OBJECTIVES: We describe the methods for power spectral analysis (PSA) of sleep electroencephalogram (EEG) data at a large clinical and research sleep laboratory. The multiple-bedroom, multiple-polygraph design of the sleep laboratory poses unique challenges for the quantitative analysis of the data. This paper focuses on the steps taken to ensure that our PSA results are not biased by the particular bedroom or polygraph from which the data were acquired. METHODS: After describing the data acquisition system hardware, we present our signal amplitude calibration procedure and our methods for performing PSA. We validate the amplitude calibration procedure in several experiments using PSA to establish tolerances for data acquisition from multiple bedrooms and polygraphs. RESULTS: Since it is not possible to acquire identical digitized versions of an EEG signal using different sets of equipment, the best that can be achieved is data acquisition that is polygraph-independent within a known tolerance. We are able to demonstrate a tolerance in signal amplitude of +/- 0.25% when digitizing data from different bedrooms. When different data acquisition hardware is used, the power tolerance is approximately +/- 3% for frequencies from 1 to 35 Hz. The power tolerance is between +/- 3 and +/- 7% for frequencies below 1 Hz and frequencies between 35 and 50 Hz. Additional data demonstrate that variability due to the hardware system is small relative to the inherent variability of the sleep EEG. CONCLUSION: The PSA results obtained in one location can be replicated elsewhere (subject to known tolerances) only if the data acquisition system and PSA method are adequately specified.
OBJECTIVES: We describe the methods for power spectral analysis (PSA) of sleep electroencephalogram (EEG) data at a large clinical and research sleep laboratory. The multiple-bedroom, multiple-polygraph design of the sleep laboratory poses unique challenges for the quantitative analysis of the data. This paper focuses on the steps taken to ensure that our PSA results are not biased by the particular bedroom or polygraph from which the data were acquired. METHODS: After describing the data acquisition system hardware, we present our signal amplitude calibration procedure and our methods for performing PSA. We validate the amplitude calibration procedure in several experiments using PSA to establish tolerances for data acquisition from multiple bedrooms and polygraphs. RESULTS: Since it is not possible to acquire identical digitized versions of an EEG signal using different sets of equipment, the best that can be achieved is data acquisition that is polygraph-independent within a known tolerance. We are able to demonstrate a tolerance in signal amplitude of +/- 0.25% when digitizing data from different bedrooms. When different data acquisition hardware is used, the power tolerance is approximately +/- 3% for frequencies from 1 to 35 Hz. The power tolerance is between +/- 3 and +/- 7% for frequencies below 1 Hz and frequencies between 35 and 50 Hz. Additional data demonstrate that variability due to the hardware system is small relative to the inherent variability of the sleep EEG. CONCLUSION: The PSA results obtained in one location can be replicated elsewhere (subject to known tolerances) only if the data acquisition system and PSA method are adequately specified.
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Authors: Scott D Rothenberger; Robert T Krafty; Briana J Taylor; Matthew R Cribbet; Julian F Thayer; Daniel J Buysse; Howard M Kravitz; Evan D Buysse; Martica H Hall Journal: Psychophysiology Date: 2014-11-28 Impact factor: 4.016
Authors: Sebastian Zaremba; Christina H Shin; Matthew M Hutter; Sanjana A Malviya; Stephanie D Grabitz; Teresa MacDonald; Daniel Diaz-Gil; Satya Krishna Ramachandran; Dean Hess; Atul Malhotra; Matthias Eikermann Journal: Anesthesiology Date: 2016-07 Impact factor: 7.892
Authors: Kristine A Wilckens; Martica H Hall; Robert D Nebes; Timothy H Monk; Daniel J Buysse Journal: Behav Sleep Med Date: 2015-08-31 Impact factor: 2.964
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