Spectral analysis of Korotkoff sounds

B3X: a novel efficient algorithm for accurate automated auscultatory blood pressure estimation

Objective.The auscultatory technique is still considered the most accurate method for non-invasive blood pressure (NIBP) measurement, although its reliability depends on operator's skills. Various methods for automated Korotkoff sounds analysis have been proposed for reliable estimation of systolic (SBP) and diastolic (DBP) blood pressures. To this aim, very complex methodologies have been presented, including some based on artificial intelligence (AI). This study proposes a relatively simple methodology, named B3X, to estimate SBP and DBP by processing Korotkoff sounds recordings acquired during an auscultatory NIBP measurement.Approach.The beat-by-beat change in morphology of adjacent Korotkoff sounds is evaluated via their cross-correlation. The time series of the beat-by-beat cross-correlation and its first derivative are analyzed to locate the timings of SBP and DBP values. Extensive tests were performed on a public database of 350 annotated measurements, and the performance was evaluated according to the BHS, AAMI/ANSI, and International Organization for Standardization (ISO) quality standards.Main results.The proposed approach achieved 'A' scores for SBP and DBP in the BHS grading system, and passed the quality tests of AAMI/ANSI and ISO standards. The B3X algorithm outperformed two well-established algorithms for oscillometric NIBP measurement in both SBP and DBP estimation. It also outperformed four AI-based algorithms in DBP estimation, while providing comparable performance for SBP, at the cost of a much lower computational burden. The full code of the B3X algorithm is provided in a public repository.Significance.The very good performances ensured by the proposed B3X algorithm, at a low computational cost and without the need for parameter training, support its direct implementation into clinical blood pressure (BP) monitoring devices. The results of this study pave the way for solving/overcoming the trade-off between the accuracy of the auscultatory technique and the objectivity of oscillatory measurements, by bringing an automated auscultatory BP measurement method in clinical practice.

Masking of Korotkoff sounds used in blood pressure measurement through auscultation

Measurement of blood pressure (BP) through manual auscultation and the observation of Korotkoff sounds (KSs) remains the gold standard in BP methodology. Critical to determining BP levels via auscultation is the determination of KS audibility. While absolute sound level audibility is well researched, the problem has not been approached from the point of view of psychoacoustic masking of the sounds. Here, during manual auscultation of BP, a direct comparison is made between what an observer perceives as audible and the electronic analysis of audibility level determined from masking of sound signal levels. KSs are collected during auscultation with an electronic stethoscope, which allows simultaneously observing sound audibility and recording the sound electronically. By time-segmenting the recorded sound around Korotkoff peaks into a test segment and a masking segment, performing Fourier transforms on the segments, and comparing frequency-band sound energy levels, signal-to-noise ratios of a sound to its masking counterpart can be defined. Comparing these ratios to difference limen in the psychoacoustic masking literature, an approximate threshold for sound audibility is obtained. It is anticipated that this approach could have profound effects on future development of automated auscultation BP measurements.

Deep learning-based robust automatic non-invasive measurement of blood pressure using Korotkoff sounds

This paper proposes a method that automatically measures non-invasive blood pressure (BP) based on an auscultatory approach using Korotkoff sounds (K-sounds). There have been methods utilizing K-sounds that were more accurate in general than those using cuff pressure signals only under well-controlled environments, but most were vulnerable to the measurement conditions and to external noise because blood pressure is simply determined based on threshold values in the sound signal. The proposed method enables robust and precise BP measurements by evaluating the probability that each sound pulse is an audible K-sound based on a deep learning using a convolutional neural network (CNN). Instead of classifying sound pulses into two categories, audible K-sounds and others, the proposed CNN model outputs probability values. These values in a Korotkoff cycle are arranged in time order, and the blood pressure is determined. The proposed method was tested with a dataset acquired in practice that occasionally contains considerable noise, which can degrade the performance of the threshold-based methods. The results demonstrate that the proposed method outperforms a previously reported CNN-based classification method using K-sounds. With larger amounts of various types of data, the proposed method can potentially achieve more precise and robust results.

Assessment of arterial stiffness from pedal artery Korotkoff sound recordings: feasibility and potential utility

Brachial artery (BA) Korotkoff sound (KS) timing reflects arterial stiffness. We recorded pedal artery (PA) KS in 68 healthy subjects using an electronic stethoscope and electrocardiography. Intervals between QRS complex of the electrocardiogram and KS waveform peaks (termed the QKD interval) were measured for 60 seconds, averaged, and QKD velocity (v) calculated. Carotid-BA and carotid-PA pulse wave velocities (PWVs) were measured by applanation tonometry. Analyzable KS recordings were obtained from BA and PA in 100% and 92% subjects. PA QKDv decreased less than BA QKDv with progressive cuff inflation. At diastolic blood pressure + 20 mm Hg (maximal yield), BA QKDv was independently associated with weight and pulse pressure, whereas PA QKDv was related to weight and age. PA QKDv correlated with its corresponding PWV stronger than BA QKDv. In conclusion, PA KS is optimally recorded at diastolic blood pressure + 20 mm Hg; PA QKDv is correlated with age and better correlates with PWV than does BA QKDv. This technique may provide a simple arterial stiffness measure.

Improving auscultatory blood pressure measurement with electronic and computer technology: the visual auscultation method

BACKGROUND

The auscultatory method is used as the reference standard in all prevalent protocols for validation of noninvasive blood pressure measuring devices, and a validation study is essentially based on the comparison between the device and observer measurements. Thus, the objectivity and accuracy of observer measurements are crucial to the validation result.

METHODS

To provide observers with more objective information about an auscultatory measurement so that sufficient information to make measurements with greater potential objectivity and accuracy can be available, a computerized data acquisition and analysis system has been developed. It cannot only acquire and store Korotkoff sound, cuff pressure, and oscillometric pulse signals, as well as the sphygmomanometer image, but it also can display the waveforms of the three signals and the sphygmomanometer video while playing the synchronous Korotkoff sounds. With this system, observers can make their measurements via the visual auscultation method, that is to say, by watching those waveforms, instead of the sphygmomanometer, while listening for synchronized Korotkoff sounds. The system was validated according to the International Protocol (IP).

RESULTS

The result showed that all the differences between system measurements by the visual auscultation method and observer measurements by the conventional auscultatory method were within 4 mm Hg.

CONCLUSIONS

The visual auscultation method achieved a high degree of accuracy, and human observers can be replaced by the system in the validation study of blood pressure measuring devices.

Characterization of the Korotkoff sounds using joint time-frequency analysis

The sounds associated with the five classical Korotkoff phases are clinically important for measuring systolic and diastolic blood pressures. The frequency ranges of the sounds have already been described simply using the overall peak frequencies within each phase by Fourier methods. However, such analysis may be missing potentially useful clinical information. The aim of this study was to compare features associated with the different phases of the Korotkoff sounds obtained during blood pressure measurement using a joint time-frequency analysis (JTFA) technique. A single operator recorded Korotkoff sounds from 25 healthy subjects using a measurement system comprising cardiology stethoscope, microphone, amplifier and recording system for computer sound digitization, and a MiniDisc system for playback to the cardiologist for Korotkoff phase classification. We have shown that using this system the phase classification by the cardiologist is repeatable, with no significant differences found in the number of sounds allocated to phases on two separate recording assessments. The digitized sounds were processed using a MATLAB-based short-time Fourier transform JTFA technique and differences in time, frequency and amplitude characteristics between the phases compared. It was found that on average, phase III had the largest overall amplitude and high frequency energy. Phase II had the greatest high frequency component and longest murmur, and was visibly the most complex phase in terms of time and frequency content. In contrast, phases IV and V had the lowest amplitude and frequency components. Overall, the statistically significant transitions between phases were: phase I to II with increases in high frequency (224 to 275 Hz) (p < 0.01) and sound duration (49 to 98 ms) (p < 0.0001), II to III with a significant decrease in sound duration (to 37 ms) (p < 0.0001), III to IV with decreases in maximum amplitude (0.95 to 0.25), highest frequency (262 to 95 Hz), and relative high frequency energy of the sounds (0.61 to 0.10) (all p < 0.0001), and IV to V with decreases in the maximum amplitude (0.25 to 0.13) (p < 0.0002) and high frequency energy (0.10 to 0.03) (p < 0.005). This study has demonstrated that joint time-frequency analysis of Korotkoff sounds was able to identify characteristic differences associated with the different phases classified by the expert cardiologist. Ultimately, exploiting the joint time and frequency characteristics of the sounds may improve blood pressure measurement and help to assess the stiffness of the peripheral arteries.

A new method for automated blood pressure measurement

We propose a new technique for automated indirect blood pressure measurement based on the auscultatory method. Systolic, diastolic and blood mean pressure are identified by looking at trend changes in the spectral energy dispersion of Korotkoff sounds. The detection is solely based on patient measurements, not on population studies. By comparing the automatic detection with common auditory detection, in 286 measurements taken in 15 subjects there was agreement (+/- 1 sound--400 Pa error) in 278 cases for the systole and 276 cases for the diastole.

A system for non-invasively measuring blood pressure on a treadmill

Measurement of signal to artifact ratio yielded optimal frequencies for a Korotkoff-based automatic system for measuring blood pressure on a treadmill. Maximal Korotkoff sounds occurred just above the crease of the elbow over the brachial artery. Output of a piezoelectric microphone and charge amplifier was measured during treadmill exercise for frequency bands from 8 to 57 Hz. An automatic system filtered output from 40 to 45 Hz, rectified it, then compared it to a threshold that had fixed and exponentially decaying components. For five subjects, the system decisions of systolic and diastolic pressures compared well with those of two observers using stethoscopes. The system shows promise for improved measurements of blood pressure during treadmill exercise.

Noninvasive blood pressure measurement on the temporal artery using the auscultatory method

Blood pressures in the temporal artery of five normotensive subjects were recorded using a modified auscultatory setup. The setup comprised a pediatric cuff to occlude the artery and a piezoelectric contact microphone to record the Korotkoff sounds. Both the cuff and microphone were held in their respective positions with an adjustable head band. The recordings were taken under four different conditions: the subject lying supine, the subject sitting at rest, the subject sitting immediately after exercise and the subject moving the head gently. These recordings were compared with readings from the brachial artery, obtained with a commercially available automatic blood pressure measuring device. Korotkoff sounds were analyzed in the time and frequency domain. Results indicate that Korotkoff sounds in the temporal artery are much smaller in amplitude, and do not exhibit the same distinctive phases as those of the brachial artery. Despite these differences, these sounds can be used to detect blood pressures at head level. The accuracy of the readings was within +/- 10%. Successful readings were also obtained with gentle head motions, demonstrating that this setup has the potential to be developed into an ambulatory blood pressure monitoring system.

The Korotkoff sound

As the auscultatory method of blood pressure measurement relies fundamentally on the generation of the Korotkoff sound, identification of the responsible mechanisms has been of interest ever since the introduction of the method, around the turn of the century. In this article, a theory is proposed that identifies the cause of sound generation with the nonlinear properties of the pressure-flow relationship in, and of the volume compliance of the collapsible segment of brachial artery under the cuff. The rising portion of a normal incoming brachial pressure pulse is distorted due to these characteristics, and energy contained in the normal pulse is shifted to the audible range. The pressure transient produced is transmitted to the skin surface and stethoscope through deflection of the arterial wall. A mathematical model is formulated to represent the structures involved and to compute the Korotkoff sound. The model is able to predict quantitatively a range of features of the Korotkoff sound reported in the literature. Several earlier theories are summarized and evaluated.

Korotkoff sound filtering for automated three-phase measurement of blood pressure

Under rest conditions, changes in the Korotkoff sounds at phases I, IV, and V can be correlated with specific frequencies within the bandpass of the stethoscope. A filter capable of detecting the changes in Korotkoff sounds at phases I, IV, and V is described together with the frequency changes that characterize these phases. The importance of frequency components outside the bandpass of the stethoscope is stressed, especially in terms of the possibility of yielding more clinical information and, perhaps, additional clues above the origin of the Korotkoff sounds themselves.