During pulse signal collection, width information of pulse waves is essential for the diagnosis of disease. However, currently used measuring instruments can only detect the amplitude while can’t acquire the width information. This paper proposed a novel wrist pulse signal acquisition system, which could realize simultaneous measurements of the width and amplitude of dynamic pulse waves under different static forces. A tailor-packaged micro-electro-mechanical system (MEMS) sensor array was employed to collect pulse signals, a conditioning circuit was designed to process the signals, and a customized algorithm was developed to compute the width. Experiments were carried out to validate the accuracy of the sensor array and system effectiveness. The results showed the system could acquire not only the amplitude of pulse wave but also the width of it. The system provided more information about pulse waves, which could help doctors make the diagnosis.

The respiratory signal is a critical index of cardiopulmonary function. In this paper, we implement the polyvinylidene fluoride (PVDF) sensor to collect the data of pulse waves and reference respiration signals. The correlations between the major feature values and breaths are investigated and presented. As a result, several feature values exhibit relatively good correlations with reference respiratory amplitude. The improvements of Kalman Filter for the respiratory signals extracted from feature value variances are also introduced. Moreover, we display the comparisons with low-pass filtering, Wavelet filtering, and ensemble empirical mode decomposition (EEMD) method. Using the method of identifying error breaths, the error rate of the new method is about 4.146%. The new method is feasible for real-time applications at quiet state.