Portable Pulse Detection System Based on IoT / 中国医疗器械杂志

Aiming at the current situation of high cost, huge volume, complex operation and difficulty in real application of pulse analyzer, this study designs and implements a portable pulse detection system based on IoT. The design utilizes Raspberry Pi 3B+, STM32 series MCU and cloud server to collect, store, display and recognize pulse signals at CUN, GUAN and CHI. The system is small in size and low in cost, which can be connected with cloud server through network to make full use of resources. The experimental results show that the recognition accuracy of the main feature points of the pulse signal by the portable pulse analyzer is higher than 97%, which has a broad prospect of development and application.

Study on a quantitative analysis method for pulse signal by modelling its waveform in time and space domain / 生物医学工程学杂志

In order to quantitatively analyze the morphology and period of pulse signals, a time-space analytical modeling and quantitative analysis method for pulse signals were proposed. Firstly, according to the production mechanism of the pulse signal, the pulse space-time analytical model was built after integrating the period and baseline of pulse signal into the analytical model, and the model mathematical expression and its 12 parameters were obtained for pulse wave quantification. Then, the model parameters estimation process based on the actual pulse signal was presented, and the optimization method, constraints and boundary conditions in parameter estimation were given. The spatial-temporal analytical modeling method was applied to the pulse waves of healthy subjects from the international standard physiological signal sub-database Fantasia of the PhysioNet in open-source, and we derived some changes in heartbeat rhythm and hemodynamic generated by aging and gender difference from the analytical models. The model parameters were employed as the input of some machine learning methods, e.g. random forest and probabilistic neural network, to classify the pulse waves by age and gender, and the results showed that random forest has the best classification performance with Kappa coefficients over 98%. Therefore, the space-time analytical modeling method proposed in this study can effectively quantify and analyze the pulse signal, which provides a theoretical basis and technical framework for some related applications based on pulse signals.

Research on adaptive pulse signal extraction algorithm based on fingertip video image / 生物医学工程学杂志

In order to solve the saturation distortion phenomenon of R component in fingertip video image, this paper proposes an iterative threshold segmentation algorithm, which adaptively generates the region to be detected for the R component, and extracts the human pulse signal by calculating the gray mean value of the region to be detected. The original pulse signal has baseline drift and high frequency noise. Combining with the characteristics of pulse signal, a zero phase digital filter is designed to filter out noise interference. Fingertip video images are collected on different smartphones, and the region to be detected is extracted by the algorithm proposed in this paper. Considering that the fingertip's pressure will be different during each measurement, this paper makes a comparative analysis of pulse signals extracted under different pressures. In order to verify the accuracy of the algorithm proposed in this paper in heart rate detection, a comparative experiment of heart rate detection was conducted. The results show that the algorithm proposed in this paper can accurately extract human heart rate information and has certain portability, which provides certain theoretical help for further development of physiological monitoring application on smartphone platform.

Analysis of Pulse Signals Based on Array Pulse Volume / 中国结合医学杂志

OBJECTIVE@#To collect and analyze multi-dimensional pulse diagram features with the array sensor of a pressure profile system (PPS) and study the characteristic parameters of the new multi-dimensional pulse diagram by pulse diagram analysis technology.@*METHODS@#The pulse signals at the Guan position of left wrist were acquired from 105 volunteers at the Shanghai University of Traditional Chinese Medicine. We obtained the pulse data using an array sensor with 3×4 channels. Three dimensional pulse diagrams were constructed for the validated pulse data, and the array pulse volume (APV) parameter was computed by a linear interpolation algorithm. The APV differences among normal pulse (NP), wiry pulse (WP) and slippery pulse (SP) were analyzed using one-way analysis of variance. The coefficients of variation (CV) were calculated for WP, SP and NP.@*RESULTS@#The APV difference between WP and NP in the 105 volunteers was statistically significant (6.26±0.28 vs. 6.04±0.36, P=0.048), as well as the difference between WP and SP (6.26±0.28 vs. 6.07±0.46, P=0.049). However, no statistically significant difference was found between NP and SP (P=0.75). WP showed a similar CV (4.47%) to those of NP (5.96%) and SP (7.58%).@*CONCLUSION@#The new parameter APV could differentiate between NP or SP and WP. Accordingly, APV could be considered an useful parameter for the analysis of array pulse diagrams in Chinese medicine.

The study on extraction method of pulse rate variability in daily unsupervised state / 生物医学工程学杂志

The extraction of pulse rate variability(PRV) in daily life is often affected by exercise and blood perfusion. Therefore, this paper proposes a method of detecting pulse signal and extracting PRV in post-ear, which could improve the accuracy and stability of PRV in daily life. First, the post-ear pulse signal detection system suitable for daily use was developed, which can transmit data to an Android phone by Bluetooth for daily PRV extraction. Then, according to the state of daily life, nine experiments were designed under the situation of static, motion, chewing, and talking states, respectively. Based on the results of these experiments, synchronous data acquisition of the single-lead electrocardiogram (ECG) signal and the pulse signal collected by the commercial pulse sensor on the finger were compared with the post-auricular pulse signal. According to the results of signal wave, amplitude and frequency-amplitude characteristic, the post-ear pulse signal was significantly steady and had more information than finger pulse signal in the traditional way. The PRV extracted from post-ear pulse signal has high accuracy, and the accuracy of the nine experiments is higher than 98.000%. The method of PRV extraction from post-ear has the characteristics of high accuracy, good stability and easy use in daily life, which can provide new ideas and ways for accurate extraction of PRV under unsupervised conditions.

Interference Detection and Quality Assessment of Pulse Signal on Android Platform / 中国医疗器械杂志

The collection process of the pulse signal is easily disturbed by the noise, that will reduce the quality of the signal, and affect its applications on the healthy monitoring system. In order to solve this problem, this paper analyzes the causes of the generation of interference during pulse signal acquisition and the characteristics of interference performance, and puts forward the corresponding detection algorithm for pulse signal interference section. Based on this algorithm, a Cascaded Layer-by-Layer Discrimination method is proposed to evaluate the quality of pulse signals, in which pulse signals are divided into available signals and unavailable signals. Experimental results on PC and Android platform show that the proposed algorithm can detect the interference segment accurately in the pulse signal in real time, and improve the usability of the evaluation for pulse signal.

Aumento en la efectividad de la identificación de cimas y pies en el pulso fotopletismográfico al reconstruirlo mediante filtrado adaptativo / Increase in the effectiveness of identifying peaks and feet of the photoplethysmographic pulse to be reconstructed it using adaptive filtering

Resumen: Objetivo: Mejorar la identificación de cimas y pies en el pulso fotopletismográfico (PPG, por sus siglas en inglés), deformado por efecto del ruido miocinético, mediante la implementación de un dedal modificado y filtrado adaptativo. Método: Se obtuvo el PPG en 10 voluntarios sanos empleando 2 sistemas de fotopletismografía colocados en el dedo índice de cada mano, y registrándolos simultáneamente durante 3 min. Durante el primer minuto de registro, ambas manos estuvieron en reposo, y durante los 2 min posteriores, solo la mano izquierda realizó movimientos cuasi-periódicos para añadir ruido miocinético. Se emplearon 2 metodologías para procesar las señales fuera de línea, en una se usó un filtro con el algoritmo de mínimos cuadrados promediados (LMS, por sus siglas en inglés) y en la otra se hizo un preprocesamiento adicional al filtrado LMS. Ambas metodologías fueron comparadas y la de menor error porcentual en la señal recuperada se utilizó para valorar la mejora en la identificación de cimas y pies del PPG. Resultados: El error promedio obtenido fue del 22.94% para la primera metodología, y del 3.72% para la segunda. Los errores en la identificación de cimas y pies antes de filtrar el PPG fueron del 24.26 y 48.39%, respectivamente, una vez filtrados, disminuyeron a 2.02 y 3.77%, respectivamente. Conclusiones: El filtrado adaptativo basado en el algoritmo LMS, más una etapa de preprocesamiento, permite atenuar el ruido miocinético en el PPG, y aumentar la efectividad en la identificación de cimas y pies de pulso, que resultan de gran importancia para una valoración médica.

Abstract: Objective: To improve the identification of peaks and feet in photoplethysmographic (PPG) pulses deformed by myokinetic noise, through the implementation of a modified fingertip and applying adaptive filtering. Method: PPG signals were recordedfrom 10 healthy volunteers using two photoplethysmography systems placed on the index finger of each hand. Recordings lasted three minutes andwere done as follows: during the first minute, both handswere at rest, and for the lasting two minutes only the left hand was allowed to make quasi-periodicmovementsin order to add myokinetic noise. Two methodologies were employed to process the signals off-line. One consisted on using an adaptive filter based onthe Least Mean Square (LMS) algorithm, and the other includeda preprocessing stage in addition to the same LMS filter. Both filtering methods were compared and the one with the lowest error was chosen to assess the improvement in the identification of peaks and feet from PPG pulses. Results: Average percentage errorsobtained wereof 22.94% with the first filtering methodology, and 3.72% withthe second one. On identifying peaks and feet from PPG pulsesbefore filtering, error percentages obtained were of 24.26% and 48.39%, respectively, and once filtered error percentageslowered to 2.02% for peaks and 3.77% for feet. Conclusions: The attenuation of myokinetic noise in PPG pulses through LMS filtering, plusa preprocessing stage, allows increasingthe effectiveness onthe identification of peaks and feet from PPG pulses, which are of great importance for medical assessment.

An algorithm of real-time peak detection for pulse signals based on FPGA / 军事医学

Objective To present a new algorithm of real-time peak detection for pulse signals based on FPGA , which is known as the dynamic threshold with half peak detection method ( DT-HP ) .Methods With Gaussian-shaped pulse signals as the target , the method was improved from conventional methods .The FPGA detection process of the algorithm required no more than three detection parameters: the starting point , the maximum value and the pulse width .Results The algorithm solved the floating baseline and repeating detection that occur in traditional methods .Compared with the results of polynomial fitting method and flow cytometry , the difference was only 3.2% and 9.3%.Conclusion The algorithm takes less time ,RAM, and cache while allowing floating baseline detection , which can be used as an effective method for rapid detection in FPGA .

Acquisition of Pulse Characteritics Based on Wavelet Module Maximum Principle / 航天医学与医学工程

Objective To study a wavelet method for acquiring the characters of pulse wave based on the principle of wavelet transform which can effectively solve the problem of inaccuracy of the conventional methods. Method The method of wavelet module maximum was used to divide the pulse wave according to periods and basically decomposed it, by arranging in time order and symbolizing the module maximum character points of pulse wave signal at the ascending and descending edges as well as the crest and trough. Result Through the method, the unobvious dicrotism, trail wave and the anomalistic wave appearing at the ascending and descending edge of the main wave, and multi-scale characters and all kinds of characters in time domain of pulse signal were further acquired more accurately. Conclusion Simplicity, quickness and accuracy are achieved by focusing on the character points of pulse signals. It provides a new means for further studies of classification and identification of pulse signals.

Design of SpO_2 Measuring and Analysis System Based on LabVIEW / 医疗卫生装备

Objective To design and develop a kind of SpO2 detection and analysis system based on LabVIEW. Methods Pulse signal process and SpO2 calculation were achieved by designing a control system based on TI Company's MSP430FG439 MCU and using the digital signal process and graphic controls of the LabVIEW software. The design project and the realization way were given out by discussing the software of LabVIEW. Results The system could acquire, display and process pulse signal and calculate SpO2. Conclusion The system carries out a new way to design medical monitor equipment. Furthermore, it provides a shortcut for special analysis of the SpO2 and pulse signal in clinic.