOI: https://doi.org/10.2991/ijcis.d.190304.001