Detection of movement artifacts in respiratory inductance plethysmography: performance analysis of a Neyman-Pearson energy-based detector.
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference（2004）
摘要
In [3] we developed a method for the automated estimation of the phase relation between thoracic and abdominal signals measured by noninvasive respiratory inductance plethysmography (RIP). In the present paper, we improve on the phase estimator by including an automated procedure for the detection of periods of gross body movements. We assume that the number of sleep obstructive events during periods of gross body movements is zero in probability. We hope that combining the phase estimator with the gross body movement detector should yield improved diagnostic tools for the automated classification of obstructive hypopnea events.
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关键词
inductance plethysmography,obstructive hypopnea events,medical signal detection,automated phase estimator,thoracic signals,gross body movements,sleep,pneumodynamics,plethysmography,medical signal processing,neyman-pearson energy-based detector,automated phase estimation,noninvasive respiratory inductance plethysmography,obstructive apnea,automated signal classification,movement artifacts detection,signal classification,movement artifacts,respiratory signals,abdominal signals,phase estimation,signal detection,sleep obstructive events,patient diagnosis,improved diagnostic tools,medical diagnosis,respiratory system
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