S. Reisman

The effect of ventilation on spectral analysis of heart rate and blood pressure variability during exercise.

Heart rate variability (HRV) and systolic blood pressure variability (BPV) during incremental exercise at 50, 75, and 100% of previously determined ventilatory threshold (VT) were compared to that of resting controlled breathing (CB) in 12 healthy subjects. CB was matched with exercise-associated respiratory rate, tidal volume, and end-tidal CO(2) for all stages of exercise. Power in the low frequency (LF, 0.04-0.15 Hz) and high frequency (HF, >0.15-0.4 Hz) for HRV and BPV were calculated, using time-frequency domain analysis, from beat-to-beat ECG and non-invasive radial artery blood pressure, respectively. During CB absolute and normalized power in the LF and HF of HRV and BPV were not significantly changed from baseline to maximal breathing. Conversely, during exercise HRV, LF and HF power significantly decreased from baseline to 100% VT while BPV, LF and HF power significantly increased for the same period. These findings suggest that the increases in ventilation associated with incremental exercise do not significantly affect spectral analysis of cardiovascular autonomic modulation in healthy subjects.

Measurement of physiological stress

In this tutorial paper, the methods presently used for measuring the degree of stress and relaxation in human physiology are discussed. Measurements include heart rate variability, respiration, blood levels of substance such as cortisol and catecholamine levels, EEG effects and the change in peripheral blood flow. Examples of methods presently used in the authors laboratory are described.

The Detection of Auditory Evoked Responses Using a Matched Filter

A method has been developed to detect auditory brainstem evoked responses (ABRs) using a minimum amount of computer averaging. The method employs a matched filter to detect the ABR buried in the EEG. The matched filter system can also be used to predict wave V latency, which is useful in testing for hearing loss. By using a matched filter derived from an ABR obtained at a high-stimulus level, it is possible to calculate wave V latency at lower intensity levels much faster. Excellent correlation is seen between wave V latencies calculated in this manner, and those obtained after significant amounts of averaging. Because of this, the matched filter system can reduce the amount of time required for a hearing loss test from 20¿30 min to approximately 5¿10 min with no significant degradation in results.

Respiration response curve analysis of heart rate variability

A noninvasive study was conducted on intact awake humans to characterize the dynamic response of the heart to the vagus during slow-, comfortable-, and fast-paced respiration (8, 12, and 18 breaths/min), under both sitting and standing conditions. The respiration response curve (RRC) of respiration-associated vagal effects on the heart was estimated, and characteristics of entrainment and frequency dependence on respiration were demonstrated. It was shown that the degree of entrainment and magnitude of phase resetting decrease with increase of pacing rate from 8 to 18 breaths/min. Further, the RRC was examined by overlapping equivalent phase shifts in different respiration cycles. This examination of the RRC can help one not only to find the common pattern underlying the RRC during different respiration cycles but also to perceive its variation related to degree of entrainment.

Voice activated wheelchair controller

The Voice Activated Wheelchair Controller (VAWC) project was designed to develop a feasibility model for activating a wheelchair using a low-cost speech recognition system. A microcontroller was programmed to provide user control over each command, as well as to prevent voice commands from being issued accidentally.

Time frequency analysis of the electromyogram during fatigue

Spectral parameters obtained from the surface electromyogram (EMG) signal have been used as indicators of fatigue during a sustained contraction. A new technique, time frequency analysis, was applied to the EMG signal. This technique generates a continuous representation of the changing spectrum of the signal through time. Three types of time frequency distributions were applied to the EMG signal. As predicted, differences existed between the distributions. The amplitude differential from the first time slice of the distribution to the last was the smallest for the short time Fourier transform. The Wigner-Ville distribution was spread out across the most frequencies. Walls appeared in the Choi-Williams distribution, but otherwise it was the most compressed. All the distributions displayed the expected spectral compression; however, more work is necessary to clarify the results.<<ETX>>

COPD severity classification using principal component and cluster analysis on HRV parameters

The application of principal component analysis and cluster analysis (PCA-CA) using heart rate variability (HRV) parameters to identify the most severe chronic obstructive pulmonary disease (COPD) subjects in a mixture of normal and COPD population is discussed. These parameters were obtained from real physiological data and cross-spectral analysis (i.e. the coherence and partial coherence between heart rate, blood pressure and respiration signals). Results demonstrated that these two groups could be differentiated with greater than 99.0% accuracy. Furthermore, differences on the same HRV parameters between all four severity levels of COPD subjects were also investigated. These groups were differentiated with over 88.0% accuracy. In analyzing the studied data of the COPD population, the technique correctly characterized 8.5% of COPD group as severe COPD. It was concluded that the PCA-CA technique identified the combination of parameters that can classify disease severity (COPD) as well as differences between normal and COPD subjects in a mixed population. The PCA-CA technique could perhaps also be used to classify other diseases non-invasively.

Wavelet representation comparison for heart rate variability analysis

Wavelet time-frequency representation has become one of the most useful tools for research today. This paper presents a comparison of three different wavelets used for heart rate variability (HRV) studies. It is an attempt to reveal some underlying differences to readers about the wavelet representations. Topics introduced include the time-frequency plots obtained by using the Morlet, Daubechies 4 and Haar wavelets on the interpolated interbeat interval signal (IIBI) derived from the electrocardiogram (ECG) of a subject at rest breathing at 16 breaths per minute.

Measurement of the electroencephalogram (EEG) coherence in group meditation

Electrical activity in the human body was investigated using EEG measurement while subjects remained with eyes open, eyes closed and in a meditation state. Careful analysis of the EEG data showed the presence of coherence in dual EEG channels and this measure was used to quantify the meditation state. The performed measurements showed high coherence around 10 Hz in individual meditating subjects. When these measurements extended to group meditation of two subjects, it was observed that coherence spectra spread significantly to other frequencies.

Adaptive time-frequency analysis of autonomic nervous system

Spectral analysis of heart rate variability (HRV) provides a noninvasive estimate of sympathetic and parasympathetic influences on heart rate. The Time-Frequency analysis was utilized to expand the concept of spectral analysis of HRV to describe changes in vagal tone as a function of time. A new adaptive methodology is now proposed to uncover the region of true parasympathetic activity. It is known that parasympathetic activity is highly correlated with the respiration frequency. This technique traces the respiration frequency and extracts the corresponding parasympathetic activity from the HRV signal by adaptive filtering.