Auscultation is an important diagnostic indicator for cardiovascular analysis. Heart sound classification and analysis play an important role in the auscultative diagnosis. This study uses a combination of Mel-frequency cepstral coefficient (MFCC) and hidden Markov model (HMM) to efficiently extract the features for pre-processed heart sound cycles for the purpose of classification. A system was developed for the interpretation of heart sounds acquired by phonocardiography using pattern recognition. The task of feature extraction was performed using three methods: time-domain feature, short-time Fourier transforms (STFT) and MFCC. The performances of these feature extraction methods were then compared. The results demonstrated that the proposed method using MFCC yielded improved interpretative information. Following the feature extraction, an automatic classification process was performed using HMM. Satisfactory classification results (sensitivity > or =0.952; specificity > or =0.953) were achieved for normal subjects and those with various murmur characteristics. These results were based on 1398 datasets obtained from 41 recruited subjects and downloaded from a public domain. Constituents characteristics of heart sounds were also evaluated using the proposed system. The findings herein suggest that the described system may have the potential to be used to assist doctors for a more objective diagnosis.

Photoplethysmography (PPG) signals can be used in clinical assessment such as heart rate (HR) estimations and extraction of arterial flow waveforms. Motion artefact and/or poor peripheral perfusion can contaminate the PPG during monitoring. A computational system is presented here to minimise these two intrinsic weaknesses of the PPG signals. Specifically, accelerometers are used to detect the presence of motion artefacts and an adaptive filter is employed to minimise induced errors. Zero-phase digital filtering is engaged to reduce inaccuracy on the PPG signals when measured from a poorly perfused periphery. In this system, a decision matrix adopts the appropriate technique to improve the PPG signal-to-noise ratio dynamically. Statistical analyses show promising results (maximum error < 7.63%) when computed HR is compared to corresponding estimates from the electrocardiogram. Hence, the results here suggest that this dual-mode approach has potential for use in relevant clinical measurements.

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Imbalance of the human haemodynamic system can provide a prognosis of syncope, dizziness or hypertension. This can be assessed by monitoring its responses to postural change. Examining variations in blood pressure (BP) is deemed an effective means to identify symptoms of this associated condition. However, conventional methods do not promote prolonged monitoring due to the discomfort caused to patients. Established correlations between BP and pulse wave transmission have shown its usefulness in clinical applications. In this study, photoplethysmography and phonocardiography were used to estimate BP changes via observed variations in delay transmission or vascular transit time (VTT) at the upper limb. Thirty-one healthy adults (21 male) were recruited to perform three test activities, namely the arm held at heart level, fully raised up and held down. Association of the three BP indices and heart rate variations with transit time changes was then computed. The results showed that observed VTT changes were related to systolic BP (R(2) = 0.820; p < 0.05), diastolic BP (R(2) = 0.517; p < 0.05), mean arterial pressure (R(2) = 0.673; p < 0.05) and heart rate (R(2) = 0.000; p > 0.05). As systolic BP had the strongest correlation, a regression equation was formulated to associate the two parameters. The non-invasive measuring nature of VTT can be more accommodating to patients, especially during continual monitoring. Moreover, it has the added advantage that the pre-ejection period is not included in its time-related derivations.

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Characteristics obtained from peripheral pulses can be used to assess the status of cardiovascular system of subjects. However, nonintrusive techniques are preferred when prolonged monitoring is required for their comfort. Pulse transit time (PTT) measurement has showed its potentials to monitor timing changes in peripheral pulse in cardiovascular and respiratory studies. In children, the common peripheries used for these studies are fingers or toes. Presently, there is no known study conducted on children to investigate the possible physiologic parameters that can confound PTT measure at these sites. In this study, PTT values from both peripheral sites were recorded from 55 healthy Caucasian children (39 male) with mean age of 8.472.3 years (range 5-12 years). Peripheries' path length, heart rate, systolic blood pressure, diastolic blood pressure (DBP) and mean arterial pressure (MAP) were measured to investigate their contributions to PTT measurement. The results reveal that PTT is significantly related to all parameters (Po0.05), except for DBP and MAP. Age is observed to be the dominant factor that affects PTT at both peripheries in a child. Regression equations for PTT were derived for measuring from a finger and toe, (6.09 age þ 189.2) ms and (6.70 age þ 243.0) ms, respectively.

Studies have shown that increased arterial stiffening can be an indication of cardiovascular diseases like hypertension. In clinical practice, this can be detected by measuring the blood pressure (BP) using a sphygmomanometer but it cannot be used for prolonged monitoring. It has been established that pulse wave velocity (PWV) is a direct measure of arterial stiffening but its usefulness is hampered by the absence of non-invasive techniques to estimate it. Pulse transit time (PTT) is a simple and non-invasive method derived from PWV. However, limited knowledge of PTT in children is found in the present literature. The aims of this study are to identify independent variables that confound PTT measure and describe PTT regression equations for healthy children. Therefore, PTT reference values are formulated for future pathological studies. Fifty-five Caucasian children (39 male) aged 8.4 +/- 2.3 yr (range 5-12 yr) were recruited. Predictive equations for PTT were obtained by multiple regressions with age, vascular path length, BP indexes and heart rate. These derived equations were compared in their PWV equivalent against two previously reported equations and significant agreement was obtained (p < 0.05). Findings herein also suggested that PTT can be useful as a continuous surrogate BP monitor in children.