Prediction of Stroke Risk Using the Magnetoplethysmogram Radial Artery Pulse Data

Long periods of stress and depression can cause heart disease, brain disease, and high blood pressure. However, regardless of the advancements in modern medicine, stroke patients face difficulties without special medicines or treatments. A computer simulation is conducted to predict stroke risk factors using a magnetoplethysmogram equipped with a magnetic sensing Hall device to analyze radial artery pulses. We use logistic regression analysis to determine the vacuous pulse from the clinical data of 60 patients with deficiency syndrome and perform a computer simulation to determine stroke and early stage diseases using a TensorFlowbased open source. Additionally, computer simulations using brachycardia diagnostic cluster analysis and fuzzy inference, which are used in oriental medicine, are conducted to improve the prediction rate of stroke by more than 10%.