Low-Power Photoplethysmogram Acquisition Integrated Circuit with Robust Light Interference Compensation

Evaluating Vascular Depth-Dependent Changes in Multi-Wavelength PPG Signals Due to Contact Force

Photoplethysmography (PPG) is a non-invasive method used for cardiovascular monitoring, with multi-wavelength PPG (MW-PPG) enhancing its efficacy by using multiple wavelengths for improved assessment. This study explores how contact force (CF) variations impact MW-PPG signals. Data from 11 healthy subjects are analyzed to investigate the still understudied specific effects of CF on PPG signals. The obtained dataset includes simultaneous recording of five PPG wavelengths (470, 525, 590, 631, and 940 nm), CF, skin temperature, and the tonometric measurement derived from CF. The evolution of raw signals and the PPG DC and AC components are analyzed in relation to the increasing and decreasing faces of the CF. Findings reveal individual variability in signal responses related to skin and vasculature properties and demonstrate hysteresis and wavelength-dependent responses to CF changes. Notably, all wavelengths except 631 nm showed that the DC component of PPG signals correlates with CF trends, suggesting the potential use of this component as an indirect CF indicator. However, further validation is needed for practical application. The study underscores the importance of biomechanical properties at the measurement site and inter-individual variability and proposes the arterial pressure wave as a key factor in PPG signal formation.

Novel Multi-Parametric Sensor System for Comprehensive Multi-Wavelength Photoplethysmography Characterization

Photoplethysmography (PPG) is widely used to assess cardiovascular health. However, its usage and standardization are limited by the impact of variable contact force and temperature, which influence the accuracy and reliability of the measurements. Although some studies have evaluated the impact of these phenomena on signal amplitude, there is still a lack of knowledge about how these perturbations can distort the signal morphology, especially for multi-wavelength PPG (MW-PPG) measurements. This work presents a modular multi-parametric sensor system that integrates continuous and real-time acquisition of MW-PPG, contact force, and temperature signals. The implemented design solution allows for a comprehensive characterization of the effects of the variations in these phenomena on the contour of the MW-PPG signal. Furthermore, a dynamic DC cancellation circuitry was implemented to improve measurement resolution and obtain high-quality raw multi-parametric data. The accuracy of the MW-PPG signal acquisition was assessed using a synthesized reference PPG optical signal. The performance of the contact force and temperature sensors was evaluated as well. To determine the overall quality of the multi-parametric measurement, an in vivo measurement on the index finger of a volunteer was performed. The results indicate a high precision and accuracy in the measurements, wherein the capacity of the system to obtain high-resolution and low-distortion MW-PPG signals is highlighted. These findings will contribute to developing new signal-processing approaches, advancing the accuracy and robustness of PPG-based systems, and bridging existing gaps in the literature.

Wearable Continuous Blood Pressure Monitoring Devices Based on Pulse Wave Transit Time and Pulse Arrival Time: A Review

Continuous blood pressure (BP) monitoring is of great significance for the real-time monitoring and early prevention of cardiovascular diseases. Recently, wearable BP monitoring devices have made great progress in the development of daily BP monitoring because they adapt to long-term and high-comfort wear requirements. However, the research and development of wearable continuous BP monitoring devices still face great challenges such as obvious motion noise and slow dynamic response speeds. The pulse wave transit time method which is combined with photoplethysmography (PPG) waves and electrocardiogram (ECG) waves for continuous BP monitoring has received wide attention due to its advantages in terms of excellent dynamic response characteristics and high accuracy. Here, we review the recent state-of-art wearable continuous BP monitoring devices and related technology based on the pulse wave transit time; their measuring principles, design methods, preparation processes, and properties are analyzed in detail. In addition, the potential development directions and challenges of wearable continuous BP monitoring devices based on the pulse wave transit time method are discussed.

Photoplethysmogram Analysis and Applications: An Integrative Review

Beyond its use in a clinical environment, photoplethysmogram (PPG) is increasingly used for measuring the physiological state of an individual in daily life. This review aims to examine existing research on photoplethysmogram concerning its generation mechanisms, measurement principles, clinical applications, noise definition, pre-processing techniques, feature detection techniques, and post-processing techniques for photoplethysmogram processing, especially from an engineering point of view. We performed an extensive search with the PubMed, Google Scholar, Institute of Electrical and Electronics Engineers (IEEE), ScienceDirect, and Web of Science databases. Exclusion conditions did not include the year of publication, but articles not published in English were excluded. Based on 118 articles, we identified four main topics of enabling PPG: (A) PPG waveform, (B) PPG features and clinical applications including basic features based on the original PPG waveform, combined features of PPG, and derivative features of PPG, (C) PPG noise including motion artifact baseline wandering and hypoperfusion, and (D) PPG signal processing including PPG preprocessing, PPG peak detection, and signal quality index. The application field of photoplethysmogram has been extending from the clinical to the mobile environment. Although there is no standardized pre-processing pipeline for PPG signal processing, as PPG data are acquired and accumulated in various ways, the recently proposed machine learning-based method is expected to offer a promising solution.

Low-Noise Photoplethysmography Sensor Using Correlated Double Sampling for Heartbeat Interval Acquisition

This study designs a low-power photoplethysmography (PPG) sensor based on the error compensation method for heartbeat interval acquisition. To perform heartbeat monitoring in daily life, it is necessary to obtain long-term and accurate heartbeat interval data with low power consumption, because of the limited size and battery capacity of the PPG sensor. Effective reduction in the power consumption of the sensor requires the duty-cycled LEDs and lowering pulse repetition frequency (PRF), i.e., decreasing the sampling rate. However, these methods reduce the accuracy of the heartbeat interval measurement because of signal-to-noise ratio (SNR) degradation and sampling errors. We propose an algorithm for heartbeat interval error compensation and incorporate a low-noise readout circuit to improve SNR. The readout circuit uses current integration to achieve low duty-cycle LED driving. A correlated double sampling (CDS) is introduced to minimize the random noise arising from the switching operation of the integration circuit. An error compensation method based on the PPG waveform similarity is also introduced using the autocorrelation and linear interpolation. The measurement results obtained from nine subjects show that a total current consumption of 28.2 μA is achieved with a 20-Hz PRF and 0.3% LED duty cycle. The proposed design effectively reduces the mean absolute error (MAE) of the heartbeat interval to an average of 6.2 ms.

Monte Carlo Analysis of Optical Interactions in Reflectance and Transmittance Finger Photoplethysmography

Photoplethysmography (PPG) is a non-invasive photometric technique that measures the volume changes in arterial blood. Recent studies have reported limitations in developing and optimising PPG-based sensing technologies due to unavailability of the fundamental information such as PPG-pathlength and penetration depth in a certain region of interest (ROI) in the human body. In this paper, a robust computational model of a dual wavelength PPG system was developed using Monte Carlo technique. A three-dimensional heterogeneous volume of a specific ROI (i.e., human finger) was exposed at the red (660 nm) and infrared (940 nm) wavelengths in the reflectance and transmittance modalities of PPG. The optical interactions with the individual pulsatile and non-pulsatile tissue-components were demonstrated and the optical parameters (e.g., pathlength, penetration depth, absorbance, reflectance and transmittance) were investigated. Results optimised the source-detector separation for a reflectance finger-PPG sensor. The analysis with the recorded absorbance, reflectance and transmittance confirmed the maximum and minimum impact of the dermis and bone tissue-layers, respectively, in the formation of a PPG signal. The results presented in the paper provide the necessary information to develop PPG-based transcutaneous sensors and to understand the origin of the ac and dc components of the PPG signal.

14.85 µW Analog Front-End for Photoplethysmography Acquisition with 142-dBΩ Gain and 64.2-pArms Noise

A low-power, high-gain, and low-noise analog front-end (AFE) for wearable photoplethysmography (PPG) acquisition systems is designed and fabricated in a 0.35 μm CMOS process. A high transimpedance gain of 142 dBΩ and a low input-referred noise of only 64.2 pA_rms was achieved. A Sub-Hz filter was integrated using a pseudo resistor, resulting in a small silicon area. To mitigate the saturation problem caused by background light (BGL), a BGL cancellation loop and a new simple automatic gain control block are used to enhance the dynamic range and improve the linearity of the AFE. The measurement results show that a DC photocurrent component up-to-10 μA can be rejected and the PPG output swing can reach 1.42 V_pp at THD < 1%. The chip consumes a total power of 14.85 μW using a single 3.3-V power supply. In this work, the small area and efficiently integrated blocks were used to implement the PPG AFE and the silicon area is minimized to 0.8 mm × 0.8 mm.

A Portable, Wireless Photoplethysomography Sensor for Assessing Health of Arteriovenous Fistula Using Class-Weighted Support Vector Machine

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%.

A low-power high-sensitivity analog front-end for PPG sensor

This paper presents a low-power analog front-end (AFE) photoplethysmography (PPG) sensor fabricated in 0.35 μm CMOS process. The AFE amplifies the weak photocurrent from the photodiode (PD) and converts it to a strong voltage at the output. In order to decrease the power consumption, the circuits are designed in subthreshold region; so the total biasing current of the AFE is 10 μ A. Since the large input DC photocurrent is a big issue for the PPG sensing circuit, we apply a DC photocurrent rejection technique by adding a DC current-cancellation loop to reject the large DC photocurrent up to 10 μA. In addition, a pseudo resistor is used to reduce the high-pass corner frequency below 0.5 Hz and Gm-C filter is adapted to reject the out-of-band noise higher than 16 Hz. For the whole sensor, the amplifier chain can achieve a total gain of 140 dBμ and an input integrated noise current of 68.87 pA_rms up to 16 Hz.

Biosignal integrated circuit with simultaneous acquisition of ECG and PPG for wearable healthcare applications

BACKGROUND

Wearable healthcare systems require measurements from electrocardiograms (ECGs) and photoplethysmograms (PPGs), and the blood pressure of the user. The pulse transit time (PTT) can be calculated by measuring the ECG and PPG simultaneously. Continuous-time blood pressure without using an air cuff can be estimated by using the PTT.

OBJECTIVE

This paper presents a biosignal acquisition integrated circuit (IC) that can simultaneously measure the ECG and PPG for wearable healthcare applications.

METHODS

Included in this biosignal acquisition circuit are a voltage mode instrumentation amplifier (IA) for ECG acquisition and a current mode transimpedance amplifier for PPG acquisition. The analog outputs from the ECG and PPG channels are muxed and converted to digital signals using 12-bit successive approximation register (SAR) analog-to-digital converter (ADC).

RESULTS

The proposed IC is fabricated by using a standard 0.18 μm CMOS process with an active area of 14.44 mm2. The total current consumption for the multichannel IC is 327 μA with a 3.3 V supply. The measured input referred noise of ECG readout channel is 1.3 μVRMS with a bandwidth of 0.5 Hz to 100 Hz. And the measured input referred current noise of the PPG readout channel is 0.122 nA/√Hz with a bandwidth of 0.5 Hz to 100 Hz.

CONCLUSIONS

The proposed IC, which is implemented using various circuit techniques, can measure ECG and PPG signals simultaneously to calculate the PTT for wearable healthcare applications.

Reconfigurable Multiparameter Biosignal Acquisition SoC for Low Power Wearable Platform

A low power and low noise reconfigurable analog front-end (AFE) system on a chip (SoC) for biosignal acquisition is presented. The presented AFE can be reconfigured for use in electropotential, bioimpedance, electrochemical, and photoelectrical modes. The advanced healthcare services based on multiparameter physiological biosignals can be easily implemented with these multimodal and highly reconfigurable features of the proposed system. The reconfigurable gain and input referred noise of the core instrumentation amplifier block are 25 dB to 52 dB, and 1 μV_RMS, respectively. The power consumption of the analog blocks in one readout channel is less than 52 μW. The reconfigurable capability among various modes of applications including electrocardiogram, blood glucose concentration, respiration, and photoplethysmography are shown experimentally.