Abstract
In this paper a definition of the activity (ACT) variable is proposed and a method to estimate it from the noisy actigraph output sensor data is described. A statistical model for the actigraph data generation process is suggested based on its working physical principles and on physiological considerations about human activity. The purposeless nature of the sleeping movements is used to discriminate the Sleep and Wakefulness (SW) states.
The estimated ACT signal from the actigraph output signal is correlated with the data from a Sleep Diary to validate the SW oscillations, computed from the ACT. A Sleep electronic Diary (SeD) was implemented in the scope of this work to make it possible an accurate register of the patient activities relevant for the diagnosis of sleep disorders.
Examples using real data, illustrating the application of the method, have shown high correlation between the output of the proposed algorithm that characterizes the activity and the data registered in the SeD.
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References
Pandi-Perumal, S.R., Leger, D.: Sleep Disorders: Their Impact on Public Health, Informa Healthcare, UK (December 2006)
Morgenthaler, T.I., Lee-Chiong, T., Alessi, C., Friedman, L., Aurora, R.N., Boehlecke, B., Brown, T., Chesson, A.L., Kapur, V., Maganti, R., Owens, J., Pancer, J., Swick, T.J., Zak, R.: Practice parameters for the clinical evaluation and treatment of circadian rhythm sleep disorders. Sleep 30(11), 1445–1459 (2007)
Motoi, K., Tanaka, S., Nogwa, M., Yamakoshi, K.: Evaluation of a new sensor system for ambulatory monitoring of human posture together with walking speed. Transactions of the Japanese Society for Medical and Biological Engineering: BME 41(4), 273–279 (2003)
Cole, R.J., Kripke, D.F., Gruen, W., Mullaney, D.J., Gillin, J.C.: Automatic sleep/wake identification from wrist activity. Sleep 15(5), 461–469 (1992)
Paquet, J., Kawinska, A., Carrier, J.: Wake detection capacity of actigraphy during sleep. Sleep 30(10), 1362–1369 (2007)
Jean-Louis, G., Kripke, D.F., Cole, R.J., Assmus, J.D., Langer, R.D.: Sleep detection with an accelerometer actigraph: comparisons with polysomnography. Physiology & behavior 72(1-2), 21–28 (2001)
Gimeno, V., Sagales, T., Miguel, L., Ballarin, M.: The statistical distribution of wrist movements during sleep. Neuropsychobiology 38, 108–112 (1998)
Vgontzas, A.N., Kales, A.: Sleep and its disorders. Annual Review of Medicine 50, 387–400 (1999)
Boykov, Y., Veksler, O., Zabih, R.: Fast approximate energy minimization via graph cuts. IEEE Trans. Pattern Anal. Mach. Intell. 23(11), 1222–1239 (2001)
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Pires, P., Paiva, T., Sanches, J. (2009). Sleep/Wakefulness State from Actigraphy. In: Araujo, H., Mendonça, A.M., Pinho, A.J., Torres, M.I. (eds) Pattern Recognition and Image Analysis. IbPRIA 2009. Lecture Notes in Computer Science, vol 5524. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02172-5_47
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DOI: https://doi.org/10.1007/978-3-642-02172-5_47
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