Input Waveform Research Articles

A Novel Wearable Flexible Dry Electrode Based on Cowhide for ECG Measurement.

The electrocardiogram (ECG) electrode, as a sensor, is an important part of the wearable ECG monitoring device. Natural leather is rarely used as the electrode substrate. In this paper, wearable flexible silver electrodes based on cowhide were prepared by sputtering and brush-painting. A signal generator, oscilloscope, impedance test instrument, and ECG monitor were used to build the test platform evaluating the performance of electrodes with six subjects. The lossless waveform transmission can be achieved with our electrodes. Therefore, the Pearson’s correlation coefficient calculated with input waveform and output waveform of the electrodes based on the top grain layer (GLE) and the split layer (SLE) of cowhide were 0.997 and 0.998 at 0.1 Hz respectively. The skin electrode impedance (Z) was tested, and the parameters of the equivalent circuit model of the skin electrode interface were calculated by a fitting method, indicating that the Z of the prepared electrodes was comparable with the standard gel electrode when the skin is moist enough. The signal-to-noise ratio of the ECG of the GLE and the SLE were 1.148 and 1.205 times that of the standard electrode in the standing posture, which meant the ECG measured by our electrodes was basically consistent with that measured by the standard electrode.

Fast pulse shaping for a novel gated electron mirror.

We present the design and prototype of a switchable electron mirror, along with a technique for driving it with an arbitrary pulse shape. We employ a general technique for electronic pulse-shaping, where high fidelity of the pulse shape is required, but the characteristics of the system, which are possibly nonlinear, are not known. This driving technique uses an arbitrary waveform generator to pre-compensate the pulse, with a simple iterative algorithm used to generate the input waveform. This is a broadly applicable, general method for arbitrary pulse shaping. Driving our switchable electron mirror with a flat-top pulse, we demonstrate an improvement in rms error of roughly two orders of magnitude compared to an uncompensated waveform. Our results demonstrate the feasibility of high fidelity waveform reproduction in the presence of nonidealities, with immediate applications in the realization of novel electron optical components.

A design of 1 to 4 GHz broadband high‐efficiency power amplifier with two‐way concurrent active load modulation method

Active load modulation and harmonic injection can be used to boost the power amplifier's (PA) efficiency, but these techniques must add a fundamental external source or a harmonic generator. In this paper, a two-way power amplifier architecture is introduced to extend high-efficiency operation bandwidth by utilizing concurrent active load modulation with a waveform mapping method. Active load modulation is realized in between the two branches with the aid of independent input amplitude and phase control. Based on a calculated waveform database, high-efficiency operations for both transistors from 1 to 4 GHz are designed in a self-defined optimization platform considering waveform distance and input parameters. Finally, this PA is fabricated and measured to offer 41.6 to 45.0 dBm power, 8.2 to 11.7 dB gain, and 56% to 89% drain efficiency from 0.85 to 3.85 GHz.

A Novel Design Method of SOF for InP DHBT ECL and CML Static Frequency Dividers

In this letter, we present a novel analysis and design approach of self-oscillation frequency (SOF) for 0.8-μm indium phosphide (InP) double-heterojunction bipolar transistor (DHBT) emitter-coupled logic (ECL) and current-mode logic (CML) static frequency dividers. SOF of ECL and CML dividers is designed to be the maximum value after theoretical analysis and multiparameter optimization. The results show that the SOF of the ECL and CML divider is 62 and 37.5 GHz, respectively. With sinusoidal waveform input, the operating frequency range of the ECL divider is from 0.1 to 65 GHz, and CML is from 0.1 to 55 GHz, while the cut-off frequency f <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</sub> is 150 GHz. For ECL, the f <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</sub> utilization of SOF (SOF /f <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</sub> ) is 0.413, and CML is 0.25. These are the maximum SOF results that can be designed for the two dividers under the same design conditions.

Speaker separation in realistic noise environments with applications to a cognitively-controlled hearing aid

Future wearable technology may provide for enhanced communication in noisy environments and for the ability to pick out a single talker of interest in a crowded room simply by the listener shifting their attentional focus. Such a system relies on two components, speaker separation and decoding the listener’s attention to acoustic streams in the environment. To address the former, we present a system for joint speaker separation and noise suppression, referred to as the Binaural Enhancement via Attention Masking Network (BEAMNET). The BEAMNET system is an end-to-end neural network architecture based on self-attention. Binaural input waveforms are mapped to a joint embedding space via a learned encoder, and separate multiplicative masking mechanisms are included for noise suppression and speaker separation. Pairs of output binaural waveforms are then synthesized using learned decoders, each capturing a separated speaker while maintaining spatial cues. A key contribution of BEAMNET is that the architecture contains a separation path, an enhancement path, and an autoencoder path. This paper proposes a novel loss function which simultaneously trains these paths, so that disabling the masking mechanisms during inference causes BEAMNET to reconstruct the input speech signals. This allows dynamic control of the level of suppression applied by BEAMNET via a minimum gain level, which is not possible in other state-of-the-art approaches to end-to-end speaker separation. This paper also proposes a perceptually-motivated waveform distance measure. Using objective speech quality metrics, the proposed system is demonstrated to perform well at separating two equal-energy talkers, even in high levels of background noise. Subjective testing shows an improvement in speech intelligibility across a range of noise levels, for signals with artificially added head-related transfer functions and background noise. Finally, when used as part of an auditory attention decoder (AAD) system using existing electroencephalogram (EEG) data, BEAMNET is found to maintain the decoding accuracy achieved with ideal speaker separation, even in severe acoustic conditions. These results suggest that this enhancement system is highly effective at decoding auditory attention in realistic noise environments, and could possibly lead to improved speech perception in a cognitively controlled hearing aid.

Deep Learning Denoising Applied to Regional Distance Seismic Data in Utah

ABSTRACTSeismic waveform data are generally contaminated by noise from various sources. Suppressing this noise effectively so that the remaining signal of interest can be successfully exploited remains a fundamental problem for the seismological community. To date, the most common noise suppression methods have been based on frequency filtering. These methods, however, are less effective when the signal of interest and noise share similar frequency bands. Inspired by source separation studies in the field of music information retrieval (Jansson et al., 2017) and a recent study in seismology (Zhu et al., 2019), we implemented a seismic denoising method that uses a trained deep convolutional neural network (CNN) model to decompose an input waveform into a signal of interest and noise. In our approach, the CNN provides a signal mask and a noise mask for an input signal. The short-time Fourier transform (STFT) of the estimated signal is obtained by multiplying the signal mask with the STFT of the input signal. To build and test the denoiser, we used carefully compiled signal and noise datasets of seismograms recorded by the University of Utah Seismograph Stations network. Results of test runs involving more than 9000 constructed waveforms suggest that on average the denoiser improves the signal-to-noise ratios (SNRs) by ∼5 dB, and that most of the recovered signal waveforms have high similarity with respect to the target waveforms (average correlation coefficient of ∼0.80) and suffer little distortion. Application to real data suggests that our denoiser achieves on average a factor of up to ∼2–5 improvement in SNR over band-pass filtering and can suppress many types of noise that band-pass filtering cannot. For individual waveforms, the improvement can be as high as ∼15 dB.

Safety Analysis of the Running Train under Earthquake Dynamic Disturbance

Focusing on the safe operation of rail transit during earthquakes, the finite element method is used to construct a wheel-track-subgrade dynamics model in this study. Through spring-damper units, the relationship between the rail and the track slab and the connection between the track slab and the subgrade are established. A method for establishing a viscoelastic artificial boundary is proposed. Four seismic waves—the Tianjin wave, the El Centro wave, the Taft wave, and the Qian’an wave—are selected as the seismic input waveforms, and only the impact of the lateral ground motion on the wheel-track-subgrade system is considered. In this paper, the ground motion problem is transformed into a wave source problem, the seismic input is transformed into an equivalent load acting on the artificial boundary, and the wave input of the viscoelastic artificial boundary is realized. The normalization method is used to process the seismic waves, and a method that converts the input of the seismic waves into equivalent loads is proposed. The changing laws of different dynamic response indexes under the influence of the four waveforms are studied. Under the action of the Tianjin wave, the wheel-rail dynamic response is very violent near the acceleration peak, whereas, after the peak, all dynamic response indexes are within a safe range. Under the effect of the El Centro wave, the collision between the wheel and the track is relatively violent, and the train is already in a dangerous state. Under the action of the Taft wave, due to the sudden action of the peak ground motion acceleration, the displacement between the wheel and the track increases instantaneously, causing the train to derail. Under the action of the Qian’an wave, the force between the wheel and rail changes approximately linearly with respect to the frequency of the ground motion, and all dynamic response indexes are within a safe range. The vibration intensity of the four seismic waves is amplified by an intensity expansion factor. Except for the Tianjin wave, the amplified seismic wave has a greater impact on safe train operations. This paper can provide a reference for research on the running safety of trains under similar dynamic disturbance conditions.

Friction pendulum test and parameter optimization for the vibration reduction of a 100 kv isolating switch

An earthquake is a natural disaster with a high destructive force. According to previous history, a great many power grid facilities are damaged during the earthquake, and the damage to electrical equipment in substations are often very serious. This article takes the isolating switch in the substation as an experimental object. Firstly, the friction pendulum for vibration isolation is designed and manufactured according to the numerical simulation, and then the seismic test and vibration isolation test of the high voltage isolating switch are designed. The input waveforms and input acceleration intensities of the seismic test were designed experimentally. The test data of the isolating switch under the seismic condition and the vibration isolation condition with the friction pendulum vibration isolation system installed are mainly investigated. The measured acceleration of the top of the isolating switch bracket is used to compare and analyze the vibration isolation performance of the friction pendulum. Then, it can be seen that the friction pendulum system has the vibration isolation effects on the isolating switch. Especially, the isolation effects of friction pendulum are better when the acceleration intensity become higher. In order to obtain a better curvature radius and friction coefficient of the friction pendulum, based on the results of this test, the systematically numerical simulation tests for optimization on the friction pendulum vibration isolation system are conducted. The simulated top displacement of the isolating switch and the stress change of the root of the porcelain bottle were obtained. By comparing the vibration isolating performance of the friction pendulum under different parameters, numerical simulations show that the vibration isolation performance of the friction pendulum is better when the radius of curvature is 1200 mm and the friction coefficient is 0.04. The numerical results demonstrate that reasonable design of friction pendulum parameters can play a significant role in isolating vibration for power equipment.

Signal Conditioning for Selective OFDM SWIPT Systems

The conversion efficiency of a harvesting component can hinder device self-sustainability. Countering this inefficiency can be a rigorous task that requires either a modified input waveform at the harvesting component or an improved design of the harvesting component itself. This paper considers a selective orthogonal frequency division multiplexing (OFDM) system that is designed for simultaneous wireless information and power transfer (SWIPT). This paper introduces an enhanced transmitter architecture designed to condition the transmit signal for improved conversion efficiency. Leveraging the structure of the OFDM signal, the cyclic prefix plus a portion of the information signal are conditioned and used for harvesting. Then, a rectifier model and prototypes are designed to further improve conversion efficiency. System performance is evaluated with the analytical derivation of the rate-energy (R-E) tradeoff and an optimized transmission strategy for system self-sustainability. Monte Carlo simulations show increased energy gains and full self-sustainability with the introduction of signal conditioning.

Dynamic Voltage Restorer to Maintain Constant Voltage at Load

This paper is used for decrease the power quality problems in electrical distribution. Sometimes potential is not stable so it causes potential disturbances in power system then it produces harmonics in the system. Therefore, this gained with a concept called DVR. This controls the potential increase and decrease the distribution. Because of these problems, there is a possibility to draw more power and reduction in the devices. DVR saves the power with potential injections which cause effect phase and also the shapes of the input waveform. In this project, we are using a lead acid battery device as energy storage element and also PWM process useful for trigger the circuits. It will be operated in unsymmetrical potential conditions and remains ideal in normal conditions. It will set the potential into system at a rated value of the quantity and cycles per second. So that it is regained the receiving side potential to accurate range. This process is used to compare the decrease in potential, increase in potential and power frequencies in the system. To decreases economic problems this project is helpful. If the potential is highly changes, the machine will get destroy it can have a severe economic problem on residential areas and industries. Which is help to improve quality of powering issues in the future power system operations.

Optical difference in the frequency domain to suppress disturbance for wearable electronics.

Measurements based on optics offer a wide range of unprecedented opportunities in the biological application due to the noninvasive or non-destructive detection. Wearable skin-like optoelectronic devices, capable of deforming with the human skin, play significant roles in future biomedical engineering such as clinical diagnostics or daily healthcare. However, the detected signals based on light intensity are very sensitive to the light path. The performance degradation of the wearable devices occurs due to device deformation or motion artifact. In this work, we propose the optical difference in the frequency domain of signals for suppressing the disturbance generated by wearable device deformation or motion artifact during the photoplethysmogram (PPG) monitoring. The signal processing is simulated with different input waveforms for analyzing the performance of this method. Then we design and fabricate a wearable optoelectronic device to monitor the PPG signal in the condition of motion artifact and use the optical difference in the frequency domain of signals to suppress irregular disturbance. The proposed method reduced the average error in heart rate estimation from 13.04 beats per minute (bpm) to 3.41 bpm in motion and deformation situations. These consequences open up a new prospect for improving the performance of the wearable optoelectronic devices and precise medical monitoring in the future.

Time-Domain Analysis of Retarded Partial Element Equivalent Circuit Models Using Numerical Inversion of Laplace Transform

Full-wave time-domain computational electromagnetic (CEM) solvers, which are integral equation (IE)-based, may suffer from what is called “late-time instability” problems. This unstable behavior occurs for CEM solvers for very fast rise-time input signals. A multitude of techniques has been devised by researchers over the years to solve the problem. In this article, we pursue an approach for the stable solution of full-wave partial element equivalent circuit (PEEC) models for fast-rising input waveforms. In particular, step and impulse response will be considered that are the most challenging from a stability point of view. For the solver part, a conventional full-wave PEEC code is used that requires one to use retarded partial elements. Unfortunately, a PEEC, as well as impedance Z-(method of moment) solvers using suitable numerical time-stepping methods have stability problems, especially for fast rising impulse or step inputs. An important step forward is achieved in this work by providing a larger class of stable solutions well above the stability achieved for time-stepping methods in the last 50 years. The time-domain stability is achieved by replacing the stepping integration methods with a numerical inversion of Laplace transform (NILT) technique. The NILT transform starts out by applying it to a frequency-domain PEEC solution. The surprising result is that the NILT-based method has a variable time-dependent bandwidth that is advantageous for the full-wave IE solution stability. In this article, we give several examples that show that a PEEC-NILT solution provides accurate and stable results for impulse, step- and piece-wise linear input waveforms.

Optimization of multi-electrode implant configurations and programming for the delivery of non-ablative electric fields in intratumoral modulation therapy.

Application of low intensity electric fields to interfere with tumor growth is being increasingly recognized as a promising new cancer treatment modality. Intratumoral modulation therapy (IMT) is a developing technology that uses multiple electrodes implanted within or adjacent tumor regions to deliver electric fields to treat cancer. In this study, the determination of optimal IMT parameters was cast as a mathematical optimization problem, and electrode configurations, programming, optimization, and maximum treatable tumor size were evaluated in the simplest and easiest to understand spherical tumor model. The establishment of electrode placement and programming rules to maximize electric field tumor coverage designed specifically for IMT is the first step in developing an effective IMT treatment planning system. Finite element method electric field computer simulations for tumor models with 2 to 7 implanted electrodes were performed to quantify the electric field over time with various parameters, including number of electrodes (2 to 7), number of contacts per electrode (1 to 3), location within tumor volume, and input waveform with relative phase shift between 0 and 2π radians. Homogeneous tissue specific conductivity and dielectric values were assigned to the spherical tumor and surrounding tissue volume. In order to achieve the goal of covering the tumor volume with a uniform threshold of 1V/cm electric field, a custom least square objective function was used to maximize the tumor volume covered by 1V/cm time averaged field, while maximizing the electric field in voxels receiving less than this threshold. An additional term in the objective function was investigated with a weighted tissue sparing term, to minimize the field to surrounding tissues. The positions of the electrodes were also optimized to maximize target coverage with the fewest number of electrodes. The complexity of this optimization problem including its non-convexity, the presence of many local minima, and the computational load associated with these stochastic based optimizations led to the use of a custom pattern search algorithm. Optimization parameters were bounded between 0 and 2π radians for phase shift, and anywhere within the tumor volume for location. The robustness of the pattern search method was then evaluated with 50 random initial parameter values. The optimization algorithm was successfully implemented, and for 2 to 4 electrodes, equally spaced relative phase shifts and electrodes placed equidistant from each other was optimal. For 5 electrodes, up to 2.5cm diameter tumors with 2.0V, and 4.1cm with 4.0V could be treated with the optimal configuration of a centrally placed electrode and 4 surrounding electrodes. The use of 7 electrodes allow for 3.4cm diameter coverage at 2.0V and 5.5cm at 4.0V. The evaluation of the optimization method using 50 random initial parameter values found the method to be robust in finding the optimal solution. This study has established a robust optimization method for temporally optimizing electric field tumor coverage for IMT, with the adaptability to optimize a variety of parameters including geometrical and relative phase shift configurations.

Modeling of Input Nonlinearity and Waveform Engineered High-Efficiency Class-F Power Amplifiers

A comprehensive time-domain modeling and a generalized design methodology for input and output waveform engineered Class-F power amplifiers (PAs) are presented in this article. A closed-form relationship between input nonlinearity and second harmonic source impedance ( $Z_{\mathrm {2S}}$ ) termination is presented from which efficiency and output power performance are predicted for Class-F PAs. The maximum, minimum, and safe $Z_{\mathrm {2S}}$ design space for a Class-F PA are identified. Moreover, the derived design equations show that the typical fundamental load of a Class-F PA operation must be re-engineered in the presence of input nonlinearity in order to achieve optimum efficiency performance. The theoretical analyses are first validated with pulsed vector load–pull (VLP) measurements with a gallium nitride (GaN) 2 mm device. Then, high-power (210 W) GaN 24-mm devices with in-package $Z_{\mathrm {2S}}$ terminations are implemented. Measurement results with the new source and load design space show efficiency improvement of 4.4% compared to the nominal Class-F PA.

Deep learning-based late fusion of multimodal information for emotion classification of music video

Affective computing is an emerging area of research that aims to enable intelligent systems to recognize, feel, infer and interpret human emotions. The widely spread online and off-line music videos are one of the rich sources of human emotion analysis because it integrates the composer’s internal feeling through song lyrics, musical instruments performance and visual expression. In general, the metadata which music video customers to choose a product includes high-level semantics like emotion so that automatic emotion analysis might be necessary. In this research area, however, the lack of a labeled dataset is a major problem. Therefore, we first construct a balanced music video emotion dataset including diversity of territory, language, culture and musical instruments. We test this dataset over four unimodal and four multimodal convolutional neural networks (CNN) of music and video. First, we separately fine-tuned each pre-trained unimodal CNN and test the performance on unseen data. In addition, we train a 1-dimensional CNN-based music emotion classifier with raw waveform input. The comparative analysis of each unimodal classifier over various optimizers is made to find the best model that can be integrate into a multimodal structure. The best unimodal modality is integrated with corresponding music and video network features for multimodal classifier. The multimodal structure integrates whole music video features and makes final classification with the SoftMax classifier by a late feature fusion strategy. All possible multimodal structures are also combined into one predictive model to get the overall prediction. All the proposed multimodal structure uses cross-validation to overcome the data scarcity problem (overfitting) at the decision level. The evaluation results using various metrics show a boost in the performance of the multimodal architectures compared to each unimodal emotion classifier. The predictive model by integration of all multimodal structure achieves 88.56% in accuracy, 0.88 in f1-score, and 0.987 in area under the curve (AUC) score. The result suggests human high-level emotions are automatically well classified in the proposed CNN-based multimodal networks, even though a small amount of labeled data samples is available for training.

Phase characteristics of E class amplifier with various output networks

Phase shift of E class amplifiers with classical output network and output network that satisfies E class loading impedance conditions twice in the frequency band were studied by simulation and experimentally. The phase shift across switch in nominal operation mode was investigated analytically. The phase shift across switch in suboptimal class E operation mode that occurs while altering the operation frequency was investigated as well. The simulation method was the harmonic balance analysis using the switch model that considers the structure of power MOSFET device, namely, the existence of antiparallel diode pair that alters the switch current waveform. The input and transition capacitances of the transistor were considered. Experimental measurement of the phase shift was performed utilizing the recorded digitized waveforms of the switch input and output voltages by computing the phases of the voltages’ first harmonics with the help of Fast Fourier Transform. It was observed that characteristics of phase shift at switch output and amplifier output are dependent on the kind of load network. The relationship between the phase shift at the switch and hodograph of the loading impedance was demonstrated. For the network with double fulfilment of class E conditions that has a loop in the loading impedance hodograph the switch phase shift dependency has an extremum, which provides an opportunity to obtain the same phase shift at two frequencies within the operating frequency band. That facilitates control of the phase-frequency characteristic and the group delay of the amplifier. Knowledge of the phase-frequency dependency simplifies the conditions for calculation of the phase shift in the feedback network. The obtained results are useful for design of class E oscillator operating in a wide frequency band.

Optimization of an Input Filter for a Three-Phase Matrix Converter

This study includes an optimization of the input filter for three-phase matrix converters. An input filter effects on the power factor while improving the Total Harmonic Distortion (THD) of the input current. Unity power factor being one of the most important advantages of matrix converters will be eliminated if this is not taken into consideration. For this reason, an optimization was used by taking both parameters into consideration in this study. A Particle Swarm Optimization (PSO) algorithm was used in order to reduce the THD of the input current about 3% with nearly unit power factor as 0.985. The first of the optimization objective functions is to decrease the THD of the input current, and the second is to increase the power factor. The matrix converter was used for a constant frequency and modulation by using the switching strategy of Venturini Method and feeds an RL load. The optimized input filter was analyzed in detail in MATLAB/SimPowerSystems environment and examined in the results. Additionally, FFT spectra of the input and output waveforms are given in the results. Thus, the most suitable input filter was obtained for this system.

New Investigations in Play Static Hysteresis Model for Increased Accuracy and Robustness

This article presents an evolution of the inverse Play model to reconstruct static hysteresis from a flux density waveform input. It is to be combined with dynamic and 2-D or 3-D models to estimate the complete iron loss in electrical machines. In the first part of the article, the article shows the significant improvement in the original inverse Play model accuracy obtained by modifying the characterization measurement methodology, the subsequent discretization, and the identification method. Thereafter, a new version of the Play model, named “continuous,” is introduced, which allowed a significant gain in performance at the expense of greater computation time for the identification process. Both model versions have been validated through experimental comparison. All measurements, characterization, and validation have been done according to IEC60404-2 on two different test laboratories. The studied material is non-oriented SiFe M400-50A electrical steel.

Open-Current Vector Based SVM Strategy of Sparse Matrix Converter for Common-Mode Voltage Reduction

The concept of open-current vector for sparse matrix converter is put forward along with its application constraints in this article. Based on the open-current vector, an improved space vector modulation (SVM) strategy is proposed to reduce the peak magnitude of common-mode voltage (CMV) by 42.3% without sacrificing the performance of input and output waveforms and the voltage transfer ratio (VTR). First, the application constraints and common-mode equivalent circuit of the open-current vector in the rectifier stage of the sparse matrix converter are analyzed. After that, in accordance with the principle of minimum switching action and two adjacent active vector synthesis, the improved SVM strategy used a suitable open-current vector instead of the active-current vector in the rectifier stage when the zero-voltage vector is used in the inverter stage, which contributes to CMV reduction. The improved SVM strategy not only reduces the peak magnitude of the CMV, but also ensures that the performance of input and output waveforms and the VTR are the same with those of traditional SVM. Finally, the effectiveness of the improved SVM strategy is verified by simulation and experiments.

A Review of Photoplethysmography-based Physiological Measurement and Estimation, Part 2: Multi-input Methods.

Photoplethysmography can be used to estimate many physiological parameters based on features extracted from the measured waveform. Following the single parameter estimations that have been reviewed in part 1 of this paper, we here review methods where the waveform is used in conjunction with other measured physiological signals. Being a low-cost, non-invasive, and user friendly technique, many PPG-based physiological data extraction methods are being researched. The parameters reviewed that can be estimated using the PPG waveform plus additional inputs include cardiac output, blood pressure, venous function assessment, blood oxygen saturation, and fetal heart rate and fetal oxygen saturation. The different processing techniques, algorithms and methods are reviewed in addition to providing a comparison of results with the reference standards to validate the different methods. Future research considerations for each parameter estimation are also discussed. This paper could be helpful for future research on PPG based wearable devices for physiological multi-parameter estimations.