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Purpose: Prosody perception is an essential component of speech communication and social interaction through which both linguistic and emotional information are conveyed. Considering the importance of the auditory system in processing prosody-related acoustic features, the aim of this review article is to review the effects of hearing impairment on prosody perception in children and adults. It also assesses the performance of hearing assistive devices in restoring prosodic perception. Method: Following a comprehensive online database search, two lines of inquiry were targeted. The first summarizes recent attempts toward determining the effects of hearing loss and interacting factors such as age and cognitive resources on prosody perception. The second analyzes studies reporting beneficial or detrimental impacts of hearing aids, cochlear implants, and bimodal stimulation on prosodic abilities in people with hearing loss. Results: The reviewed studies indicate that hearing-impaired individuals vary widely in perceiving affective and linguistic prosody, depending on factors such as hearing loss severity, chronological age, and cognitive status. In addition, most of the emerging information points to limitations of hearing assistive devices in processing and transmitting the acoustic features of prosody. Conclusions: The existing literature is incomplete in several respects, including the lack of a consensus on how and to what extent hearing prostheses affect prosody perception, especially the linguistic function of prosody, and a gap in assessing prosody under challenging listening situations such as noise. This review article proposes directions that future research could follow to provide a better understanding of prosody processing in those with hearing impairment, which may help health care professionals and designers of assistive technology to develop innovative diagnostic and rehabilitation tools.

Traditional cuff-based sphygmomanometers for measuring blood pressure can be uncomfortable and particularly unsuitable to use during sleep. A proposed alternative method uses dynamic changes in the pulse waveform over short intervals and replaces calibration with information from photoplethysmogram (PPG) morphology to provide a calibration-free approach using a single sensor. Results from 30 patients show a high correlation of 73.64% for systolic blood pressure (SBP) and 77.72% for diastolic blood pressure (DBP) between blood pressure estimated with the PPG morphology features and the calibration method. This suggests that the PPG morphology features could replace the calibration stage for a calibration-free method with similar accuracy. Applying the proposed methodology on 200 patients and testing on 25 new patients resulted in a mean error (ME) of −0.31 mmHg, a standard deviation of error (SDE) of 4.89 mmHg, a mean absolute error (MAE) of 3.32 mmHg for DBP and an ME of −4.02 mmHg, an SDE of 10.40 mmHg, and an MAE of 7.41 mmHg for SBP. These results support the potential for using a PPG signal for calibration-free cuffless blood pressure estimation and improving accuracy by adding information from cardiovascular dynamics to different methods in the cuffless blood pressure monitoring field. [ABSTRACT FROM AUTHOR]

Purpose: Prosody perception is an essential component of speech communication and social interaction through which both linguistic and emotional information are conveyed. Considering the importance of the auditory system in processing prosody-related acoustic features, the aim of this review article is to review the effects of hearing impairment on prosody perception in children and adults. It also assesses the performance of hearing assistive devices in restoring prosodic perception. Method: Following a comprehensive online database search, two lines of inquiry were targeted. The first summarizes recent attempts toward determining the effects of hearing loss and interacting factors such as age and cognitive resources on prosody perception. The second analyzes studies reporting beneficial or detrimental impacts of hearing aids, cochlear implants, and bimodal stimulation on prosodic abilities in people with hearing loss. Results: The reviewed studies indicate that hearing-impaired individuals vary widely in perceiving affective and linguistic prosody, depending on factors such as hearing loss severity, chronological age, and cognitive status. In addition, most of the emerging information points to limitations of hearing assistive devices in processing and transmitting the acoustic features of prosody. Conclusions: The existing literature is incomplete in several respects, including the lack of a consensus on how and to what extent hearing prostheses affect prosody perception, especially the linguistic function of prosody, and a gap in assessing prosody under challenging listening situations such as noise. This review article proposes directions that future research could follow to provide a better understanding of prosody processing in those with hearing impairment, which may help health care professionals and designers of assistive technology to develop innovative diagnostic and rehabilitation tools. [ABSTRACT FROM AUTHOR]

An important means for preventing and managing cardiovascular disease is the non-invasive estimation of blood pressure. There is particular interest in developing approaches that provide accurate cuffless and continuous estimation of this important vital sign. This paper proposes a method that uses dynamic changes of the pulse waveform over short time intervals and calibrates the system based on a mathematical model that relates reflective PTT (R-PTT) to blood pressure. An advantage of the method is that it only requires collecting the photoplethysmogram (PPG) using one optical sensor, in addition to initial non-invasive measurements of blood pressure that are used for calibration. This method was applied to data from 30 patients, resulting in a mean error (ME) of 0.59 mmHg, a standard deviation of error (SDE) of 7.07 mmHg, and a mean absolute error (MAE) of 4.92 mmHg for diastolic blood pressure (DBP) and an ME of 2.52 mmHg, an SDE of 12.15 mmHg, and an MAE of 8.89 mmHg for systolic blood pressure (SBP). These results demonstrate the possibility of using the PPG signal for the cuffless continuous estimation of blood pressure based on the analysis of calibrated changes in cardiovascular dynamics, possibly in conjunction with other methods that are currently being researched. [ABSTRACT FROM AUTHOR]

Speech production while wearing hearing protectors poses significant challenges due to their occlusion effect and disruption of the Lombard effect. An experiment was conducted with 24 individuals as they read a list of 12 sentences in open ears and while wearing an earmuff in quiet and in four different noises [pink, International Female Fluctuating Masker (IFFM), speech-spectrum noise (SSnoise), and helicopter] at two levels (70 and 85 dBA). An acoustic manikin, fitted or not with an identical protector, served as the target listener. In noise, speech levels decreased when the talkers wore the earmuff but increased when the target listener was fitted with the earmuff. When the earmuff was used by both the talkers and target listener, speech levels were lower by 3–6 dB at the higher noise level compared to when they were both open ears. Speech levels were typically lower, but extended speech intelligibility index estimates were consistently higher, in fluctuating (IFFM, helicopter) than in continuous noises (pink, SSnoise). Talkers' pitch frequency and voice spectrum measurements followed very closely the changes in speech levels, showing no evidence of compensatory voice modifications. Implications of the lower talker speech levels when wearing hearing protectors are discussed in terms of protector selection, training, and individuals with hearing loss. [ABSTRACT FROM AUTHOR]

We investigated whether pitch-synchronous neural activity could be recorded in humans, with a natural vowel and a vowel in which the fundamental frequency was suppressed. Small variations of speech periodicity were detected in the evoked responses using a fine structure spectrograph (FSS). A significant response (P [much less than] 0.001) was measured in all seven normal subjects even when the fundamental frequency was suppressed, and it very accurately tracked the acoustic pitch contour (normalized mean absolute error < 0.57%). Small variations in speech periodicity, which humans can detect, are therefore available to the perceptual system as pitch-synchronous neural firing. These findings suggest that the measurement of pitch-evoked responses may be a viable tool for objective speech audiometry. Index Terms--Bioelectric potentials, biomedical signal processing, speech processing, time-frequency analysis.

Researchers have investigated the impact of congestive heart failure (CHF) on the rhythmic control of muscle sympathetic nerve activity (MSNA). This involved characterizing oscillations in MSNA in the frequency domain in health men and men with CHF. These were related to blood pressure (BP), breathing frequency and heart rate (HR). It was possible to identify spectral power in the MSNA signal which is similar in magnitude in people with normal and impaired ventricular functions in relation to total power and the relative proportion of harmonic and nonharmonic elements.

We propose the binaural auditory system as a candidate neural system that may be disrupted by exposure to relatively weak LF magnetic fields. Extracellular currents, induced by time-varying magnetic fields, may change the timing of action potentials in the auditory nerve, thereby disrupting sound localization when interaural time differences are very small. Three subjects were exposed to a 1000 Hz magnetic field--with a maximum rate of change of 2.3 T/s at the location of the cochlea--while presenting two identical 1000 Hz tones randomly delayed to the left or right ear by less than 10 ps. The subjects were asked whether the signal was perceived to be displaced to the left or right side of midline. After a total of over 20,000 trials, conducted at different phase angles between the field signal and the tones, there was no clear evidence for a consistent change in performance when the magnetic field was present. This, however, does not rule out an effect at other combinations of magnetic and acoustic frequencies.

In this brief review, we will introduce arterial stiffness, describe how it is currently measured and point to new developments that might lead towards arterial stiffness estimation outside of specialized clinics in the future. In almost all methods for measuring arterial stiffness, the arterial pulse plays an important role. Therefore, new developments are related to novel non-invasive sensors for acquiring the arterial pulse, simulation and modeling of the arterial pulse waves, parameter estimation of the stiffness parameters through physical models of the arterial pulse and machine learning methods for predicting the arterial stiffness. [ABSTRACT FROM AUTHOR]

Measurement of noise exposure from communication headsets is challenging due to the need for specialized equipment, methods, and training. Canadian standard Z107.56-13 [(2013). Measurement of Noise Exposure (Canadian Standards Association, Mississauga, Canada)] introduced a calculation procedure to promote a simpler method that stakeholders in hearing loss prevention could readily apply using widely accessible sound level equipment. The original procedure specified a fixed signal-to-noise ratio (SNR) of 15 dB above the protected background noise when estimating the speech listening level through the headset communication channel. The relationship between background noise level, noise type, headset noise reduction (NR), and speech listening level is revisited in this study. In a noise simulation room, 24 participants were asked to adjust the headset volume while listening to speech and executing a visual reaction task. Results indicate that the growth in speech listening levels with noise is not adequately represented by a fixed SNR, and that one-sided listening increases speech levels by about 5–7 dB in quiet and in noise compared to two-sided listening. Moreover, use of an octave-band procedure with derating to estimate headset NR best captured the speech listening level data. A revised calculation procedure based on linear regression modeling is described with parameters adjusted separately for one-sided and two-sided headsets. [ABSTRACT FROM AUTHOR]

This study introduces an improved method to investigate the effects of reverberation using the speech-evoked auditory brainstem response (ABR) that more realistically captures the influence of self- and overlap-masking induced by room reverberation. Speech-evoked ABR was measured under three acoustic scenarios: anechoic, mild reverberation with dominance of early reflections, and severe reverberation with dominance of late reverberation. Responses were significantly weaker and had longer latencies with severe reverberation relative to anechoic and mild reverberation. Although larger responses and shorter latencies were observed with mild reverberation than anechoic, possibly due to early reflections, these reached significance in only one of six ABR response measures. [ABSTRACT FROM AUTHOR]

Noninvasive blood pressure (BP) measurement is an important tool for managing hypertension and cardiovascular disease. However, automated noninvasive BP measurement devices, which are usually based on the oscillometric method, do not always provide accurate estimation of BP. It has been found that change in arterial stiffness (AS) is an underlying mechanism of disagreement between an oscillometric BP monitor and a sphygmomanometer. This problem is addressed by incorporating parameters related to AS in the algorithm for BP measurement. Pulse transit time (PTT) is first used to estimate AS parameters, which are fixed into a model of the oscillometric envelope. This model can then be used to perform curve fitting to the measured signal using only four parameters: systolic BP, diastolic BP, mean BP, and lumen area at zero transmural pressure. The proposed technique is independent of the experimentally determined characteristic ratios that are commonly used in existing oscillometric methods. The accuracy of the proposed technique was evaluated by comparing with the same model without incorporation of AS, and with reference BP device measurements. The new method achieved standard deviation of error less than 8 mmHg and mean error less than 5 mmHg. The results show consistency with ANSI/AAMI SP-10 standard for noninvasive BP measurement techniques. [ABSTRACT FROM AUTHOR]

Accuracy of blood pressure (BP) measurement is a challenging issue in oscillometry. Most of the automated noninvasive BP monitors estimate BP from envelope of the measured oscillometric pulses. The peak and the trough of the oscillometric pulses are very sensitive to noise caused by breathing, heart-rate variability, motion artifacts, muscle contraction, and environmental noise. Therefore, accuracy of the estimated BP based on the oscillometric waveform envelopes is not reliable in some cases. Recently, employing a modeling approach to estimate BP, we obtained the accurate results for a set of healthy subjects. The method is based on the lumen area oscillations model and estimates BP by comparing the actual and corresponding simulated waveforms. The method’s accuracy worsened when we tested it on a broader range of healthy subjects, while a significant drop was observed when the method was used for patients with chronic cardiovascular diseases. The work presented in this paper represents an improved version of our previous approach. We tested the proposed method on both healthy subjects and patients with chronic cardiovascular diseases, and compared the results to two popular BP estimation algorithms: maximum amplitude algorithm and maximum/minimum slope algorithm. We observed up to 56.7% and 57.3% improvements in mean absolute error, 98.9% and 64.4% improvements in mean error, 50% and 59% improvements in standard deviation of errors, and up to 57.6% and 55.8% in measurement uncertainty for the estimated systolic and diastolic pressures, respectively. [ABSTRACT FROM AUTHOR]

Objectives: The use of remote sensing technologies such as radar is gaining popularity as a technique for contactless detection of physiological signals and analysis of human motion. This paper presents a methodology for classifying different events in a collection of phase modulated continuous wave radar returns. The primary application of interest is to monitor inmates where the presence of human vital signs amidst different, interferences needs to be identified. Methods: A comprehensive set of features is derived through time and frequency domain analyses of the radar returns. The Bhattacharyya distance is used to preselect the features with highest class separability as the possible candidate features for use in the classification process. The uncorrelated linear discriminant analysis is performed to decorrelate, denoise, and reduce the dimension of the candidate feature set. Linear and quadratic Bayesian classifiers are designed to distinguish breathing, different human motions, and nonhuman motions. The performance of these classifiers is evaluated on a pilot dataset of radar returns that contained different events including breathing, stopped breathing, simple human motions, and movement of fan and water. Results: Our proposed pattern classification system achieved accuracies of up to $93$% in stationary subject detection, $90$% in stop-breathing detection, and $86$% in interference detection. Conclusion: Our proposed radar pattern recognition system was able to accurately distinguish the predefined events amidst interferences. Significance: Besides inmate monitoring and suicide attempt detection, this paper can be extended to other radar applications such as home-based monitoring of elderly people, apnea detection, and home occupancy detection. [ABSTRACT FROM AUTHOR]

Blood pressure (BP) readings in oscillometry are very sensitive to the posture of the body, arm, and body movements during the BP measurements, so measuring conditions are the first important factors for trusted BP readings. Next is the BP estimation algorithm, which is responsible to convert the cuff deflation curve (CDC) pressure signal to accurate BP readings. With proper measuring conditions and an accurate BP estimation algorithm one can expect trusted BP readings. Trustworthiness of the BP readings is still a challenging issue in automated oscillometric BP monitors, and patients need to see the doctor for trusted measurements. To this end, we have proposed a novel method called a Dynamic Threshold Algorithm (DTA) that evaluates trustworthiness of the BP readings immediately after the BP is estimated, such that the patient can decide whether to repeat the measurement or not. DTA employs the heart rate (HR) of the subject and determines a specific threshold (TR). TR is used to determine maximum and minimum limits for trustable pressures (SBP2, DBP2) of a given subject. The limits are called trusted boundaries (TB). Trusted boundaries are compared with the estimated systolic blood pressure (SBP) and diastolic blood pressure (DBP) to determine trustworthiness of the measured BP. BP readings are trusted if estimated SBP and DBP are inside the TB and untrusted or labeled an outlier if otherwise. In this research, DTA is applied on three different data- sets of healthy and sick subjects, outliers are determined and removed from the datasets, and remaining recordings are validated against references and compared with validated results of original datasets. According to observations, improvements were significant after outliers were removed from the datasets. [ABSTRACT FROM PUBLISHER]

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The measurement of noise exposure from communication headsets poses a methodological challenge. Although several standards describe methods for general noise measurements in occupational settings, these are not directly applicable to noise assessments under communication headsets. For measurements under occluded ears, specialized methods have been specified by the International Standards Organization (ISO 11904) such as the microphone in a real ear and manikin techniques. Simpler methods have also been proposed in some national standards such as the use of general purpose artificial ears and simulators in conjunction with single number corrections to convert measurements to the equivalent diffuse field. However, little is known about the measurement agreement between these various methods and the acoustic manikin technique. Twelve experts positioned circum-aural, supra-aural and insert communication headsets on four different measurement setups (Type 1, Type 2, Type 3.3 artificial ears, and acoustic manikin). Fit-refit measurements of four audio communication signals were taken under quiet laboratory conditions. Data were transformed into equivalent diffuse-field sound levels using third-octave procedures. Results indicate that the Type 1 artificial ear is not suited for the measurement of sound exposure under communication headsets, while Type 2 and Type 3.3 artificial ears are in good agreement with the acoustic manikin technique. Single number corrections were found to introduce a large measurement uncertainty, making the use of the third-octave transformation preferable. [ABSTRACT FROM AUTHOR]

Radar-based noncontact sensing of life sign signals is often used in safety and rescue missions during disasters such as earthquakes and avalanches and for home care applications. The radar returns obtained from a human target contain the breathing frequency along with its strong higher harmonics depending on the target’s posture. As a consequence, well understood, computationally efficient, and the most popular traditional FFT-based estimators that rely only on the strongest peak for estimates of breathing rates may be inaccurate. The paper proposes a solution for correcting the estimation errors of such single peak-based algorithms. The proposed method is based on using harmonically related comb filters over a set of all possible breathing frequencies. The method is tested on three subjects for different postures, for different distances between the radar and the subject, and for two different radar platforms: PN-UWB and phase modulated-CW (PM-CW) radars. Simplified algorithms more suitable for real-time implementation have also been proposed and compared using accuracy and computational complexity. The proposed breathing rate estimation algorithms provide a reduction of about 81% and 80% in the mean absolute error of breathing rates in comparison to the traditional FFT-based methods using strongest peak detection, for PN-UWB and PM-CW radars, respectively. [ABSTRACT FROM AUTHOR]

An accurate noninvasive estimation of mean arterial pressure (MAP) is of great importance in the evaluation of circulatory function and prognosis of some cardiovascular diseases. This paper proposes a novel oscillometric MAP estimation method based on the dependence of pulse transit time (PTT) on cuff pressure (CP). The PTT computed as the time interval between the electrocardiogram (ECG) R-peaks and the maximum slope points on the oscillometric pulses is mathematically modeled by considering the cuff-arm-artery system and the blood flow dynamics. It is then analytically shown that MAP can be approximated as the CP at which the PTT is maximum. Based on our theoretical findings, a new method of MAP estimation from simultaneous ECG and oscillometric blood pressure measurements is proposed. Our proposed method is validated with a pilot study in which 150 recordings from 10 subjects are analyzed. The reference MAP is computed from the systolic and diastolic pressures measured by the Food and Drug Administration-approved Omron HEM-790IT monitor using three different formulas given in the literature. The performance of our proposed method is compared with the maximum amplitude and zero-crossing methods in terms of mean error (ME), mean absolute error, and standard deviation of error (SDE). It is found that our proposed method achieves improvements of more than 20% in SDE compared with the maximum amplitude method and more than 50% in ME compared with the zero-crossing method. [ABSTRACT FROM PUBLISHER]

Sleep apnea is a common condition that poses serious health risks. Current state-of-the-art technology for diagnosing and assessing sleep apnea is obtrusive, expensive, and lacks integration/analysis of important cardiovascular and respiratory parameters. This paper evaluates a novel unobtrusive multiparameter sleep apnea monitor, namely, the Biopeak chest belt monitor, and describes a collection of associated algorithms for the detection of sleep apnea and assessment of the extent of the resulting physiological disturbance. The system uses dry electrodes to acquire electrocardiogram, respiratory, and stroke volume data and analyzes multiple physiological parameters from it. In a pilot investigation on eight healthy subjects simulating a total of 66 obstructive sleep apnea (OSA) events with Mueller maneuvers, the proposed system achieves an accuracy of 95.6%, a specificity of 97.2%, and a sensitivity of 93.8% for identifying these events. Moreover, the response of the simulated OSA events on the multiple physiological parameters conforms to earlier published work. We thus conclude that the proposed chest belt system has potential to be used for reliable sleep apnea detection and comprehensive evaluation of cardiovascular and respiratory parameters in sleep apnea. [ABSTRACT FROM PUBLISHER]

Oscillometry is a popular technique for automatic estimation of blood pressure (BP). However, most of the oscillometric algorithms rely on empirical coefficients for systolic and diastolic pressure evaluation that may differ in various patient populations, rendering the technique unreliable. A promising complementary technique for automatic estimation of BP, based on the dependence of pulse transit time (PTT) on cuff pressure (CP) (PTT–CP mapping), has been proposed in the literature. However, a theoretical grounding for this technique and a nonparametric BP estimation approach are still missing. In this paper, we propose a novel coefficient-free BP estimation method based on PTT–CP dependence. PTT is mathematically modeled as a function of arterial lumen area under the cuff. It is then analytically shown that PTT–CP mappings computed from various points on the arterial pulses can be used to directly estimate systolic, diastolic, and mean arterial pressure without empirical coefficients. Analytical results are cross-validated with a pilot investigation on ten healthy subjects where 150 simultaneous electrocardiogram and oscillometric BP recordings are analyzed. The results are encouraging whereby the mean absolute errors of the proposed method in estimating systolic and diastolic pressures are 5.31 and 4.51 mmHg, respectively, relative to the Food and Drug Administration approved Omron monitor. Our work thus shows promise toward providing robust and objective BP estimation in a variety of patients and monitoring situations. [ABSTRACT FROM PUBLISHER]

The measurement of sound exposure for individuals using communication headsets and headphones in the workplace imposes many technical challenges, and it has been difficult to integrate such measurements in national and international standards on occupational noise exposure. This paper reviews existing methods to measure sound exposure directly under listening devices, including the use of specialized acoustic manikins, artificial ears and real-ear procedures, and the associated field logistics and data analysis procedures. An alternative indirect calculation method is proposed that uses the main determinants of exposure as input parameters into the assessment, such as the external noise around the user, the attenuation of the device, and the user's listening signal-to-noise ratio. The advantages and disadvantages of the different methods are discussed. Together, they form the basis for a set of four measurement methods and one calculation method on assessing occupational sound exposure from headsets and headphones under consideration by a technical Working Group of the Canadian Standards Association [ABSTRACT FROM AUTHOR]

Although estimation of average blood pressure is commonly done with oscillometric measurements, confidence intervals (CIs) for systolic blood pressure (SBP) and diastolic blood pressure (DBP) are not usually estimated. This paper adopts bootstrap methodologies to build CI from a small sample set of measurements, which is a situation commonly encountered in practice. Three bootstrap methodologies, namely, nonparametric percentile bootstrap, standard bootstrap, and bias-corrected and accelerated bootstrap are investigated. A two-step methodology is proposed based on pseudomeasurements using bootstrap principles to first derive the pseudomaximum amplitudes and then the pseudoenvelopes (PEs). The SBP and DBP are estimated using the new relationships between mean cuff pressure and PE and then the CIs for such estimates are obtained. In order to reduce the amount of processing, a single-step methodology that directly derives PE using bootstrap principles is also presented. Application of the proposed methodology on an experimental data set of 85 patients with five sets of measurements for each patient has yielded a narrower CI than the currently available conventional methods such as Student's t-distribution method. [ABSTRACT FROM PUBLISHER]

In this paper, we present a novel feature-based neural network (NN) approach for estimation of blood pressure (BP) from wrist oscillometric measurements. Unlike previous methods that use the raw oscillometric waveform envelope (OMWE) as input to the NN, in this paper, we propose to use features extracted from the envelope. The OMWE is mathematically modeled as a sum of two Gaussian functions. The optimum parameters of this model are found by minimizing the least squares error between the model and the OMWE using the Levenberg–Marquardt algorithm and are used as features. Two separate feed-forward NNs (FFNNs) are then designed to estimate the systolic and diastolic BPs using these features. The FFNNs are trained using the resilient backpropagation learning algorithm and tested on a data set of BP measurements recorded from 85 subjects. The performance is then compared with that of the conventional maximum amplitude algorithm, adaptive neuro-fuzzy inference system, and already published NN-based methods. It is found that the proposed approach achieves lower values of mean absolute error and standard deviation of error in the estimation of BP. In addition, the proposed approach has the following advantages: lower complexity with respect to the design parameters, smaller training data set, and lower computational load. [ABSTRACT FROM PUBLISHER]

Breathing causes fluctuations in blood pressure and contributes to variations in blood pressure estimates. In order to reduce the variability in the blood pressure estimates induced by breathing, either the breathing signal should be removed from the oscillometric blood pressure signal, or its effects should be suppressed. This paper presents a hybrid method that combines homomorphic and adaptive signal processing techniques to extract the breathing signal from the oscillometric signal with or without a simultaneously recorded electrocardiogram (ECG). The quality of the extracted breathing signal and the depth of breathing are assessed using the reference breathing signals. The breathing signals extracted using the accompanying ECG signal were found to be superior in quality compared to the ones extracted from the oscillometric waveform. The blood pressure estimates were evaluated before and after the breathing suppression techniques were implemented. As a result of the breathing suppression, the fluctuation of the systolic and diastolic blood pressure estimates obtained from a database of 85 healthy subjects is reduced. [ABSTRACT FROM AUTHOR]

A filterbank-based algorithm for time-varying spectral analysis is proposed. The algorithm, which is an enhanced realization of the conventional spectrogram, consists of hundreds or thousands of highly overlapping wideband filter/detector stages, followed by a peak detector that probes the filter/detector outputs at very short time intervals. Analysis with synthetic modulated signals illustrates how the proposed method demodulates these signals. The resulting spectrogram-like display, referred to as a “fine structure spectrogram,” shows the fine structure of the modulations in substantially higher detail than is possible with conventional spectrograms. Error evaluation is performed as a function of various parameters of a single- and two-component synthetic modulated signal, and of parameters of the analysis system. In speech, the fine structure spectrogram can detect small frequency and amplitude modulations in the formants. It also appears to identify additional significant time-frequency components in speech that are not detected by other methods, making it potentially useful in speech processing applications. © 2005 Acoustical Society of America. [ABSTRACT FROM AUTHOR]

Oscillometry is the most common measurement method used in electronic blood pressure (BP) monitors. However, most of the existing oscillometric algorithms employ empirical ratios on the oscillometric waveform envelope (OMWE) to determine the systolic pressure (SP) and diastolic pressure (DP). As these algorithms do not consider the cardiovascular system parameters that may vary due to health conditions or age, the pressure estimates are not always reliable. In this paper, we develop a new mathematical model for the OMWE by incorporating an existing model of the cuff-arm-artery system. [ABSTRACT FROM PUBLISHER]

This paper introduces a novel approach to estimate the systolic and diastolic blood pressure ratios (SBPR and DBPR) based on the maximum amplitude algorithm (MAA) using a Gaussian mixture regression (GMR). The relevant features, which clearly discriminate the SBPR and DBPR according to the targeted groups, are selected in a feature vector. The selected feature vector is then represented by the Gaussian mixture model. The SBPR and DBPR are subsequently obtained with the help of the GMR and then mapped back to SBP and DBP values that are more accurate than those obtained with the conventional MAA method. [ABSTRACT FROM PUBLISHER]

Automated oscillometric blood pressure monitors are commonly used to measure blood pressure for many patients at home, office, and medical centers, and they have been actively studied recently. These devices usually provide a single blood pressure point and they are not able to indicate the uncertainty of the measured quantity. We propose a new technique using an ensemble-based recursive methodology to measure uncertainty for oscillometric blood pressure measurements. There are three stages we consider: the first stage is pre-learning to initialize good parameters using the bagging technique. In the second stage, we fine-tune the parameters using the ensemble-based recursive methodology that is used to accurately estimate blood pressure and then measure the uncertainty for the systolic blood pressure and diastolic blood pressure in the third stage. [ABSTRACT FROM AUTHOR]

Objectives: To study level effects in the encoding of four vowels in normal hearing adults using the envelope and spectral frequency following response (eFFR and sFFR). We hypothesized that F0, F1 and their neighboring harmonics would grow with increasing level. Material and methods: 19 subjects (8F, 11M, 20-35 yrs) were recorded with four 100 ms vowel stimuli with F0=100 Hz (F1: /a/=700 Hz, /e/=600 Hz,/d/=500 Hz,/u/=300 Hz) at four levels (55, 65, 75, and 85 dBA). eFFR and sFFR spectral amplitudes for each vowel and level were analyzed. Results: Significant effects of level exist at F0 in the eFFR and F1 in the sFFR (p<0.01 in all cases). The combined harmonics show effects oflevel (p<0.001 in all cases), as well as significant pairwise comparisons between most levels. Conclusions: Effects of level exist in the encoding of the speech eFFR and sFFR. 'Ihe eFFR shows increasing spectral richness via the growth of the harmonics of F0 but not at F0 itself, while the sFFR shows a pattern of growth at FI and its neighboring harmonics. [ABSTRACT FROM AUTHOR]

Current noninvasive blood pressure (BP) measurement methods, such as the oscillometric method, estimate the systolic and diastolic blood pressure (SBP and DBP) at two random instants in time and do not take into account the natural variability in BP. The standard for automated BP devices sets a maximum allowable system error of ±5 mmHg, even though natural BP variability often exceeds these limits. This paper proposes a new approach using simultaneous recordings of the oscillometric and continuous arterial pulse waveforms to augment the conventional noninvasive measurement by providing (1) the mean SBP and DBP over the measurement interval and the associated confidence intervals of the mean, (2) the standard deviation of SBP and DBP over the measurement interval, which indicates the degree of fluctuation in BP and (3) an indicator as to whether or not the oscillometric reading is an outlier. Recordings with healthy subjects demonstrate the potential utility of this approach to characterize BP, to detect outlier measurements, and that it does not suffer from bias relative to the conventional oscillometric method. [ABSTRACT FROM AUTHOR]

Background: Current oscillometric blood pressure measurement devices generally provide only singlepoint estimates for systolic and diastolic blood pressures and rarely provide confidence ranges for these estimates. A novel methodology to obtain confidence intervals (CIs) for systolic blood pressure (SBP) and diastolic blood pressure (DBP) estimates from a single oscillometric blood pressure measurement is presented. Methods: The proposed methodology utilizes the multiple regression technique to fuse optimally a set of SBP and DBP estimates obtained through different algorithms. However, the set of SBP and DBP estimates is a small number to determine the CI of each individual subject. To address this issue, the weighted bootstrap approach based on the multiple regression technique was used to generate a pseudo sample set for the SBP and the DBP. In this paper, the multiple regression technique can estimate the best-fitting surface of an efficient function that relates the input sample set as an independent vector to the auscultatory nurse measurement as a dependent vector to estimate regression coefficients. Consequently, the coefficients are assigned to an eight-sample set obtained from the fusion of different algorithms as optimally weighted parameters. CIs are also estimated using the conventional methods on the set of fused SBP and DBP estimates for comparison purposes. Results: The proposed method was applied to an experimental dataset of 85 patients. The results indicated that the proposed approach provides better blood pressure estimates than the existing algorithms and, in addition, is able to provide CIs for a single measurement. Conclusions: The CIs derived from the proposed scheme are much smaller than those calculated by conventional methods except for the pseudo maximum amplitude-envelope algorithm for both the SBP and the DBP, probably because of the decrease in the standard deviation through the increase in the pseudo measurements using the weighted bootstrap method for each subject. The proposed methodology is likely the only one currently available that can provide CIs for single-sample blood pressure measurements. [ABSTRACT FROM AUTHOR]

Continuous blood pressure (BP) monitoring is important for the prevention and early diagnosis of cardiovascular diseases. Cuffless BP estimation using pulse arrival time (PAT) via a mathematical model which enables continuous BP measurement has recently become a popular research topic. In this study, simultaneous biomedical signals from ten healthy subjects were acquired by electrocardiogram (ECG) and photoplethysmogram (PPG) sensors and the continuous reference BP data were collected by a cuff-based Finometer PRO BP monitor. A hierarchical model was applied to estimate the parameters of a nonlinear model which in turn is used to estimate systolic blood pressure (SBP) using PAT with few calibration measurements. The mean absolute difference (MAD) between the estimated SBP and reference SBP is 4.35±1.43 mmHg using the proposed hierarchical model with three calibration measurements and is 4.36±1.17 mmHg with a single calibration measurement.

Blood pressure (BP) is an important physiological marker of human health. It is commonly measured by a cuff-based monitor via either auscultatory or oscillometric methods. Recently, significant research has been conducted to mathematically estimate BP from pulse transit time (PTT) to enable cuffless and continuous BP measurement. In this research, a new time reference, RJ interval, which is the time delay between electrocardiogram (ECG) R peak and ballistocardiogram (BCG) J peak was evaluated to determine if it can be used as a surrogate of PTT in cuffless BP estimation. Biomedical signals from ten healthy subjects were acquired by BCG, ECG and PPG sensors and the continuous reference BP data were collected by a cuff-based Finometer PRO BP monitor. An exponential model was employed to estimate systolic blood pressure (SBP) using RJ interval and PTT. RJ intervals extracted from ECG and BCG were shown to be useful in evaluating trends of SBP and can be the surrogate of PTT in cuffless SBP estimation.