Key result
Inexpensive AVR microcontroller system collects and analyzes HRV signals using Poincare and Rescale Range techniques.
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The study presents an inexpensive AVR microcontroller-based data acquisition system for analyzing heart rate variability, which may serve as a useful noninvasive diagnostic tool.
Heart rate variability (HRV) is a reliable index and reflection of the many physiological factors modulating the normal rhythm of the heart. In fact, this provides a powerful means of observing the interplay between the sympathetic and parasympathetic nervous systems. Heart Rate (HR) is a non stationary signal; its variation may contain indicators of current disease, or warnings about impending cardiac diseases. The indicators may be present at all times or may occur at random during certain intervals of the day. Hence t is strenuous and time consuming to study and pinpoint abnormalities in voluminous data collected over several hours. Therefore HR variation analysis (instantaneous HR against time axis) has become a popular noninvasive tool for assessing the activities of the autonomic nervous system. Computer based analytical tools for in-depth study of data over daylong intervals can be very useful in diagnostics. Therefore, the HRV signal parameters, extracted and analyzed using computers, are highly useful in diagnostics. Here we present an inexpensive AVR microcontroller based data acquisition system with computer interface. Typical data collected is presented and analyzed using Poincare plot and Rescale Range analysis technique and thus fractal dimension of the time series of HR signal is determined and details discussed.
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Akhter et al. (2012) studied Heart Rate Variability measurement. AVR microcontroller based data acquisition system was evaluated. An inexpensive AVR microcontroller-based data acquisition system was developed to collect and analyze heart rate variability signals using Poincare plot and Rescale Range analysis techniques.
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