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Ayurvedic and other alternative medical practitioners throughout the world have been using pulse diagnosis to detect disease and the organ at distress by feeling the palpations at three close yet precise positions of the radial artery. This paper presents a robust electro-mechanical system, 'Nadi Yantra' which uses piezoelectric based pressure sensors to capture the signals from the radial artery. Morphology of the waveforms obtained from our system concurs with standard physiological arterial signals. Reproducibility and stability of the system has been verified. Signal processing techniques were applied to obtain features such as amplitude, power spectral density, bandpower and spectral centroid to reflect variations in signals from the three channels. Further, wavelet based techniques were used to process the pressure signals and percussion peaks were identified. The interval between the percussion peaks was used to calculate Heart Rate Varibility (HRV), a useful tool for assessing the status of the autonomic nervous system of the human body noninvasively. Time domain indices were calculated from direct measurement of peak-peak (PP) intervals and from differences between the PP intervals. Frequency domain indices such as very low frequency (VLF) power, low frequency (LF) power, high frequency (HF) power, LF/HF ratio were also calculated. Thereafter, nonlinear Poincare analysis was carried out. A map of consecutive PP intervals was fitted to an ellipse using least squares method. Results from 7 datasets are depicted in this paper. A novel pressure pulse recording instrument is developed for the objective assessment of the ancient science of pulse diagnosis. The features calculated using multi resolution wavelet analysis show potential in the evaluation of the autonomic nervous system of the human body.

The purpose of this study is to apply and evaluate performance of wavelets and select an appropriate wavelet to detect the peaks and dicrotic notch from the waveform captured from infrared finger-tip Photoplethesmography (PPG) and detect the significant peaks and valleys from the signal captured from the radial artery. Accurate detection of dicrotic notch is important as it finds its usage in various medical applications viz. pulse oximeters, vascular diagnostics, digital beat-to-beat blood pressure measurement systems and autonomic function analyzers. The method was extended to detect points of interest in pressure signal from radial artery. Radial artery signals were captured from a robust system called 'Nadi Yantra' [1] developed for the validation of ancient method of non-invasive pulse diagnosis of ailments. The system uses piezoelectric based pressure system to capture the palpations from the radial artery. To characterize the signals, wavelets were applied and the percussion wave, tidal wave and dicrotic notch were detected. The techniques developed were executed on a set of 120 data samples from healthy subjects. Daubechies wavelet was found to be suitable for PPG and radial artery pulse analysis. Overall efficiency of 98.45% for PPG signal and 97.89% for radial artery signal was achieved.

The risk of plaque rupture in carotid atherosclerotic disease is associated more closely with the composition of plaque rather than the severity of stenosis. The constituents of plaque can be determined from ultrasonic spectral parameters obtained from normalized backscatter tissue data. Calibration of the data is done using echoes off a specular reflector which removes the system response of an ultrasound transducer, Terason (Teratech Corporation), from the backscatter data. A reference spectrum study is used to compare specular reflectors based on time domain (echo) and frequency domain (power spectrum, centroid and parabola test) analysis. Nylon and a tissue-mimicking phantom (velocity = 1560 m/s, slope of attenuation = 0.7 dB/cm MHz) have an intermediate acoustic impedance with respect to water and appear good choices as specular reflectors for clinical ultrasound imaging scanners compared to Plexiglas and other higher reflecting materials. A tissue-mimicking phantom is used to correct for attenuation in plaque, diffraction and saturation of electronics of the ultrasound scanner. Autoregressive power spectrum estimation methods are used to extract spectral parameters (spectral slope, y-intercept, midband fit, maximum and minimum power with corresponding frequencies, and integrated backscatter) from calibrated tissue data and linear and quadratic discriminant rules developed for classification of carotid arterial plaque. Regions of interest (n = 64; 64 samples x 8 scan lines with 30 MHz sampling frequency) consisting of 48 fibrous-fibrofatty (Class 1), 11 thrombus-necrotic core (Class 2), and 5 dense calcium (Class 3) areas selected for analysis show that fibrosis can be differentiated from necrosis and calcification. The quadratic discriminant rule identified necrosis with a lower misclassification rate (9.1%) than the linear discriminant rule (18.2%).