Abstract
Pulse wave signal sensed over the radial artery on the wrist is a crucial physiological indicator in disease diagnosis. The sensor array composed of multiple sensors has the ability to collect abundant pulse wave information. As a result, it has gradually attracted the attention of practitioners. However, few practical methods are used to obtain a one-dimensional pulse wave from the sensor array’s spatial multi-dimensional signals. The current algorithm using pulse wave with the highest amplitude value as the significant data suffers from low consistency because the signal acquired each time differs significantly due to the sensor’s relative position shift to the test area. This paper proposes a processing method based on time series similarity, which can take full advantage of sensor arrays’ spatial multi-dimensional characteristics and effectively avoid the above factors’ influence. A pulse wave acquisition system (PWAS) containing a micro-electro-mechanical system (MEMS) sensor array is continuously extruded using a stable dynamic pressure input source to simulate the pulse wave acquisition process. Experiments are conducted at multiple test locations with multiple data acquisitions to evaluate the performance of the algorithm. The experimental results show that the newly proposed processing method using time series similarity as the criterion has better consistency and stability.
Highlights
Like the electrocardiography (ECG) signal, the heart’s regular contraction and diastole produce a pulse wave signal [1]
Consistent with the above, the Dynamic Time Warping (DTW) distance was used to assess the similarity of the two waveforms
We describe and evaluate the algorithms’ characteristics in two ways: the degree to which the processing result of the algorithm is close to the standard input signal, including DTW distance and gain; and the magnitude of the change in the processing result of the algorithm in different test areas
Summary
Like the electrocardiography (ECG) signal, the heart’s regular contraction and diastole produce a pulse wave signal [1]. The diagnosis of diseases through pulse signals has been highly approved by traditional Chinese medicine (TCM) but has received increasing attention from modern medicine [4,5,6]. In TCM diagnosis, the pulse wave collection position is mainly distributed in the radial artery area near the subject’s wrist. The pulse waveform is related to the static force applied to the test area, divided into three segments: Fu, Zhong, and Chen, according to the course of the force from light to heavy, as shown in Figure 1b [8]
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