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- Heart Rate Monitor Tutorial Vs. Stochastic Signal Processing
Heart Rate Monitor Tutorial vs Stochastic Signal Processing Uso & Estadísticas
The concepts of Heart Rate measurement using reflective photoplethysmography (PPG) along with some of the basic digital signal processing (DSP) techniques are demonstrated. PPG waveforms are displayed and your heart rate is calculated. Signal processing controls are provided for experimenting with different DSP techniques on heart rate measurement.
DSP techniques discussed in the tutorial sections include:
- recursive high-pass filter
- recursive low-pass filter
- signal source and signal to noise ratio (SNR)
- sampling rate
The main SwiftUI code for the demo is provided for reference or as a starting point for further investigation.
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Speech, music, seismic vibrations, oil prices, and climate measurements are all examples of stochastic (random) signals. In this textbook—intended for individuals with prior training in introductory signal processing and introductory probability theory—we develop techniques to process such signals to extract useful information. We present case studies ranging from music to photographic images to oil prices to climate data to the motion of individual biomolecules. This textbook, as an interactive textbook ("iBook"), makes use of your device's ability to display dynamic information through films and animations and to hear the results of the techniques applied to music. At the end of every chapter there are homework problems ranging from easy to "olympic".
A new and exciting aspect is that we make use of your device's interactive capabilities to offer 59 laboratory experiments in signal processing. The experiments use the camera, the microphone, the speakers, and the graphical user interface. These experiments are not simulations; they are examples of real digital processing of signals in your device. In this time of at-home and online learning, this is the way to learn signal processing through study and experimentation.
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Heart Rate Monitor Tutorial frente a Stochastic Signal Processing: comparación de la clasificación
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enero 22, 2026