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Performance Analysis of Stationary and Discrete Wavelet Transform for Action Potential Detection From Sympathetic Nerve Recordings in Humans

机译:人类交感神经记录的动作电位检测静止和离散小波变换的性能分析

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Accurate investigation of the sympathetic nervous system is important in the diagnosis and study of various autonomic and cardiovascular control and disorders. Sympathetic function associated with blood pressure regulation in humans can be evaluated by recording muscle sympathetic nerve activity (MSNA), which is characterised by synchronous neuronal discharges separated by periods of neural silence dominated by colored gaussian noise. In this paper two common methods for detecting filtered action potential in MSNA recordings is compared. These methods are based on stationary wavelet transform (SWT) and discrete wavelet transform (DWT). The performance analysis are evaluated using simulated MSNA using templates extracted from real MSNA recorded from three healthy subjects.
机译:准确调查同情神经系统在各种自主主义和心血管控制和疾病的诊断和研究中是重要的。通过记录肌肉交感神经活性(MSNA)可以评估与人类血压调节相关的交感神经功能,其特征在于由彩色高斯噪声主导的神经沉默的时期分开的同步神经元排放。在本文中,比较了用于检测MSNA记录中的过滤动作电位的两种常见方法。这些方法基于固定小波变换(SWT)和离散小波变换(DWT)。使用模拟MSNA使用从3个健康受试者记录的真实MSNA中提取的模板来评估性能分析。

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