Recognition of sub-health state by using pulse and electrocardiogram signals

Sub-health is an intermediate state between healthy and diseased, and it is becoming more and more popular. Sub-healthy individuals are at high risk of developing disease if not treated in time. In order to evaluate sub-health state, synchronous acquisition of pulse and electrocardiogram (ECG) signals was conducted by using self-designed synchronous acquisition system. An objective measurement to evaluate sub-health state was studied based on the hidden information within ECG and pulse signals that might offer insights into the nature of the sub-health state. The pulse and ECG features such as pulse power spectrum peak and PTT were extracted. Linear Discriminant Analysis (LDA) algorithm was used for sub-health state classification. The satisfactory recognition result was obtained by using all ECG and pulse features, which provide a new research approach for evaluating sub-health state.