Pulse diagnosis is one of the four diagnostic methods of traditional Chinese medicine. However it suffers from the lack of objective and efficient detection method. We propose a noncontact optical method to detect human wrist pulse, aiming at the precise determination of the temporal and spatial distributions of pulse. The method uses the spatial-carrier digital speckle pattern interferometry (DSPI) to measure the micro/nanoscale skin displacement dynamically. Significant improvements in DSPI measurement have been made to allow the DSPI to detect the comprehensive information of the arterial pulsation at locations of Cun, Guan, and Chi. The experimental results prove that the spatiotemporal distributions of pulse can be obtained by the proposed method. The obtained data can be further used to describe most of the pulse parameters such as rate, rhythm, depth, length, width, and contour.
Human arterial pulsation is considered as a vital sign. It includes much information of human health. In Chinese traditional medicine (TCM), the arterial pulsation at the locations of Cun, Guan, and Chi, which are near wrist joint, as shown in Figure
Pulsation at the locations of Cun, Guan, and Chi.
Traditionally, physicians of Chinese medicine touch patient’s wrist and feel the pulsations at the three locations: Cun, Guan, and Chi. The diagnostic test relies entirely on the doctor’s own experiential judgment. This subjective test may be affected by many factors. Moreover, the diagnostic results are hard to record and exchange. Thus, the quantification and standardization of the pulse diagnosis are very important. It requires the transformation of doctors’ subjective feelings into objective physical quantities. To achieve this goal, the precise determination of the temporal and spatial distributions of the wrist pulse is required.
Owning to the development of modern transducers and computer technology, many physical methods have been presented to detect the wrist pulse during the last thirty years. These methods are mainly classified into pressure sensing and optical test methods. The pressure sensing methods are further divided into piezoresistive, piezoelectric, and piezocapacitive sensors. These sensors are attached to wrist skin tightly in order to sense the pulse pressure. For example, Sook Hyang Yoon et al. attached three semiconductor resistance strain gauge piezoresistive sensors at the three locations of Cun, Guan, and Chi to detect their pressure changes and pulse waves [
Optical method can be divided into point measurement and full-field measurement methods. These methods detect the pulse by measuring the displacements of the human skin at selected locations or the full field. The optical point measurement, such as optical interferometry [
Full-field measurement using optical method is desired to allow the obtainment of the pulse spatial distributions. Efforts in this research area mainly focus on vision measurement and digital image correlation (DIC) techniques. For example, Zhang developed an image device to satisfy the full-field detection of pulse [
We introduce a precise pulse detection method based on digital speckle pattern interferometry (DSPI), allowing the highly sensitive detection of the temporal and spatial distributions of the pulse and the obtainment of more comprehensive and detailed pulse information. DSPI is a full-field optical technique which can measure the displacement/deformation distributions of object surfaces. Compared to vision measurement and DIC, DSPI enjoys significant advantages of much higher measuring accuracy and independence from cooperation target [
DSPI is classified, based on their optical setups and phase determination methods, into phase-shifting DSPI (PS-DSPI) and spatial-carrier DSPI (SC-DSPI) [
Optical setup for wrist pulse detection.
The intensity distribution of the interferogram captured by the camera is given by
The inclination angle of the reference beam towards the optical axis determines the spatial frequency of the speckle interferogram. The maximal spatial frequency is calculated by
The last two terms of (
DSPI records a sequence of speckle interferograms and determines the phase
After the phase differences are obtained, a sine/cosine average filter is used to filter the noise at the obtained phase maps, yielding smoothed phase maps. The entire process of digital speckle interferogram collection and phase reconstruction is shown in Figure
Process of the phase difference map calculation.
The relationship between the phase difference and displacement
Usually the angle between the illumination and observation directions is very small. The absolute value of the sensitivity vector
Phase unwrapping (PU) is a process to remove the 2
TPU is carried out along the time axis due to the independence of each camera pixel. The phase at each pixel is treated as a function of time and unwrapped by a one-dimensional unwrapping algorithm. SPU involves a spatial comparison of phase values at neighboring pixels, which can be further classified into path-dependent and path-independent methods. STPU unwraps the whole phase map along the 2D spatial domain and several selected points along the time axis. The combination of the spatial and temporal phase distributions yields the dynamic phase difference maps. The operating procedure of STPU is depicted by Figure
Procedure of spatiotemporal three-dimensional phase unwrapping.
A 5 W diode pumped solid state laser with a central wavelength of 532nm (Coherent Verdi G5) and CMOS camera (CatchBEST MU3S230 (SGYYO)) with a frame rate of 80 frames per second (fps) at 2.3 megapixels were used in the experiment. The frame rate can be enhanced when the pixel resolution is reduced. The camera was triggered by an external clock signal which guaranteed the uniformly sampling of the wrist pulse. A nonspherical lens whose focal length is 100 mm was used for imaging.
Reference [
The right wrist of a volunteer was fixed by two lashing bands on a backplane. In addition, the output of the laser was adjusted to 0.25 W to avoid human’s discomfort. In the experiment, totally 28800 digital speckle interferograms were captured for further processing. The vibration of pulse during the test time of 3 minutes was then obtained. The experimental setup is shown in Figure
Experimental setup for wrist pulse detection.
Results within a period of 30 s were selected for exhibition. Figure
Absolute displacement of pulse at the location of pixel (290, 480): (a) raw data obtained by performing the temporal phase unwrapping; (b) amplitude spectrum; (c) raw and denoised data.
The displacement detail and frequency spectrum of the pulse vibration are depicted by Figure
Detail of the pulse amplitude and frequency: (a) pulse displacement; (b) pulse amplitude spectrum.
The spatial distributions of pulse vibration are given by Figure
Spatial displacement distributions of the pulse.
The paper presents a human wrist arterial pulsation detection method using SC-DSPI. The feasibility of pulse detection using the presented method is illustrated by the theoretical analysis as well as the experiment. The advantage of noninvasive, full-field, and high-precision detection has also been demonstrated.
The authors declare that they have no conflicts of interest.
This work is supported by the National Natural Science Foundation of China (Grants nos. 51675055, 51705025, and 11672045) and Qin Xin Talents Cultivation Program, Beijing Information Science & Technology University. The authors would like to thank the volunteer named Tengfei Yuan for providing experimental support.