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During physical exercise, pulse transit time (PTT), expressed as the interval between ventricular electrical activity and peripheral pulse wave, may provide a surrogate estimate for blood pressure by the use of specific calibration procedures. The objective of this study was to determine systolic blood pressure (SBP) values derived from the PTT method and from an established method of non-invasive continuous blood pressure measurement based on the volume clamp technique, and to compare their agreement with sphygmomanometry during exercise tests. In 18 subjects, electrocardiogram (ECG) and finger-photoplethysmography were continuously recorded during maximal cycle exercise tests. Intermittent and continuous blood pressure measurements were simultaneously taken using automated sphygmomanometry and a Portapres Model-2 device, respectively. PTT was calculated for each ECG R-wave and the corresponding steepest upstroke slope in the photoplethysmogram, and was transformed to a continuous blood pressure estimate using multipoint nonlinear regression calibration based on the individual subject's sphygmomanometer readings. Bland-Altman limits of agreement between PTT-derived SBP estimates and sphygmomanometer values were -24.7 to 24.1 mmHg, and between Portapres and sphygmomanometer SBP values were -42.0 to 70.1 mmHg. For beat-to-beat SBP estimation during exercise, PTT measurement combined with multipoint nonlinear regression calibration based on intermittent sphygmomanometry may be an alternative to volume clamp devices.

Sleep apnea is one of the most common sleep disorders. Here, patients suffer from multiple breathing pauses longer than 10 s during the night which are referred to as apneas. The standard method for the diagnosis of sleep apnea is the attended cardiorespiratory polysomnography (PSG). However, this method is expensive and the extensive recording equipment can have a significant impact on sleep quality falsifying the results. To overcome these problems, a comfortable and novel system for sleep monitoring based on the recording of tracheal sounds and movement data is developed. For apnea detection, a unique signal processing method utilizing both signals is introduced. Additionally, an algorithm for extracting the heart rate from body sounds is developed. For validation, ten subjects underwent a full-night PSG testing, using the developed sleep monitor in concurrence. Considering polysomnography as gold standard the developed instrumentation reached a sensitivity of 92.8% and a specificity of 99.7% for apnea detection. Heart rate measured with the proposed method was strongly correlated with heart rate derived from conventional ECG (r 2 = 0.8164). No significant signal losses are reported during the study. In conclusion, we demonstrate a novel approach to reliably and noninvasively detect both apneas and heart rate during sleep. [ABSTRACT FROM AUTHOR]