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Bidirectional Recurrent Auto-Encoder for Photoplethysmogram Denoising
摘要： Photoplethysmography (PPG) has become ubiquitous with the development of smartwatches and the mobile healthcare market. However, PPG is vulnerable to various types of noises which are ever-present in uncontrolled environments, and the key to obtaining meaningful signals depends on successful denoising of PPG. In this context, algorithms have been developed to denoise PPG, but many were validated in controlled settings or are reliant on multiple steps that must all work correctly. This paper proposes a novel PPG denoising algorithm based on bidirectional recurrent denoising auto-encoder (BRDAE) which requires minimal pre-processing steps and have the benefit of waveform feature accentuation beyond simple denoising. The BRDAE was trained and validated on a dataset with artificially augmented noise, and was tested on a large open-database of PPG signals collected from patients enrolled in intensive care units (ICUs) as well as from PPG data collected intermittently during the daily routine of 9 subjects over 24-hours. Denoising with the trained BRDAE improved signal-to-noise ratio of the noise-augmented data by 7.9dB during validation. In the test datasets, the denoised PPG showed statistically significant improvement in heart rate detection as compared to the original PPG in terms of correlation to reference and root-mean-squared error. These results indicate that the proposed method is an effective solution for denoising the PPG signal, and promises values beyond traditional denoising by providing PPG feature accentuation for pulse waveform analysis.
关键词： auto-encoder (AE),denoising,recurrent neural networks (RNN),photoplethysmography (PPG)
更新于2025-09-23 15:23:52
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Non-Invasive Detection of Mechanical Alternans Utilizing Photoplethysmography
摘要： Background and Significance: Mechanical alternans (MA) is a biomarker associated with mortality and life-threatening arrhythmias in heart failure patients. Despite showing prognostic value, its use is limited by the requirement of measuring continuous blood pressure (BP), which is costly and impractical. Objective: To develop and test, for the first time, non-invasive MA surrogates based on photoplethysmography (PPG). Methods: Continuous BP and PPG were recorded during clinical procedures and tests in 35 patients. MA was induced either by ventricular pacing (Group A, N=19) or exercise (Group B, N=16). MA was categorized as sustained or intermittent if MA episodes were observed in at least 20 or between 12 to 20 consecutive beats, respectively. Eight features characterizing pulse morphology were derived from the PPG and MA surrogates were evaluated. Results: Sustained alternans was observed in 9 patients (47%) from Group A, whereas intermittent alternans was observed in 13 patients (68%) from Group A and in 10 patients (63%) from Group B. The PPG-based MA surrogate showing the highest accuracy, V’M, was based on the maximum of the first derivative of the PPG pulse. It detected both sustained and intermittent MA with 100% sensitivity and 100% specificity in Group A and intermittent MA with 100% sensitivity and 83% specificity in Group B. Furthermore, the magnitudes of MA and its PPG-based surrogate were linearly correlated (R2=0.83, p<0.001). Conclusion: MA can be accurately identified non-invasively through PPG analysis. This may have important clinical implications for risk stratification and remote monitoring.
关键词： Blood pressure (BP),cardiac alternans,photoplethysmography (PPG),hemodynamic instabilities,mechanical alternans (MA)
更新于2025-09-23 15:21:21
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Comparison and Noise Suppression of the Transmitted and Reflected Photoplethysmography Signals
摘要： The photoplethysmography (PPG) is inevitably corrupted by many kinds of noise no matter whether its acquisition mode is transmittance or reflectance. To enhance the quality of PPG signals, many studies have made great progress in PPG denoising by adding extra sensors and developing complex algorithms. Considering the reasonable cost, compact size, and real-time and easy implementation, this study proposed a simple real-time denoising method based on double median filters which can be integrated in microcontroller of commercial or portable pulse oximeters without adding extra hardware. First, we used the boundary extension to preserve the signal boundary distortion and designed a first median filter with the time window at approximately 78 ms to eliminate the high-frequency components of the signal. Then, through the second median filter with a time window which was about 780 ms, we estimated the low-frequency components. Finally, we removed the estimated low-frequency components from the signal to obtain the denoised signal. Through comparing the multiple sets of signals under calmly sitting and slightly moving postures, the PPG signals contained noises no matter whether collected by the transmittance-mode or the reflectance-mode. To evaluate the proposed method, we conducted measured, simulated experiments and a strong noisy environment experiment. Through comparing the morphology distortions, frequency spectra, and the signal-to-noise ratios (SNRs), the results showed that the proposed method can suppress noise effectively and preserve the essential morphological features from PPG signals. As a result, the proposed method can enhance the quality of PPG signals and, thus, can contribute to the improvement of the calculation accuracy of the subsequent physiological parameters. In addition, the proposed method could be a good choice to address the real-time noise reduction of portable PPG measuring instruments.
关键词： median filters,photoplethysmography,PPG,signal-to-noise ratio,motion artifacts,denoising
更新于2025-09-23 15:21:01
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[IEEE 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) - Honolulu, HI, USA (2018.7.18-2018.7.21)] 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) - Improved Heart Rate Tracking Using Multiple Wrist-type Photoplethysmography during Physical Activities
摘要： Photoplethysmography (PPG) signals collected from wearable sensing devices during physical exercise are easily corrupted by motion artifact (MA), which poses great challenge on heart rate (HR) estimation. This paper proposes a new framework to accurately estimate HR using two leads of PPG signals in combination with accelerometer (ACC) data in the presence of MA. A moving time window is first used to segment PPG signals and ACC signals. Then, MA is attenuated by joint sparse spectrum reconstruction in each time window, where maximum spectrum frequencies of ACC are subtracted from the spectrum frequency of PPG signals. Further, HR for each cleansed PPG is estimated from the frequency with maximum amplitude in the sparse spectrum. The actual HR is determined using spectral band powers calculated from each reconstructed PPG signals. The proposed method was validated using the 2015 IEEE Signal Processing Cup dataset. The average absolute error is 1.15 beats per minutes (BPM) (standard deviation: 2.00 BPM), and the average absolute error percentage is 0.95% (standard deviation: 1.86%). The proposed method outperforms the previously reported work in terms of accuracy.
关键词： accelerometer (ACC),heart rate (HR),motion artifact (MA),joint sparse spectrum reconstruction,Photoplethysmography (PPG)
更新于2025-09-23 15:21:01
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[IEEE 2019 IEEE SENSORS - Montreal, QC, Canada (2019.10.27-2019.10.30)] 2019 IEEE SENSORS - A New Adaptive Readout System For a New OLED OPD Flexible Patch PPG Sensor
摘要： This study proposes a new multiwavelength OLED-OPD flexible PPG sensor with a time-interleaved, optimal high order adaptive analog filter-based readout system for the long-time continuous monitoring of PPG time, temperature modulation of the light absorption and scattering coefficient of the human skin and its compensation strategy has been explored in this study. This study intended to minimize the issue like motion artifacts and mispositioning. Analog front end of the readout circuit incorporates a transimpedance amplifier, optimal filter, programmable gain amplifier (1x to 7x), PWM-DAC based OLED intensity control, Bluetooth transceiver, MCU with inbuilt ADC and a power management unit. At the backend, digital control and pre-signal processing-algorithm are developed to improve the adaptability of the readout system against non-idealities which enable the readout system for the longtime continuous measurement of the biological sign. Digitally variable resistance is used herein to tune the central frequency of the bandpass filter which helps to minimize low heart rate issue. The sensing range of the readout circuit is 20nA to 10μA. With 3.3 V power supply the total power consumption of the readout system is 0.4W. Experimental result shows that the heart rate measurement error is less than 3.4bpm. In the worst case, the measured repulsive pulse transit time (RPTT) variation from PPG cycle to cycle is less than 2%.
关键词： Photoplethysmography (PPG) Sensor,OLED,OPD,flexible patch,filter
更新于2025-09-16 10:30:52
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[IEEE ICASSP 2018 - 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) - Calgary, AB (2018.4.15-2018.4.20)] 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) - Robust Beat-To-Beat Detection Algorithm for Pulse Rate Variability Analysis from Wrist Photoplethysmography Signals
摘要： Heart rate variability (HRV) from electrocardiograms (ECG) is a well-known diagnostic method for the assessment of autonomic nervous function of the heart. A more convenient approach to assess cardiac function is by using Photoplethysmography (PPG) waveforms where pulse rate variability (PRV) replaces HRV. However, the unavailability of robust detection algorithms for PPG signals has prevented the medical market from providing clinical diagnosis using PRV and from measuring biological information for wellness purposes, such as sleep stage, stress state, and fatigue. This paper provides a robust peak and onset detection algorithm for beat-to-beat (B2B) pulse interval analysis using PPG signals. We demonstrate our method through large data collection with the Analog Devices (ADI) multi-sensory watch platform with high coverage, sensitivity, and low Root Mean Square of Successive Difference (RMSSD) as compared to the B2B results from ECG signals.
关键词： Delineation,Pulse Rate Variability (PRV),Heart Rate Variability,Beat-to-Beat,Photoplethysmography (PPG)
更新于2025-09-10 09:29:36
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[IEEE 2018 24th International Conference on Pattern Recognition (ICPR) - Beijing, China (2018.8.20-2018.8.24)] 2018 24th International Conference on Pattern Recognition (ICPR) - Variational Mode Decomposition-Based Heart Rate Estimation Using Wrist-Type Photoplethysmography During Physical Exercise
摘要： Heart rate (HR) monitoring based on Photoplethysmography (PPG) has drawn increasing attention in modern wearable devices due to its simple hardware implementation and low cost. In this work, we propose a variational mode decomposition (VMD)-based HR estimation method using wrist-type PPG signals during physical exercise. To remove motion artifacts (MA), VMD was first used and then a post-processing method after VMD was proposed to guarantee the robustness of MA removal. The performance of our proposed method was evaluated on two PPG datasets used in 2015 IEEE Signal Processing Cup. The method achieved the average absolute error of 1.45 beat per minute (BPM) on the 12 training sets and 3.19 BPM on the 10 testing sets, confirmed by the experimental results.
关键词： Photoplethysmography (PPG),Heart rate monitoring,variational mode decomposition,motion artifacts,wearable devices
更新于2025-09-09 09:28:46
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Two-Pronged Motion Artifact Reduction for Wearable Photoplethysmographic Biosensors
摘要： Motion artifact poses a big challenge in photoplethysmography (PPG) for it greatly increases the difficulties of extracting the signal of interest accurately and reliably. Various techniques have been put forward in the past to tackle the issue. While these techniques have focused exclusively on artifact reduction, we attack the problem on two fronts. By integrating the auxiliary sensor and exploiting its correlations with the optical PPG sensor, not only do we cancel the artifacts but also, at the same time, enhance the signal of interest. Enhancing the signal of interest equivalently boosts the artifact reduction. The experiments have shown that the strategy performs rather effectively: The 95% limits of agreement (LOA) after the artifact reduction has been reduced down to less than one third of the LOA before the artifact reduction and is only three fourths as much as that of the artifact-free PPG.
关键词： biological sensors,Sensor systems,photoplethysmography (PPG),motion artifacts
更新于2025-09-09 09:28:46
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A Portable, Wireless Photoplethysomography Sensor for Assessing Health of Arteriovenous Fistula Using Class-Weighted Support Vector Machine
摘要： A portable, wireless photoplethysomography (PPG) sensor for assessing arteriovenous fistula (AVF) by using class-weighted support vector machines (SVM) was presented in this study. Nowadays, in hospital, AVF are assessed by ultrasound Doppler machines, which are bulky, expensive, complicated-to-operate, and time-consuming. In this study, new PPG sensors were proposed and developed successfully to provide portable and inexpensive solutions for AVF assessments. To develop the sensor, at first, by combining the dimensionless number analysis and the optical Beer Lambert’s law, five input features were derived for the SVM classifier. In the next step, to increase the signal-noise ratio (SNR) of PPG signals, the front-end readout circuitries were designed to fully use the dynamic range of analog-digital converter (ADC) by controlling the circuitries gain and the light intensity of light emitted diode (LED). Digital signal processing algorithms were proposed next to check and fix signal anomalies. Finally, the class-weighted SVM classifiers employed five different kernel functions to assess AVF quality. The assessment results were provided to doctors for diagonosis and detemining ensuing proper treatments. The experimental results showed that the proposed PPG sensors successfully achieved an accuracy of 89.11% in assessing health of AVF and with a type II error of only 9.59%.
关键词： support vector machine (SVM),arteriovenous fistula (AVF),photoplethysmography (PPG) sensor
更新于2025-09-09 09:28:46
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[IEEE 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) - Honolulu, HI (2018.7.18-2018.7.21)] 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) - A 5-ms Error, 22-μA Photoplethysmography Sensor using Current Integration Circuit and Correlated Double Sampling
摘要： This paper presents a low-power Photoplethysmography (PPG) sensing method. The PPG is commonly used in recent wearable devices to detect cardiovascular information including heartbeat. The heartbeat is useful for physical activity and stress monitoring. However, the PPG circuit consumes large power because it consists of LED and photodiode. To reduce its power consumption without accuracy degradation, a cooperative design of circuits and algorithms is proposed in this work. A straightforward way to reduce the power is intermittent driving of LED, but there is a disadvantage that the signal is contaminated by a noise while circuit switching. To overcome this problem, we introduce correlated double sampling (CDS) method, which samples an integration circuit output twice with short intervals after the LED turns on and uses the difference of these voltage. Furthermore, an up-conversion method using linear interpolation, and an error correction using autocorrelation are introduced. The proposed PPG sensor, which consists of the LED, the photodiode, the current integration circuit, a CMOS switch, an A/D converter, and an MCU, is prototyped. It is evaluated by actual measurement with 22-year-old subject. The measurement results show that 22-μA total current consumption is achieved with 5-ms mean absolute error.
关键词： wearable devices,low-power,heartbeat monitoring,Photoplethysmography (PPG),autocorrelation,correlated double sampling (CDS)
更新于2025-09-04 15:30:14