Analysis of the effect of CPAP on hemodynamics using clinical data and a theoretical model: CPAP therapy decreases cardiac output mechanically but increases it via afterload reduction.

BACKGROUND: Noninvasive positive pressure ventilation (NIPPV) has been established as an effective treatment for heart failure. Positive airway pressure such as continuous positive airway pressure (CPAP) increases cardiac output (CO) in some patients but decreases it in others. However, the mechanism behind such unpredictable responses remains undetermined. METHODS AND RESULTS: We measured hemodynamic parameters of 38 cases using Swan-Ganz catheter before and after CPAP in chronic heart failure status. In those whose CO increased by CPAP, pulmonary vascular resistance (PVR) was significantly decreased and SpO2 significantly increased, but the other parameters were not changed. On the other hand, PVR was not changed, but systemic vascular resistance (SVR) was increased in those whose CO decreased by CPAP. To explain this phenomenon, we simulated the cardiovascular system using a cardiac model of time-varying elastance. In this model, it was indicated that CPAP decreases CO irrespective of cardiac function or filling status under constant PVR condition. However, when reduction of PVR by CPAP was taken into account, an increase in CO was expected especially in the hypervolemic and low right ventricle (RV) systolic function cases. CONCLUSIONS: CPAP would increase CO only where PVR can be reduced by CPAP therapy, especially in the case with hypervolemia and/or low RV systolic function. Understanding the underlying mechanism should help identify the patients for whom NIPPV would be effective.

A PPG-Based Calibration-Free Cuffless Blood Pressure Estimation Method Using Cardiovascular Dynamics.

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.

Perception of Prosody in Hearing-Impaired Individuals and Users of Hearing Assistive Devices: An Overview of Recent Advances.

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. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.21809772.

The effect of hearing protection worn by talker and/or target listener on speech production in quiet and noise.

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.

Cuffless Blood Pressure Estimation Using Calibrated Cardiovascular Dynamics in the Photoplethysmogram.

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.

Novel Cuffless Blood Pressure Estimation Method Using a Bayesian Hierarchical Model.

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.

Uncertainty in Blood Pressure Measurement Estimated Using Ensemble-Based Recursive Methodology.

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.

An indirect calculation method for estimating occupational sound exposure from communication headsets.

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.

Continuous Tracking of Changes in Systolic Blood Pressure using BCG and ECG.

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.

Detecting Cardiac Activity by Capacitive Electrodes from a Single Point on the Wrist.

Ballistocardiography (BCG) is the measurement of body movement by forces associated with heart contraction that can be used for monitoring cardiac activity. It has already been measured by force sensor and accelerometer. In this research, we developed a capacitive wristband that provides a method for single point, continuous BCG measurement, which has the potential to become a new type of sensor for wearable health care. The aim of this paper is to validate that the signal detected by capacitive electrodes is actually the BCG signal. Signals from four healthy subjects were acquired by a capacitive wristband together with Electrocardiogram (ECG). The capacitive signal was validated by both morphology matching analysis and wave occurrence time matching analysis to show that it is indeed BCG signal. JJ intervals extracted from BCG were shown to have potential to be surrogate of ECG RR series in heart rate variability analysis.

Effects of Early- and Late-Arriving Room Reflections on the Speech-Evoked Auditory Brainstem Response.

BACKGROUND: Room reverberation alters the acoustical properties of the speech signals reaching our ears, affecting speech understanding. Therefore, it is important to understand the consequences of reverberation on auditory processing. In perceptual studies, the direct sound and early reflections of reverberated speech have been found to constitute useful energy, whereas the late reflections constitute detrimental energy. PURPOSE: This study investigated how various components (direct sound versus early reflections versus late reflections) of the reverberated speech are encoded in the auditory system using the speech-evoked auditory brainstem response (ABR). RESEARCH DESIGN: Speech-evoked ABRs were recorded using reverberant stimuli created as a result of the convolution between an ongoing synthetic vowel /a/ and each of the following room impulse response (RIR) components: direct sound, early reflections, late reflections, and full reverberation. Four stimuli were produced: direct component, early component, late component, and full component. STUDY SAMPLE: Twelve participants with normal hearing participated in this study. DATA COLLECTION AND ANALYSIS: Waves V and A amplitudes and latencies as well as envelope-following response (EFR) and fine structure frequency-following response (FFR) amplitudes of the speech-evoked ABR were evaluated separately with one-way repeated measures analysis of variances to determine the effect of stimulus. Post hoc comparisons using Tukey's honestly significant difference test were performed to assess significant differences between pairs of stimulus conditions. RESULTS: For waves V and A amplitudes, a significant difference or trend toward significance was found between direct and late components, between direct and full components, and between early and late components. For waves V and A latencies, significant differences were found between direct and late components, between direct and full components, between early and late components, and between early and full components. For the EFR and FFR amplitudes, a significant difference or trend toward significance was found between direct and late components, and between early and late components. Moreover, eight, three, and one participant reported the early, full, and late stimuli, respectively, to be the most perceptually similar to the direct stimulus. CONCLUSIONS: The stimuli that are acoustically most similar (direct and early) result in electrophysiological responses that are not significantly different, whereas the stimuli that are acoustically most different (direct and late, early and late) result in responses that are significantly different across all response measures. These findings provide insights toward the understanding of the effects of the different components of the RIRs on auditory processing of speech.

An integrated blood pressure measurement system for suppression of motion artifacts.

Accuracy in blood pressure (BP) estimation is essential for proper diagnosis and management of hypertension. Motion artifacts are considered external sources of inaccuracy and can be due to sudden arm motion, muscle tremor, shivering, and transport vehicle vibrations. In the proposed work, a new algorithmic stage is integrated in a non-invasive BP monitor. This stage suppresses the effect of the motion artifact and adjusts the pressure estimation before displaying it to users. The proposed stage is based on a 3-axis accelerometer signal, which helps in the accurate detection of the motion artifact. Both transient motion artifacts and artifact due to vibrations are suppressed using algorithms based on Empirical Mode Decomposition (EMD). Measurements with human subjects show that the proposed algorithms considerably improved the accuracy of the blood pressure estimates in comparison with the commonly-used conventional oscillometric algorithm that does not include an EMD-based stage for artifact suppression, and allowed the estimates to meet the requirements of the international ANSI/AAMI/ISO standard.

Self-masking and overlap-masking from reverberation using the speech-evoked auditory brainstem response.

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.

Characteristic Ratio-Independent Arterial Stiffness-Based Blood Pressure Estimation.

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.

Event Recognition for Contactless Activity Monitoring Using Phase-Modulated Continuous Wave Radar.

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.

Oscillometric blood pressure estimation by combining nonparametric bootstrap with Gaussian mixture model.

BACKGROUND: Blood pressure (BP) is one of the most important vital indicators and plays a key role in determining the cardiovascular activity of patients. METHODS: This paper proposes a hybrid approach consisting of nonparametric bootstrap (NPB) and machine learning techniques to obtain the characteristic ratios (CR) used in the blood pressure estimation algorithm to improve the accuracy of systolic blood pressure (SBP) and diastolic blood pressure (DBP) estimates and obtain confidence intervals (CI). The NPB technique is used to circumvent the requirement for large sample set for obtaining the CI. A mixture of Gaussian densities is assumed for the CRs and Gaussian mixture model (GMM) is chosen to estimate the SBP and DBP ratios. The K-means clustering technique is used to obtain the mixture order of the Gaussian densities. RESULTS: The proposed approach achieves grade "A" under British Society of Hypertension testing protocol and is superior to the conventional approach based on maximum amplitude algorithm (MAA) that uses fixed CR ratios. The proposed approach also yields a lower mean error (ME) and the standard deviation of the error (SDE) in the estimates when compared to the conventional MAA method. In addition, CIs obtained through the proposed hybrid approach are also narrower with a lower SDE. CONCLUSIONS: The proposed approach combining the NPB technique with the GMM provides a methodology to derive individualized characteristic ratio. The results exhibit that the proposed approach enhances the accuracy of SBP and DBP estimation and provides narrower confidence intervals for the estimates.

Bayesian fusion algorithm for improved oscillometric blood pressure estimation.

A variety of oscillometric algorithms have been recently proposed in the literature for estimation of blood pressure (BP). However, these algorithms possess specific strengths and weaknesses that should be taken into account before selecting the most appropriate one. In this paper, we propose a fusion method to exploit the advantages of the oscillometric algorithms and circumvent their limitations. The proposed fusion method is based on the computation of the weighted arithmetic mean of the oscillometric algorithms estimates, and the weights are obtained using a Bayesian approach by minimizing the mean square error. The proposed approach is used to fuse four different oscillometric blood pressure estimation algorithms. The performance of the proposed method is evaluated on a pilot dataset of 150 oscillometric recordings from 10 subjects. It is found that the mean error and standard deviation of error are reduced relative to the individual estimation algorithms by up to 7 mmHg and 3 mmHg in estimation of systolic pressure, respectively, and by up to 2 mmHg and 3 mmHg in estimation of diastolic pressure, respectively.

Improved Accuracy of Automated Estimation of Cardiac Output Using Circulation Time in Patients with Heart Failure.

BACKGROUND: Lung-to-finger circulation time of oxygenated blood during nocturnal periodic breathing in heart failure patients measured using polysomnography correlates negatively with cardiac function but possesses limited accuracy for cardiac output (CO) estimation. METHODS AND RESULTS: CO was recalculated from lung-to-finger circulation time using a multivariable linear model with information on age and average overnight heart rate in 25 patients who underwent evaluation of heart failure. The multivariable model decreased the percentage error to 22.3% relative to invasive CO measured during cardiac catheterization. CONCLUSIONS: This improved automated noninvasive CO estimation using multiple variables meets a recently proposed performance criterion for clinical acceptability of noninvasive CO estimation, and compares very favorably with other available methods.

Comparison of direct measurement methods for headset noise exposure in the workplace.

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.

Estimated confidence interval from single blood pressure measurement based on algorithmic fusion.

BACKGROUND: Current oscillometric blood pressure measurement devices generally provide only single-point 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.