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Showing 1 to 5 of 5 for “"Instantaneous heart rate"”.

  1. An Instantaneous Frequency Based Approach to Estimate Heart Rate and Calculate Heart Rate Variability Metrics

    An emerging diagnostic tool for detecting heart and physiological conditions is heart rate variability (HRV). Copious research continuously discovers relationships between heart rate variability metrics and physiological functions and cardiac health. The first step in calculating HRV metrics is …

    vt Repository record for An Instantaneous Frequency Based Approach to Estimate Heart Rate and Calculate Heart Rate Variability Metrics (opens in a new tab)

  2. Applying domain knowledge to clinical predictive models

    … models. We first applied knowledge about the heart to engineer better frequency-domain features from electrocardiograms (ECG). The standard frequency domain (in Hz) quantifies events that repeat with respect to time. However, this may be misleading because patients have different heart rates. …

    mit Repository record for Applying domain knowledge to clinical predictive models (opens in a new tab)

  3. Cardiac Signals: Remote Measurement and Applications

    … the proposed method eliminates the effect of instantaneous heart rate on the shape morphology and improves authentication accuracy. For noninvasive measurement of PPG beats, we have developed a systematic algorithm to extract pulse rate from face video in diverse situations using video …

    vt Repository record for Cardiac Signals: Remote Measurement and Applications (opens in a new tab)

  4. Modeled and Unmodeled Approaches for Quantification of the Cardiac Autonomic Nervous System

    … information about traumatic brain injury, heart failure, stroke, diabetes, and sports performance; information that can ultimately aid in clinical decision making. In this work, we develop a non-invasive model-based approach and characterize a large class of unmodeled approaches for …

    mit Repository record for Modeled and Unmodeled Approaches for Quantification of the Cardiac Autonomic Nervous System (opens in a new tab)

  5. Extraction of Blood Volume Pulse Morphology from Facial Videos Using an LSTM-Based Temporal Encoder-Decoder Model

    … signals from facial videos, moving beyond basic heart rate estimation to capture full pulse waveforms. Our approach adapts techniques from audio signal separation and applies them to video, using a machine learning model capable of processing complex time-based data. By incorporating both regular …

    vt Repository record for Extraction of Blood Volume Pulse Morphology from Facial Videos Using an LSTM-Based Temporal Encoder-Decoder Model (opens in a new tab)