Ahmed, N.,Rajagopalan, Kesava C.2009-03-192009-03-1919971997Source: Masters Abstracts International, Volume: 36-01, page: 0217.9780612209459http://hdl.handle.net/10393/4549http://dx.doi.org/10.20381/ruor-13918The Cohen's class of time-frequency spectral analysis distributions are receiving significant attention in the signal processing field because of their appropriateness in analyzing time-varying signals. This work has investigated in detail the application of several Cohen class time frequency distributions to Heart Rate Variability Signals. The clinical application of these tools to these physiological signals has been limited. Using simulated nonstationary and stationary HRV signals, it has been shown that the time-frequency spectral estimators such as smoothed pseudo-Wigner and the exponential distribution offer better performance over the Short Time Fourier Transform in terms of resolution and ability to track the nonstationary behavior or instantaneous frequency if the parameters used in the distributions are carefully chosen. These time-frequency spectral analysis tools have been used as a means to quantify the autonomic tone for seven adults under the effects of right unilateral stellate blockade. The mean peak amplitudes under the predefined low frequency (LF) band (0.05-0.15 Hz) and high frequency band (0.15-0.45 Hz) were computed for pre and post blockade conditions in the supine and standing positions. These results have demonstrated the partial stellate blockade decreased the LF areas by 33% when standing and underlines the importance of efferents from the contralateral and higher cervical ganglia in the control of heart rate. In conclusion, these time-frequency spectral analysis tools will provide the cardiologist with valuable diagnostic, cost effective and noninvasive information about the sympathetic and parasympathetic balance in patients to identify if they are at any medical risk.100 p.Engineering, Biomedical.Thesis