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The second heart sound ($2) is triggered by an aortic valve closure as a result of the ventricular-arterial interaction of the cardiovascular system. The objective of this paper is to investigate the timing of $2 in response to the changes in hemodynamic parameters and its relation to aortic blood pressure (BP). An improved model of the left ventricular-arterial interaction was proposed based on the combination of the newly established pressure source model of the ventricle and the nonlinear pressure-dependent compliance model of the arterial system. The time delay from the onset of left ventricular pressure rise to the onset of $2 (R[S.sub.2]) was used to measure the timing of $2. The results revealed that RS2 bears a strong negative correlation with both systolic blood pressure and diastolic blood pressure under the effect of changing peripheral resistance, heart rate, and contractility. The results were further validated by a series of measurements of 16 normal subjects submitted to dynamic exercise. This study helps understand the relationship between the timing of $2 and aortic BP under various physiological and pathological conditions. Index Terms--Cardiovascular modeling, heart-arterial interaction, heart sounds, model simulation.

Pulse transit time (PTT) has been widely used for noninvasive examination of the arterial viscoelastic properties, such as elasticity, compliance, and stiffness of the vessel walls. PTT is usually determined as the time interval between the peak of the electrocardiogram R wave and the foot of the photoplethysmogram (PPG). However, it was observed that the PPG is affected by the applied contact force between the photoplethysmographic sensor and the measurement site, e.g., finger. In this study, the nonlinear biomechanical properties of the finger arterial wall were considered when investigating the changes in PTT with varying contact force. Emphasis was placed on the changes in the shape of the arterial wall pressure-volume curve. The simulation results indicated that at positive transmural pressure, PTT increased with the applied contact force, reaching the maximum at zero transmural pressure and remaining at a constant level at negative transmural pressure. The theoretical analysis was further verified by the experiments carried out on thirty young subjects and six elderly subjects using twelve discrete levels of contact force. Index Terms--Contact force, photoplethysmogram, pulse transit time.

Cochlear implants (CIs) restore partial hearing to people with severe to profound sensorineural deafness; but there is still a marked performance gap in speech recognition between those who have received cochlear implant and people with a normal hearing capability. One of the factors that may lead to this performance gap is the inadequate signal processing method used in CIs. This paper investigates the application of an improved signal processing method called bionic wavelet transform (BWT). This method is based upon the auditory model and allows for signal processing. Comparing the neural network simulations on the same experimental materials processed by wavelet transform (WT) and BWT, the application of BWT to speech signal processing in CI has a number of advantages, including: improvement in recognition rates for both consonants and vowels, reduction of the number of required channels, reduction of the average stimulation duration for words, and high noise tolerance. Consonant recognition results in 15 normal hearing subjects show that the BWT produces significantly better performance than the WT (t = -4.36276, p = 0.00065). The BWT has great potential to reduce the performance gap between CI listeners and people with a normal hearing capability in the future. Index Terms--Bionic wavelet transform, cochlear implants, neural networks, speech signal processing.

In this paper, transient-evoked otoacoustic emissions (TEOAE's) are synthesized by an active auditory model, and decomposed by continuous wavelet transform (CWT) to study the frequency-latency relationship and the generation of TEOAE signals. The controlled voltage sources that relate to the mobile mechanism of the outer hair cells (OHC's) are proposed to serve as the generation sources of TEOAE signals. The state-variable method is adopted to calculate the auditory model. The mother wavelet used in CWT is selected on basis of the model. The results of this study show that the simulated TEOAE signal is similar to the clinically detected ones not only in the time-domain waveform, but also in the frequency-latency relationship. It seems to be clear that the generation of TEOAE signals is related to the same active mechanism as the cochlear sharp frequency selectivity. Index Terms - Auditory system, otoacoustic emissions, transient-evoked otoacoustic emissions (TEOAE's), wavelet transform.

This paper proposes a noninvasive method to diagnose chondromalacia patella at its early stages by recording knee vibration signals (also known as vibroarthrographic or VAG signals) over the mid-patella during normal movement. An adaptive segmentation method was developed to segment the nonstationary VAG signals. The least squares modeling method was used to reduce the number of data samples to a few model parameters. Model parameters along with a few clinical parameters and a signal variability parameter were then used as discriminant features for screening VAG signals by applying logistic and discriminant algorithms. The system was trained using ten normal and eight abnormal signals. It correctly screened a separate test set often normal and eight abnormal signals except for one normal signal. The proposed method should find use as an alternative technique for diagnosis of knee joint pathology or as a test before arthroscopy or major knee surgery.

Vibromyographic (VMG) signals, which are low-frequency vibration signals generated during muscle contraction, were studied in comparison with electromyographic (EMG) signals recorded simultaneously during isometric contraction of the human quadriceps muscles. The comparison was accomplished by evaluating the averaged root mean squared (rms) value, mean frequency (MF), and peak frequency (PF) of the VMG and EMG signals for four muscle contraction levels at joint angles of 30 degrees, 60 degrees, and 90 degrees. The four contraction levels, namely 20, 40, 60, and 80% of maximum voluntary contraction (MVC), were estimated and controlled by the torque readings of a Cybex II dynamometer. It was found that the VMG and EMG under the same conditions on the same muscle group are in general equally sensitive to the levels of muscle contraction. Results show that the rms value of the VMG signal increases linearly, in a manner similar to the EMG rms/%MVC relationship, with increasing muscle contraction levels. Furthermore, the study indicates that the averaged MF (6-24 Hz) and PF (9-19 Hz) of the VMG signals are much lower than the MF (75-109 Hz) and PF (40-80 Hz) of the EMG signals. The slopes of MF/%MVC curves for the VMG and EMG are approximately the same for 60 degrees and 90 degrees joint angles (equivalent to 3.1 Hz per 20% MVC for VMG and equivalent to 2.6 Hz per 20% MVC for EMG). This slope similarity means that the rms/%MVC and MF/%MVC relationships of the VMG signal, like those of the EMG, may reflect muscle activation patterns, while the difference in frequency content between the VMG and the EMG reflects the morphological differences between the mechanical and electrical responses to muscle activation. It was also noted that the VMG signal, like the EMG signal, exhibits a feature of joint angle dependence. Results of all these studies show that the VMG, as a direct mechanical index of muscular contraction, has potential as a noninvasive tool for studying the mechanical behavior of active skeletal muscles.

Clinical methods used at present for the diagnosis of cartilage pathology in the knee are invasive in nature, and carry some risks. There exists a need for the development of a safe, objective, noninvasive method for early detection, localization, and quantification of cartilage pathology in the knee. This paper investigates the possibility of developing such a method based on an analysis of vibrations produced by joint surfaces rubbing against one another during normal movement. In particular, the method of modeling by linear prediction is used for adaptive segmentation and parameterization of knee vibration signals. Dominant poles are extracted from the model system function for each segment based on their energy contributions and bandwidths. These dominant poles represent the dominant features of the signal segments in the spectral domain. Two-dimensional feature vectors are then constructed using the first dominant pole and the ratio of power in the 40-120 Hz band to the total power of the segment. The potential use of this method to distinguish between vibrations produced by normal volunteers and patients known to have cartilage pathology (chondromalacia) is discussed.

Analysis of vibration signals emitted by the knee joint has the potential for the development of a noninvasive procedure for the diagnosis and monitoring of knee pathology. In order to obtain as much information as possible from the power density spectrum of the knee vibration signal, it is necessary to identify the physiological factors (or physiologically relevant parameters) that shape the spectrum. This paper presents a mathematical model for knee vibration signals, in particular the physiological patello-femoral pulse (PFP) train produced by slow knee movement. It demonstrates through the mathematical model that the repetition rate of the physiological PFP train introduces repeated peaks in the power spectrum, and that it affects the spectrum mainly at low frequencies. The theoretical results also show that the spectral peaks at multiples of the PFP repetition rate become more evident when the variance of the interpulse interval (IPI) is small, and that these spectral peaks shift toward higher frequencies with increasing PFP repetition rates. To evaluate the mathematical model, a simulation algorithm was developed, which generates PFP signals with adjustable repetition rate and IPI variance. Signals generated by simulation were seen to possess representative spectral characteristics typically observed in physiological PFP signals. This simulation procedure allows an interactive examination of several factors which affect the PFP train spectrum. Finally, in vivo measurements of physiological PFP signals of normal volunteers are presented. Results of simulations and analysis of signals recorded from human subjects support the mathematical model's prediction that the IPI statistics play a very significant role in determining the low-end power spectrum of the physiological PFP signal. Evidence is presented to show that ignoring these IPI statistics will affect the interpretation of the spectrum.

In this paper, a new adaptive wavelet transform, named bionic wavelet transform (BWT), is developed based on a model of the active auditory system. The most distinguishing characteristic of BWT is that its resolution in the time-frequency domain can be adaptively adjusted not only by the signal frequency but also by the signal instantaneous amplitude and its first-order differential. The automatically adjusted resolution, even in a fixed frequency along the time-axis, is achieved by introducing the active control of the auditory system into the wavelet transform (WT). Other properties of BWT include that: 1) BWT is a nonlinear transform that has high sensitivity and frequency selectivity: 2) BWT represents the signal with a concentrated energy distribution; and 3) the inverse BWT can reconstruct the original signal from its time-frequency representation. In order to compare these three properties between BWT and WT, experiments were conducted on both constructed signals and real speech signals. The results show that BWT performs better than WT in these three aspects, and that BWT is appropriate for speech signal processing, especially for cochlear implants. Index Terms--Bionic wavelet transform, cochlear implants, otoacoustic emissions, time-frequency analysis.

Pulse transit time (PTT) is a cardiovascular parameter of emerging interest due to its potential to estimate blood pressure (BP) continuously and without a cuff. Both linear and nonlinear equations have been used in the estimation of BP based on PTT. This study, however, demonstrates that there is a hysteresis phenomenon between BP and PTT during and after dynamic exercise. A total of 46 subjects including 16 healthy subjects, 13 subjects with one or more cardiovascular risk factors, and 17 patients with cardiovascular disease underwent graded exercise stress test. PTT was measured from electrocardiogram and photoplethysmogram of the left index finger of the subject, i.e., a pathway that includes predominately aorta, brachial, and radial arteries. The results of this study showed that, for the same systolic BP (SBP), PTT measured during exercise was significantly larger than PTT measured during recovery for all subject groups. This hysteresis was further quantified as both normalized area bounded by the SBP–PTT relationship (AreaN) and SBP difference at PTT during peak exercise plus 20 ms (ΔSBP20). Significant attenuation of both AreaN (p < \0.05) and ΔSBP20 ( p < \0.01) is observed in cardiovascular patients compared with healthy subjects, independent of resting BP. Since the SBP–PTT relationship are determined by the mechanical properties of arterial wall, which is predominately mediated by the sympathetic nervous system through altered vascular smooth muscle (VSM) tone during exercise, results of this study are consistent with the previous findings of autonomic nervous dysfunction in cardiovascular patients. We further conclude that VSM tone has a nonnegligible influence on the BP–PTT relationship and thus should be considered in the PTT-based BP estimation. [ABSTRACT FROM PUBLISHER]

The second heart sound (S2) is triggered by an aortic valve closure as a result of the ventricular-arterial interaction of the cardiovascular system. The objective of this paper is to investigate the timing of S2 in response to the changes in hemodynamic parameters and its relation to aortic blood pressure (BP). An improved model of the left ventricular-arterial interaction was proposed based on the combination of the newly established pressure source model of the ventricle and the nonlinear pressure-dependent compliance model of the arterial system. The time delay from the onset of left ventricular pressure rise to the onset of S2 (RS2) was used to measure the timing of S2. The results revealed that RS2 bears a strong negative correlation with both systolic blood pressure and diastolic blood pressure under the effect of changing peripheral resistance, heart rate, and contractility. The results were further validated by a series of measurements of 16 normal subjects submitted to dynamic exercise. This study helps understand the relationship between the timing of S2 and aortic BP under various physiological and pathological conditions. [ABSTRACT FROM AUTHOR]

Pulse transit time (PTT) has been widely used for non- invasive examination of the arterial viscoelastic properties, such as elasticity, compliance, and stiffness of the vessel walls. PTT is usually determined as the time interval between the peak of the electrocardiogram R wave and the foot of the photoplethysmogram (PPG). However, it was observed that the PPG is affected by the applied contact force between the photoplethysmographic sensor and the measurement site, e.g., finger. In this study, the nonlinear biomechanical properties of the finger arterial wall were considered when investigating the changes in PTT with varying contact force. Emphasis was placed on the changes in the shape of the arterial wall pressure-volume curve. The simulation results indicated that at positive transmural pressure, PTT increased with the applied contact force, reaching the maximum at zero transmural pressure and remaining at a constant level at negative transmural pressure. The theoretical analysis was further verified by the experiments carried out on thirty young subjects and six elderly subjects using twelve discrete levels of contact force. [ABSTRACT FROM AUTHOR]

Cochlear implants (CIs) restore partial hearing to people with severe to profound sensorineural deafness; but there is still a marked performance gap in speech recognition between those who have received cochlear implant and people with a normal hearing capability. One of the factors that may lead to this performance gap is the inadequate signal processing method used in CIs. This paper investigates the application of an improved signalprocessing method called bionic wavelet transform (BWT). This method is based upon the auditory model and allows for signal processing. Comparing the neural network simulations on the same experimental materials processed by wavelet transform (WT) and BWT, the application of BWT to speech signal processing in CI has a number of advantages, including: improvement in recognition rates for both consonants and vowels, reduction of the number of required channels, reduction of the average stimulation duration for words, and high noise tolerance. Consonant recognition results in 15 normal hearing subjects show that the BWT prOduces significantly better performance than the WT (t = -4.36276, p = 0.00065). The BWT has great potential to reduce the performance gap between CI listeners and people with a normal hearing capability in the future. [ABSTRACT FROM AUTHOR]

Deals with a study which developed bionic wavelet transform (BWT), an adaptive wavelet transform based on a model of the active auditory system. Properties of BWT; Ear model based on otoacoustic emissions; Definition of BWT.

Presents information on a study which examined the frequency-latency relationship and the generation of transient-evoked otoacoustic emission (TEOAE) signals. Introduction of an active auditory model used to synthesize TEOAE; Decomposition of TEOAE by continuous wavelet transform; Experimental methods and results; Discussions.