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NON-CONTACT HEART RATE MONITORING USING MACHINE LEARNING

Health Monitoring Is An Important Parameter To Determine The Health Status Of A Person. Measuring The Heart Rate Is An Easy Way To Gauge Our Health. Normal Heart Rate May Vary From Person To Person And A Usually High Or Low Resting Heart Rate Can Be A Sign Of Trouble. There Are Several Methods For The Measurement Of Heart Rate Monitoring Such As Ecg, Ppg Etc. Such Methods Having A Disadvantage That These Are Invasive And Have A Continuous Contact With The Human Body. In Order To Overcome This Problem A New System Is Proposed Using Camera. In This Method A Blind Source Separation Algorithm Is Used For Extracting The Heart Rate Signal From The Face Image. Viola Jones Based Face Detection Algorithm Is Used To Track The Face. FastICA Algorithm Is Exploited To Separate Heart Rate Signal From Noise And Artefacts. Machine Learning Algorithm Is Implemented To Standardize The Signal. The Data Is Successfully Tested With Real Time Video.

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