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Wavelet entropy is an analysis tool applicable to biomedical signals, including EEG and ECG. The current paper proposes an application of methods from visual analytics to time-frequency energy distribution in ECG signals, with the goal of studying heart rate variability from the main ECG band corresponding to heart rate. Such an approach can complement(More)
Cardiovascular disease (CVD) impacts the autonomic nervous system and cognitive functions related to activities of daily living, including driving an automobile. Although CVD has been linked to unsafe driving, mechanisms underlying this relationship remain elusive. The aim of this study was to examine the role of cognitive functions and the autonomic(More)
Cardiovascular disease (CVD) has been linked to decreases in driving performance and an increased crash risk. Regular exercise has been linked to improved driving performance among healthy adults. The aim of the current study was to investigate the relationship between a 12-week cardiac rehabilitation (CR) program and driving performance among individuals(More)
Because of its utility in the investigation and diagnosis of clinical abnormalities, heart rate variability (HRV) has been quantified with both time and frequency analysis tools. Recently, time-frequency methods, especially wavelet transforms, have been applied to HRV. In the current study, a complementary computational approach is proposed wherein(More)
Biomedical signals are generally complex, non-stationary, and non-periodic, making them difficult to analyze and to compare. Time-frequency correlation, in combination with information theoretic measures, can provide a clearer quantitative understanding of the relationships between these signals. Using the known correspondence between muscle sympathetic(More)
During Doppler ultrasound assessment of blood flow, a wall filter is used to reduce or eliminate high-amplitude, low-velocity signals from the vessel wall and the surrounding tissue. This study investigated the impact of a range of wall filters (22 Hz, 75 Hz, 128 Hz, and 252 Hz) on the accuracy of forearm blood flow monitoring during the sympathoexcitatory(More)
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