TITLE:
Nadi Yantra: a robust system design to capture the signals from the radial artery for assessment of the autonomic nervous system non-invasively
AUTHORS:
A bhinav, Meghna Sareen, Mahendra Kumar, Jayashree Santhosh, Ashok Salhan, Sneh Anand
KEYWORDS:
Radial Artery; Pulse Diagnosis; Power Spectral Density; Spectral Centroid; Multi Resolution Wavelet; Autonomic Nervous System; Heart Rate Variability; Time Domain; Frequency Domain; Poincare
JOURNAL NAME:
Journal of Biomedical Science and Engineering,
Vol.2 No.7,
November
19,
2009
ABSTRACT: Ayurvedic and other alternative medical practi-tioners 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 non-invasively. 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 deve loped for the objective assessment of the ancient sci-ence 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.