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        <identifier>oai:figshare.com:article/33264066</identifier>
        <datestamp>2026-09-17T23:06:20Z</datestamp>
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          <dc:title>Low-Cost Flexible PPG-Based Heart Rate Monitoring System Using PIC Microcontroller with ML Fusion</dc:title>
          <dc:creator>Nazmus Salehin Noman (24205500)</dc:creator>
          <dc:subject>Biomechanical engineering</dc:subject>
          <dc:subject>Electrical circuits and systems</dc:subject>
          <dc:subject>Photoplethysmography (PPG)</dc:subject>
          <dc:subject>Pulse Sensor</dc:subject>
          <dc:subject>PIC16F877A</dc:subject>
          <dc:subject>Machine Learning</dc:subject>
          <dc:description>&lt;p dir="ltr"&gt;This dataset contains photoplethysmography (PPG)-based heart rate measurements collected for the development and evaluation of a low-cost heart rate monitoring system. The dataset includes PPG signals acquired using a pulse sensor and corresponding heart rate measurements obtained from a Rossmax pulse oximeter as the reference device. Data were collected under different physiological conditions, including resting and exercise conditions, to evaluate the performance of the proposed system across varying heart rate levels. The collected data were used for preprocessing, feature extraction, machine learning-based calibration, and comparison with the reference measurements. The dataset is intended to support research on PPG-based heart rate estimation, sensor calibration, embedded machine learning, and low-cost physiological monitoring systems.&lt;/p&gt;</dc:description>
          <dc:date>2026-09-17T23:06:20Z</dc:date>
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          <dc:identifier>10.6084/m9.figshare.33264066.v3</dc:identifier>
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