In recent year, the age of patients with heart disease has been decreasing year by year. Myocardial ischemia is the symptom of myocardial infarction, which has the highest mortality rate among heart diseases. Traditional methods can-not provide medical caregivers with a set of immediate and effective monitoring methods, which can hardly provide immediate medical measurement. As a result, we propose an instant AR visualization method to monitor the physiological condition of people in these field to develop the calculation of features and the interpretation of cardiac signals on wearable de-vice. Considering the controversy over the privacy of RGB cameras, we combine RPLiDAR to develop an inertial wearable device identity recognition system, which can identify and track the people in the field. Each person’s physio-logical sensory information is instantly recorded and characterized, which makes medical care-givers monitor at any time clearly and quickly. Through using machine learning model to determine myocardial ischemia and sensor-based fusion of identity recognition technology, it will actively issue alerts when the care recipient’s physiological condition is abnormal and to assist healthcare provider in preventing possible emergency situations. In the experimental evaluation, the algorithms developed in this system are more accurate and efficient than other algorithms.
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