Mr. Jindong Zhang Profile

Jindong Zhang

at Tianjin Jingfan Technology Co., Ltd.

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Publications (3)

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Proceedings Article | 15 February 2022 Paper

Analysis and research on the change of characteristic parameters with age based on PPG signal

Huirong Tao, Jindong Zhang, Jiu-li Cui

Proceedings Volume 12166, 121667P (2022) https://doi.org/10.1117/12.2618001

KEYWORDS: Analytical research, Signal processing, Blood vessels, Edge detection, Feature extraction, Blood pressure

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The most important uncontrollable factor in the decrease of blood vessel elasticity is aging. Therefore, if the deterioration of blood vessel function can be detected early, it will play an important role in the prevention of various cardiovascular diseases. This paper aims to find the characteristic parameters of pulse wave waveforms that are highly correlated with cardiovascular diseases and provide early warning for possible cardiovascular diseases. In this paper, the pulse waves of 6 healthy volunteers of different ages were collected, 100 samples were collected for each age, and the cardiovascular characteristic parameters of each sample were extracted. In order to overcome the instability of the pulse waveform during the acquisition of a single sample, this paper proposes a multi-waveform superimposition average processing method based on edge detection. This method separates the collected samples individually, selects excellent one-week waveforms for fusion, and then uses the fused average waveform to extract feature parameters, and finally calculates the average and standard deviation of each sample feature parameter at each age stage. So as to analyze the changes of PPG characteristic parameters in different age groups. The experimental results show that the inflow time, the inflow time index, the outflow time index, the ratio of inflow time to outflow time vary with age, and there is a strong correlation, while outflow time, reflection parameters, main wave and dicrotic wave time difference is not particularly sensitive to changes in age.

Proceedings Article | 24 November 2021 Paper

Research on dual-spectrum headband health monitoring system

Huirong Tao, Jindong Zhang

Proceedings Volume 12065, 120652X (2021) https://doi.org/10.1117/12.2606771

KEYWORDS: Heart, Oxygen, Intelligence systems, Signal processing

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The development of photoelectric detection technology has promoted the development of the smart wearable market. Wristband heart rate monitoring equipment has become a familiar product to the public. However, according to related research tests, there is a large error between the heart rate monitoring data of the wristband device and the real data during exercise. This article proposes a dual-spectrum headband health monitoring system solution with ultra-small size, ultra-low power consumption, and high integration for the above problems, which converts the monitoring part from the common wrist to the forehead. The integrated monitoring system is as small as 11.8mm*5mm. Ultra-low power consumption design effectively improves the battery life of smart wearable devices. The dual-spectrum monitoring system adopts the reflected photoelectric pulse wave detection method, and integrates red light and infrared light to form a dual LED. The heart rate value is calculated through the collected photoplethysmography (PPG) signal. In the software algorithm processing, the Mallat algorithm of wavelet transform is first used for software filtering, and then the pulse wave signal characteristic points are identified. By comparing the system designed in this paper with the fluke blood oxygen simulator, the results show that the heart rate measurement error of the system reaches plus or minus 1% + 1 beat/min. In addition, the dual-spectrum health monitoring system can also use "cloud" big data analysis technology to provide more health information. It can also be used for the management of chronic cardiovascular diseases.

Proceedings Article | 5 November 2020 Paper

Research on photoelectric pulse monitoring system

Huirong Tao, Jindong Zhang

Proceedings Volume 11568, 115681P (2020) https://doi.org/10.1117/12.2580198

KEYWORDS: Blood, Heart, Oxygen, Light sources, Infrared radiation, Reflectivity

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Aiming at the shortcomings of the existing photoelectric pulse wave acquisition and analysis chip with large volume or no data processing and analysis function in the prior art, this paper proposes a small and highly integrated heart rate blood oxygen monitoring system solution with a built-in pulse wave algorithm. Its internal data acquisition and analysis module is as small as 3 × 3mm² . The position of each module on the PCB is reasonably distributed, and the overall structure of the heart rate and blood oxygen monitoring system is miniaturized. The integrated monitoring system can be as small as 7 × 15mm² , which makes the heart rate oximetry system can be embedded in more portable products. The software algorithm first performs an average filtering process on the original signal. Then, the differential threshold method is used to extract the characteristic points of the pulse wave signal, that is, the maximum value and the minimum value, so as to obtain the positions of the peaks and troughs. The heart rate value is calculated based on the time difference t between two adjacent peaks of the light signal reflected by the red light source during the period. The experimental results show that the heart rate error of the integrated system can reach ±2% + 1 times / minute, and the blood oxygen error can reach ±2% within the range of 70-100.

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