PSG DYNAMIC CHANGES IN METHAMPHETAMINE ABUSE USING RECURRENCE QUANTIFICATION ANALYSIS
DOI:
https://doi.org/10.31436/iiumej.v20i1.956Keywords:
Sleep Apnea; Methamphetamine; Chaos; Recurrence Qualification Analysis; PolysomnographyAbstract
ABSTRACT: Polysomnography (PSG) is a standard approach based on comprehensive monitoring of cardiorespiratory signals during sleep. This study has been conducted on subjects with a record of methamphetamine abuse. The significance of this work is methamphetamine abuse detection and measurement without the use of blood tests. With regard to the nonlinear and chaotic dynamic of vital signals and the richness of PSG, the tool employed to carry out the study is Recurrence Qualification Analysis. The objective behind this is to observe and quantify nonlinear dynamic changes of vital signals caused by methamphetamine abuse. Results reveal that: 1) chaotic signals, in other words, system complexity has decreased; 2) under the influence of methamphetamine, signal entropy has increased, bringing about the irregularity of the signals; 3) methamphetamine consumption prompts signal compression to overtake signal expansion which means signal information has declined.
ABSTRAK: Polisomnografi (PSG) adalah pendekatan piawai berdasarkan pengawasan menyeluruh signal kardiorespiratori ketika tidur. Kajian ini telah dijalankan ke atas subjek yang mempunyai rekod salah guna methapitamin. Kepentingan kajian ini adalah bagi mengesan salah guna methapitamin dan mengukurnya tanpa menggunakan ujian darah. Dengan mengambil kira ketidak-linearan dan signal penting dinamik dan PSG yang berharga, kaedah yang digunakan bagi menjalankan kajian ini adalah Analisis Kelayakan Berulang. Objektif di sebalik kajian ini adalah bagi melihat dan mengkuantiti perubahan dinamik tidak linear ke atas signal penting disebabkan salah guna methapitamin. Hasil menunjukkan: 1) Signal huru-hara, atau kata lain, kesulitan sistem telah berkurang; 2) di bawah pengaruh methapitamin, signal entropi telah bertambah, menjadikan signal tidak normal; 3) pengambilan methapitamin menyebabkan signal mampat mengambil alih signal kembang bermaksud informasi signal telah berkurang.
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Netsi E, Santos IS, Stein A, Barros FC, Barros AJD, Matijasevich A. (2017). A different rhythm of life: sleep patterns in the first 4 years of life and associated sociodemographic characteristics in a large Brazilian birth cohort. Sleep Medicine, 37: 77-87.
Goldberger AL, Amaral LA, Glass L, Hausdorff JM, Ivanov PC, Mark RG, et al. (2000). Physiobank, physiotoolkit, and physionet components of a new research resource for complex physiologic signals. Circulation, 101: e215-e220.
Valladares EM, Irwin MR. (2007). Polysomnographic sleep dysregulation in cocaine dependence. The Scientific World Journal, 7: 213-216.
Subasi A. (2013). Classification of EMG signals using PSO optimized SVM for diagnosis of neuromuscular disorders. Computers in Biology and Medicine, 43: 576-586.
Tkachenko N, Singh K, Abreu N, Morse AM, Day C, Fitzgerald K, et al. (2016). Establishing a Role for Polysomnography in Hospitalized Children. Pediatric Neurology, 57: 39-45.
O'Reilly C, Gosselin N, Carrier J, Nielsen T. (2014). Montreal Archive of Sleep Studies: an open‐access resource for instrument benchmarking and exploratory research. Journal of Sleep Research, 23: 628-635.
Koebbe M, Mayer-Kress G. (1992). Use of recurrence plots in the analysis of time-series data," in Santa Fe Institute Studies in the Sciences of Complexity-Proceedings, pp. 361-361.
Eckmann J-P, Kamphorst SO, Ruelle D. (1987). Recurrence plots of dynamical systems. EPL (Europhysics Letters), 4: 973.
Marwan N, Wessel N, Meyerfeldt U, Schirdewan A, Kurths J. (2002). Recurrence-plot-based measures of complexity and their application to heart-rate-variability data. Physical Review E, 66: 026702.
Marwan N, Kurths J. (2004). Cross recurrence plots and their applications. Mathematical Physics Research at the Cutting Edge, CV Benton Editor, pp. 101-139.
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