Removal of multiple artifacts from ECG signal using cascaded multistage adaptive noise cancellers

Although cascaded multistage adaptive noise cancellers have been employed before by researchers for multiple artifact removal from the ElectroCardioGram (ECG) signal, they all used the same adaptive algorithm in all the cascaded multi-stages for adjusting the adaptive filter weights. In this paper, we propose a cascaded 4-stage adaptive noise canceller for the removal of four artifacts present in the ECG signal, viz. baseline wander, motion artifacts, muscle artifacts, and 60 Hz Power Line Interference (PLI). We have investigated the performance of eight adaptive algorithms, viz. Least Mean Square (LMS), Least Mean Fourth (LMF), Least Mean Mixed-Norm (LMMN), Sign Regressor Least Mean Square (SRLMS), Sign Error Least Mean Square (SELMS), Sign-Sign Least Mean Square (SSLMS), Sign Regressor Least Mean Fourth (SRLMF), and Sign Regressor Least Mean Mixed-Norm (SRLMMN) in terms of Signal-to-Noise Ratio (SNR) improvement for removing the aforementioned four artifacts from the ECG signal. We employed the LMMN, LMF, LMMN, LMF algorithms in the proposed cascaded 4-stage adaptive noise canceller to remove the respective ECG artifacts as mentioned above. We succeeded in achieving an SNR improvement of 12.7319 dBs. The proposed cascaded 4-stage adaptive noise canceller employing the LMMN, LMF, LMMN, LMF algorithms outperforms those that employ the same algorithm in the four stages. One unique and powerful feature of our proposed cascaded 4-stage adaptive noise canceller is that it employs only those adaptive algorithms in the four stages, which are shown to be effective in removing the respective ECG artifacts as mentioned above. Such a scheme has not been investigated before in the literature

Analysis and Evaluation of the Family of Sign Adaptive Algorithms

In this thesis, four novel sign adaptive algorithms proposed by the author were analyzed and evaluated for floating-point arithmetic operations. These four algorithms include Sign Regressor Least Mean Fourth (SRLMF), Sign Regressor Least Mean Mixed-Norm (SRLMMN), Normalized Sign Regressor Least Mean Fourth (NSRLMF), and Normalized Sign Regressor Least Mean Mixed-Norm (NSRLMMN). The performance of the latter three algorithms has been analyzed and evaluated for real-valued data only. While the performance of the SRLMF algorithm has been analyzed and evaluated for both cases of real- and complex-valued data. Additionally, four sign adaptive algorithms proposed by other researchers were also analyzed and evaluated for floating-point arithmetic operations. These four algorithms include Sign Regressor Least Mean Square (SRLMS), Sign-Sign Least Mean Square (SSLMS), Normalized Sign-Error Least Mean Square (NSLMS), and Normalized Sign Regressor Least Mean Square (NSRLMS). The performance of the latter three algorithms has been analyzed and evaluated for both cases of real- and complex-valued data. While the performance of the SRLMS algorithm has been analyzed and evaluated for complex-valued data only. The framework employed in this thesis relies on energy conservation approach. The energy conservation framework has been applied uniformly for the evaluation of the performance of the aforementioned eight sign adaptive algorithms proposed by the author and other researchers. In other words, the energy conservation framework stands out as a common theme that runs throughout the treatment of the performance of the aforementioned eight algorithms. Some of the results from the performance evaluation of the four novel sign adaptive algorithms proposed by the author, namely SRLMF, SRLMMN, NSRLMF, and NSRLMMN are as follows. It was shown that the convergence performance of the SRLMF and SRLMMN algorithms for real-valued data was similar to those of the Least Mean Fourth (LMF) and Least Mean Mixed-Norm (LMMN) algorithms, respectively. Moreover, it was also shown that the NSRLMF and NSRLMMN algorithms exhibit a compromised convergence performance for realvalued data as compared to the Normalized Least Mean Fourth (NLMF) and Normalized Least Mean Mixed-Norm (NLMMN) algorithms, respectively. Some misconceptions among biomedical signal processing researchers concerning the implementation of adaptive noise cancelers using the Sign-Error Least Mean Fourth (SLMF), Sign-Sign Least Mean Fourth (SSLMF), and their variant algorithms were also removed. Finally, three of the novel sign adaptive algorithms proposed by the author, namely SRLMF, SRLMMN, and NSRLMF have been successfully employed by other researchers and the author in applications ranging from power quality improvement in the distribution system and multiple artifacts removal from various physiological signals such as ElectroCardioGram (ECG) and ElectroEncephaloGram (EEG)

Adaptive Nonlinear RF Cancellation for Improved Isolation in Simultaneous Transmit-Receive Systems

This paper proposes an active radio frequency (RF) cancellation solution to suppress the transmitter (TX) passband leakage signal in radio transceivers supporting simultaneous transmission and reception. The proposed technique is based on creating an opposite-phase baseband equivalent replica of the TX leakage signal in the transceiver digital front-end through adaptive nonlinear filtering of the known transmit data, to facilitate highly accurate cancellation under a nonlinear TX power amplifier (PA). The active RF cancellation is then accomplished by employing an auxiliary transmitter chain, to generate the actual RF cancellation signal, and combining it with the received signal at the receiver (RX) low noise amplifier (LNA) input. A closed-loop parameter learning approach, based on the decorrelation principle, is also developed to efficiently estimate the coefficients of the nonlinear cancellation filter in the presence of a nonlinear TX PA with memory, finite passive isolation, and a nonlinear RX LNA. The performance of the proposed cancellation technique is evaluated through comprehensive RF measurements adopting commercial LTE-Advanced transceiver hardware components. The results show that the proposed technique can provide an additional suppression of up to 54 dB for the TX passband leakage signal at the RX LNA input, even at considerably high transmit power levels and with wide transmission bandwidths. Such novel cancellation solution can therefore substantially improve the TX-RX isolation, hence reducing the requirements on passive isolation and RF component linearity, as well as increasing the efficiency and flexibility of the RF spectrum use in the emerging 5G radio networks.Comment: accepted to IEE

Subband adaptive filtering for acoustic echo control using allpass polyphase IIR filterbanks

Published versio

Equalization of Third-Order Intermodulation Products in Wideband Direct Conversion Receivers

This paper reports a SAW-less direct-conversion receiver which utilizes a mixed-signal feedforward path to regenerate and adaptively cancel IM3 products, thus accomplishing system-level linearization. The receiver system performance is dominated by a custom integrated RF front end implemented in 130-nm CMOS and achieves an uncorrected out-of-band IIP3 of -7.1 dBm under the worst-case UMTS FDD Region 1 blocking specifications. Under IM3 equalization, the receiver achieves an effective IIP3 of +5.3 dBm and meets the UMTS BER sensitivity requirement with 3.7 dB of margin

Dirty RF Signal Processing for Mitigation of Receiver Front-end Non-linearity

Moderne drahtlose Kommunikationssysteme stellen hohe und teilweise gegensätzliche Anforderungen an die Hardware der Funkmodule, wie z.B. niedriger Energieverbrauch, große Bandbreite und hohe Linearität. Die Gewährleistung einer ausreichenden Linearität ist, neben anderen analogen Parametern, eine Herausforderung im praktischen Design der Funkmodule. Der Fokus der Dissertation liegt auf breitbandigen HF-Frontends für Software-konfigurierbare Funkmodule, die seit einigen Jahren kommerziell verfügbar sind. Die praktischen Herausforderungen und Grenzen solcher flexiblen Funkmodule offenbaren sich vor allem im realen Experiment. Eines der Hauptprobleme ist die Sicherstellung einer ausreichenden analogen Performanz über einen weiten Frequenzbereich. Aus einer Vielzahl an analogen Störeffekten behandelt die Arbeit die Analyse und Minderung von Nichtlinearitäten in Empfängern mit direkt-umsetzender Architektur. Im Vordergrund stehen dabei Signalverarbeitungsstrategien zur Minderung nichtlinear verursachter Interferenz - ein Algorithmus, der besser unter "Dirty RF"-Techniken bekannt ist. Ein digitales Verfahren nach der Vorwärtskopplung wird durch intensive Simulationen, Messungen und Implementierung in realer Hardware verifiziert. Um die Lücken zwischen Theorie und praktischer Anwendbarkeit zu schließen und das Verfahren in reale Funkmodule zu integrieren, werden verschiedene Untersuchungen durchgeführt. Hierzu wird ein erweitertes Verhaltensmodell entwickelt, das die Struktur direkt-umsetzender Empfänger am besten nachbildet und damit alle Verzerrungen im HF- und Basisband erfasst. Darüber hinaus wird die Leistungsfähigkeit des Algorithmus unter realen Funkkanal-Bedingungen untersucht. Zusätzlich folgt die Vorstellung einer ressourceneffizienten Echtzeit-Implementierung des Verfahrens auf einem FPGA. Abschließend diskutiert die Arbeit verschiedene Anwendungsfelder, darunter spektrales Sensing, robuster GSM-Empfang und GSM-basiertes Passivradar. Es wird gezeigt, dass nichtlineare Verzerrungen erfolgreich in der digitalen Domäne gemindert werden können, wodurch die Bitfehlerrate gestörter modulierter Signale sinkt und der Anteil nichtlinear verursachter Interferenz minimiert wird. Schließlich kann durch das Verfahren die effektive Linearität des HF-Frontends stark erhöht werden. Damit wird der zuverlässige Betrieb eines einfachen Funkmoduls unter dem Einfluss der Empfängernichtlinearität möglich. Aufgrund des flexiblen Designs ist der Algorithmus für breitbandige Empfänger universal einsetzbar und ist nicht auf Software-konfigurierbare Funkmodule beschränkt.Today's wireless communication systems place high requirements on the radio's hardware that are largely mutually exclusive, such as low power consumption, wide bandwidth, and high linearity. Achieving a sufficient linearity, among other analogue characteristics, is a challenging issue in practical transceiver design. The focus of this thesis is on wideband receiver RF front-ends for software defined radio technology, which became commercially available in the recent years. Practical challenges and limitations are being revealed in real-world experiments with these radios. One of the main problems is to ensure a sufficient RF performance of the front-end over a wide bandwidth. The thesis covers the analysis and mitigation of receiver non-linearity of typical direct-conversion receiver architectures, among other RF impairments. The main focus is on DSP-based algorithms for mitigating non-linearly induced interference, an approach also known as "Dirty RF" signal processing techniques. The conceived digital feedforward mitigation algorithm is verified through extensive simulations, RF measurements, and implementation in real hardware. Various studies are carried out that bridge the gap between theory and practical applicability of this approach, especially with the aim of integrating that technique into real devices. To this end, an advanced baseband behavioural model is developed that matches to direct-conversion receiver architectures as close as possible, and thus considers all generated distortions at RF and baseband. In addition, the algorithm's performance is verified under challenging fading conditions. Moreover, the thesis presents a resource-efficient real-time implementation of the proposed solution on an FPGA. Finally, different use cases are covered in the thesis that includes spectrum monitoring or sensing, GSM downlink reception, and GSM-based passive radar. It is shown that non-linear distortions can be successfully mitigated at system level in the digital domain, thereby decreasing the bit error rate of distorted modulated signals and reducing the amount of non-linearly induced interference. Finally, the effective linearity of the front-end is increased substantially. Thus, the proper operation of a low-cost radio under presence of receiver non-linearity is possible. Due to the flexible design, the algorithm is generally applicable for wideband receivers and is not restricted to software defined radios