K. Sivani

ICA-Based Improved DTCWT Technique for MA Reduction in PPG Signals With Restored Respiratory Information

In addition to estimation of arterial blood oxygen saturation (SpO2), pulse oximeters photoplethysmographic (PPG) signals can be well utilized for extracting the vital respiratory information. The motion artifacts (MA) in PPGs not only make SpO2 estimations unreliable and inaccurate but also make it difficult to extract respiratory information. Addressing this issue, for the first time, we propose a novel approach called “ICA-based improved dual-tree complex wavelet transform (I2DTCWT)” technique, for efficient reduction of MAs leaving the respiratory information undisturbed. The method makes use of source separation ability of independent component analysis (ICA) along with computationally efficient modified DTCWT processing. A prototype pulse oximeter was developed and performance analysis of DTCWT, modified DTCWT and I2DTCWT processing methods was carried out using PPG data recorded with intentionally created MAs (horizontal MA, vertical MA, and bending MA). Experimental results demonstrated the efficiency of DTCWT processing methods in restoring PPG morphology and proved that there is a significant improvement guaranteed in reducing MAs with the presented methods. Statistical performance is evaluated in terms of measures like signal-to-noise ratio, normalized root mean square error, and correlation analysis with correlation co-efficient measure. The I2DTCWT outperformed other DTCWT processing methods in respect of MA reduction and the computed spectra revealed that safe extraction of respiratory information is guaranteed from these MA reduced PPGs. The proposed method is also validated by comparing with the well established signal extraction technology of MASIMO pulse oximeters, for which the discrete saturation transform (DST) is the key element. The %SpO2 estimations from processed PPGs by the proposed method closely followed the estimations based on DST and were very close to that of clean sections of PPG. In addition, the proposed method resulted in less computation cost compared to the MASIMO SET. Digital volume pulse waveform contour analysis is also performed on MA reduced PPGs to validate PPG morphology and the conventional parameters are calculated for assessing the arterial stiffness.

Dual-tree complex wavelet transform for motion artifact reduction of PPG signals

Ever since the medical device pulse oximeter was invented, reliable and accurate estimation of arterial blood oxygen saturation (SpO2), based on the differential absorption of red/infrared light by hemoglobins, has been a challenging task. The Photoplethysmogram (PPG) waveform, also known as the “pulse oximetry waveform”, is well recognized for its use in pulse oximetry applications for the estimation of SpO2 and can be obtained noninvasively and continuously in a comfortable manner using low cost & portable PPG sensors. Inaccuracy in the estimation of SpO2 may prevail due to the motion artifacts (MA) corruption in the detected PPG signals by the intentional or unintentional movements of a patient. The MA noise corruption is unavoidable while recording the PPGs because of a very small pulsatile component in PPG (0.1% of total signal amplitude) and it can be reduced by suitable processing of the PPG signals. In this paper, an approach for motion artifact (MA) reduction of photoplethysmographic (PPG) signals based on the concept of dual-tree complex wavelet transform technique is proposed. Experimental results revealed that DTCWT processing of MA corrupted PPGs outperformed the db10 wavelet processing for MA reduction of PPG signals and can be referred as best suitable MA reduction technique for pulse oximetry applications.

HHT based signal decomposition for reduction of motion artifacts in photoplethysmographic signals

Motion artifact (MA) corrupted photoplethysmographic (PPG) signals are the main source of errors in the estimation of arterial blood oxygen saturation (SpO2) in pulse oximeters. For addressing the issue of MA reduction in pulse oximetry applications, the physical origins of PPG signals are to be explored and effective signal processing technique may be employed. In this paper, we propose simple and efficient empirical mode decomposition (EMD) method based on the Hilbert-Huang Transform (HHT) for MA reduction in PPG signals. EMD is relatively a new time-frequency analysis technique having wide range of applications. EMD uses HHT calculation to handle non-linear and non-stationary data to find the intrinsic mode function (IMF) components and analyze the variations in power spectrum over time. The efficacy of the proposed method is proved by comparing it with well known wavelet transform based MA reduction method for the PPG data recorded with different MA (Horizontal, Vertical and Bending motion of finger). While statistical analysis demonstrated the robustness of the method, the SpO2 estimations from MA reduced PPG signals by proposed method being very close to the actual ones, make it reliable for pulse oximetry applications.

E 2 MD for reduction of motion artifacts from photoplethysmographic signals

Most of the intensive care units (ICU) are equipped with commercial pulse oximeters for monitoring arterial blood oxygen saturation (SpO2) and pulse rate (PR). Photoplethysmographic (PPG) data recorded from pulse oximeters usually corrupted by motion artifacts (MA), resulting in unreliable and inaccurate estimated measures of SpO2. In this paper, a simple and efficient MA reduction method based on Ensemble Empirical Mode Decomposition (E2MD) is proposed for the estimation of SpO2 from processed PPGs. Performance analysis of the proposed E2MD is evaluated by computing the statistical and quality measures indicating the signal reconstruction like SNR and NRMSE. Intentionally created MAs (Horizontal MA, Vertical MA and Bending MA) in the recorded PPGs are effectively reduced by the proposed one and proved to be the best suitable method for reliable and accurate SpO2 estimation from the processed PPGs.

Hardware implementation of OFDM transceiver using FPGA

Latest developments in the field of wireless communication systems require a technology which should be accurate, reliable and adopt high data rate transmission across the systems. Orthogonal frequency division multiplexing (OFDM) technique will provide good resistance to multi path interference and inter symbol interference (ISI) caused by broadband multi carrier (MC) high data rate wireless systems Conventional OFDM transceiver system is formed by considering the orthogonality among the subcarriers achieved by the use of orthogonal discrete Fourier transform (DFT). The DFT can be implemented using computational efficient fast Fourier transform (FFT) algorithms. A new orthogonal transform developed by Hirschman, Hirschman optimal transform (HOT), the basis function of HOT is derived from DFT and it can be efficiently implemented using the same FFT algorithms. A computationally efficient HOT based OFDM was developed by the authors and reconfigurable hardware prototyping of the same was considered here for practical implementation using FPGA. Even though, similar bit error rate (BER) was reported in simulations for both DFT and HOT, the HOT is computationally attractive. FPGA implementation reveals the efficacy of the proposed HOT based OFDM transceiver in terms the computational complexity.

On the use of singular spectrum analysis for OFDM channel estimation

Over the last decade or so, the data rate and spectrum efficiency of wireless communication systems has been significantly improved with the advent of multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) technology. In order to operate in the most effective way, OFDM-based communication systems need accurate channel estimation. The channel estimation in OFDM communication systems becomes a challenging problem ever since from its inception. Singular Spectrum Analysis (SSA) has proven to be a flexible method for the analysis of time-series data, because of the decomposition derived from signal itself. Empirical orthogonal functions (EOFs) are derived from lag matrix of the time series. In this paper, the OFDM channel estimation problem is being addressed using SSA. The performance of method is observed in terms of bit error rate (BER) calculations for Rayleigh and Rician fading channels. A lower BER compared to least squares (LS) and LMMSE methods demonstrated the efficacy of the proposed method.

A novel approach for power-gating technique with Improved Efficient Charge Recovery Logic

In this paper, a novel approach for power gating technique with Improved Efficient Charge Recovery Logic (IECRL) introduced. An Asynchronous Fine-Grain Power-Gated Logic Technique (AFPLT) developed by Improved Efficient Charge Recovery Logic, which gives logic function to the next succeeding stage. In the AFPLT circuit, IECRL gates acquires power from hand shake controller and become active only when performing required executions. In active mode the leakage currents are suppressed by providing infinite resistance path through the NMOS transistor in pull-up network. In in-active mode IECRL gates are not taken any amount of power, this gives negligible leakage power dissipation. Its maximum power saving against ECRL is up to 82.88% at 100 MHZ input data rate. Similarly the power saving against static CMOS logic is up to 92.68% at 100 MHZ. In AFPLT circuit handshake controller is used to provide power to the IECRL gate and which performs the hand shaking with the neighboring stages. In order to reduce the energy dissipation, the PCR mechanism is used in AFPLT pipeline structure. PCR mechanism is used to transfer the charge of discharging phase of IECRL gate to evaluate phase of the another IECRL gate. Early discharging of IECRL gate can be provided by enhanced C-element called C*-element.

Use of complex EMD generated noise reference for adaptive reduction of motion artifacts from PPG signals

Different signal processing methods are proposed for addressing the motion artifact (MA) related issues in pulse oximetry applications. MA corruption due to voluntary or involuntary movements of patient, while recording the photoplethysmographic (PPG) data using pulse oximeter, is the main source of error in the estimation of arterial blood oxygen saturation (SpO2). In this paper, for addressing the issue of MA reduction in recorded PPG data, the physical origins of PPG signals are explored and complex empirical mode decomposition (CEMD) adaptive filter is proposed. The novelty of the proposed filtering method lies in the fact that instead of using additional hardware for acquisition of noise reference signal, representing MA noise, for adaptive filtering process, is generated internally from the MA corrupted PPG signal using CEMD technique. The generated noise reference signal is then applied to the adaptive step-size least mean squares (AS-LMS) algorithm for artifact removal. The merit of the proposed filtering method is proved by comparing it with Daubechies wavelet transform (Db10) based MA reduction method for the PPG data recorded with different MA (Horizontal, Vertical and Bending motion of finger). Statistical results demonstrated the robustness of the proposed method and SpO2 parameter calculations from MA reduced PPG signals proved the efficacy of method in accurate and reliable estimation of SpO2.

A tunnel field effect transistor is a substitute for ultra-low power applications

As Moors law is concerned, down scaling of conventional CMOS technology results in, rapidly approaching fundamental limits. Alternative device structures are constantly proposed to substitute the traditional CMOS type devices. That type of device is a gated reverse-biased structure, commonly referred to as Tunnel Field-Effect Transistor (TFET). This device is particularly suitable for ultra-low-power applications. The most prominent feature of TFETs is their capacity for producing an inverse sub-threshold swing (SS) smaller than the 60 mV/decade thermal limit (at 300 K) of conventional inversion mode MOSFETs. Sub-thermal SS is achievable because, the drain current in TFETs is produced by carrier injection from source to channel which is predominantly governed by quantum mechanical band-to-band tunnelling (BTBT), rather than by diffusion as in MOSFETs. In, this paper we will show the silvaco TCAD simulation results for both conventional MOSFET and Tunnel field effect transistor. From the results, it is evident that TFET is suitable for ultra-low power applications.

A novel approach for power reduction in asynchronous circuits by using AFPT

In this paper, a novel approach for power reduction in asynchronous circuits by using Asynchronous Fine-Grain Power-Gated Technique (AFPT) introduced. An AFPT developed by Improved Efficient Charge Recovery Logic (IECRL), which gives logic function to the next succeeding stage. In the AFPT circuit, IECRL gates attains power from hand shake controller and become active only when executing required calculations. In active mode the leakage currents are reduced by providing high resistance path through the NMOS transistor in pull-up network. In inactive mode IECRL gates are not taken any amount of power, this gives insignificant leakage power dissipation. Its maximum power saving against ECRL is up to 89.35%. In AFPT circuit handshake controller used to provide power to the IECRL gate and which handles the hand shaking with the neighboring stages. In the AFPT circuit PCR mechanism is used to transfer the charge of discharging phase of IECRL gate to evaluate phase of the another IECRL gate, to reduce the energy dissipation. Early discharging of IECRL gate can be achieved by using modified C-element called C*-element.