Automated quantification of sympathetic beat-by-beat activity, independent of signal quality.
Sympathetic nerve activity (SNA) can provide critical information on cardiovascular regulation; however, in a typical laboratory setting, adequate recordings require assiduous effort, and otherwise high-quality recordings may be clouded by frequent baseline shifts, noise spikes, and muscle twitches. Visually analyzing this type of signal can be a tedious and subjective evaluation, whereas objective analysis through signal averaging is impossible. We propose a new automated technique to identify bursts through objective detection criteria, eliminating artifacts and preserving a beat-by-beat SNA signal for a variety of subsequent analyses. The technique was evaluated during both steady-state conditions (17 subjects) and dynamic changes with rapid vasoactive drug infusion (14 recordings from 5 subjects) on SNA signals of widely varied quality. Automated measures of SNA were highly correlated to visual measures of steady-state activity (r = 0.903, P < 0.001), dynamic relation measures (r = 0.987, P < 0.001), and measures of burst-by-burst variability (r = 0.929, P < 0.001). This automated sympathetic neurogram analysis provides a viable alternative to tedious and subjective visual analyses while maximizing the usability of noisy nerve tracings.
Hamner
J W
JW
Laboratory for Cardiovascular Research, Research and Training Institute, Hebrew Rehabilitation Center for the Aged, Boston, Massachusetts 02131, USA.
Taylor
J A
JA
D000293:Adolescent; D000328:Adult; D000368:Aged; D000465:Algorithms; D016477:Artifacts; D017704:Baroreflex / Q000502:physiology*; D005260:Female; D006339:Heart Rate / Q000502:physiology; D006801:Humans; D008297:Male; D008875:Middle Aged; D010543:Peroneal Nerve / Q000502:physiology; D017156:Photoplethysmography / Q000379:methods*; D012119:Respiration; D012815:Signal Processing, Computer-Assisted; D013564:Sympathetic Nervous System / Q000502:physiology*