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Amit manocha

Thapar University, Patiala, Electrical and instrumentation, ph.d research scholar

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Dr. Amit Kumar Manocha is currently working as an Associate Professor and Head in the Department of Electrical & Electronics Engineering at Maharaja Agrasen University, Baddi, Himachal Pradesh, India. He has over 10 years of experience in Academia. He has completed his M.E. And Ph.D in 2006 and 2015 respectively. His Ph.D research work was focused on enhanced ischemia classifier for ECG signals.

Dr. Manocha had successfully organized two International Conferences (in the capacity of Convener and Editor in-chief for publishing proceedings) and many Workshops & Seminars. He has also organized three special sessions in reputed International conferences like, IEEE & ACM. He also been invited as session chair in many international conferences. His area of research includes biomedical signal processing and control systems. He has published 30 research papers in peer reviewed journals and conferences of International and national repute. Prof. Manocha is associated with various International conference committees as a TPC member. He is also serving various journals as editorial board member and as a reviewer.
Supervisors: Dr. Mandeep Singh, Dr. Lillie Dewan, and Dr. Mukhtiar Singh

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Jordan University of Science and Technology

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University of Tennessee Knoxville

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IIT Bhubaneswar

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Papers by Amit manocha

accurate delineation of ECG characteristics points using window search and wavelet transform

Automatic and accurate delineation of ECG characteristic's points play a pivotal role in computer... more Automatic and accurate delineation of ECG characteristic's points play a pivotal role in computerized electrocardiography for prognosis of heart diseases. The paper presents an algorithm research for removal of artifacts& noises and delineation of ECG characteristics points based on wavelet transform. The multi-resolution, thresholding, minima/maxima pairs with window searching feature of wavelet transform has been used for the implementation of algorithm. The measured values of characteristics waves of ECG are validated for European ST-T database records. The result shows over 100% accurate detection rate in terms of amplitude and occurrence with respect to time for P wave, QRS complex & T wave and also can be easily distinguished even contaminated with baseline drift and artifacts.

Application of Digital Signal Processing to ECG Signal

Improved Method for ECG Denoising Using Wavelet Transform

The Electrocardiogram (ECG) is a recording of heart’s contractile activity in electrical potentia... more The Electrocardiogram (ECG) is a recording of heart’s contractile activity in electrical potentials which is consist of P, QRS and T waves. The ECG is recorded by placing the electrodes at specific positions on patient’s skin. The artifacts are generated either by patient's motion or by other electrical devices attached during the recording. Two important noises are noticed; one of them is low amplitude muscle tremor that mimics the baseline seen in atrial fibrillation and another one is power line interference (PLI) which distorts the normal segments of ECG. The goal of noise removal in ECG is to facilitate easy and accurate interpretations. This paper aims at de-noising the simulated muscle tremors and power line interference while preserving the amplitude and frequency component present in ECG. The proposed method performs the de-noising of ECG in a better manner as compared to the existing methods. The performance of various wavelets for de-noising has been checked by calcul...

An Improved Method for ECG Denoising Using Wavelet Transform

ABSTRACT The Electrocardiogram (ECG) is a recording of heart’s contractile activity in electrical... more ABSTRACT The Electrocardiogram (ECG) is a recording of heart’s contractile activity in electrical potentials which is consist of P, QRS and T waves. The ECG is recorded by placing the electrodes at specific positions on patient’s skin. The artifacts are generated either by patient&#39;s motion or by other electrical devices attached during the recording. Two important noises are noticed; one of them is low amplitude muscle tremor that mimics the baseline seen in atrial fibrillation and another one is power line interference (PLI) which distorts the normal segments of ECG. The goal of noise removal in ECG is to facilitate easy and accurate interpretations. This paper aims at de-noising the simulated muscle tremors and power line interference while preserving the amplitude and frequency component present in ECG. The proposed method performs the de-noising of ECG in a better manner as compared to the existing methods. The performance of various wavelets for de-noising has been checked by calculating the percentage root mean square difference (PRD) for European ST-T Database.

Compensation scheme for power quality improvement in present power system

2014 Recent Advances in Engineering and Computational Sciences (RAECS), 2014

The power quality (PQ) management is the key issue in electrical power system and industries are ... more The power quality (PQ) management is the key issue in electrical power system and industries are facing this issues around the world. The hybrid filter configuration with PI Controller is more efficient scheme for the improvement of power quality in power system. The main purpose of this work is to reduce the effects of Harmonics in a cost effective by mitigating both voltage and current harmonics generated in an electrical power system owing to the presence of non linear loads. This paper shows comparative study of a simple filter circuit, circuit with hybrid filter and a circuit with hybrid filter using P-I controller. The systems are modeled by using SIMULINK in MATLAB and performance is observed. The simulation results reveal that the proposed method of hybrid filter with PI controller is the better solution for improving power quality.

Optimal Selection of Wavelet Function and Decomposition Level for Removal of ECG Signal Artifacts

Electrocardiogram (ECG) signals are used for prognosis of anatomic heart functions in clinical ro... more Electrocardiogram (ECG) signals are used for prognosis of anatomic heart functions in clinical routine. During recording, ECG is contaminated with artifacts owing to specific reasons, which makes accurate delineation and interpretation of ECG more difficult. The commonly noticed artifacts include; baseline wanders, power line interference and muscle tremors. This paper aims at elucidation for the algorithms for optimal selection of wavelet function and decomposition level for removal of these artifacts in ECG, while preserving the diagnostic information. The features of wavelet transforms viz. multi-resolution, information in time and frequency, and thresholding have been employed for the implementation of algorithms in MATLAB. The performance of wavelet functions at various decomposition levels has been evaluated using percentage root mean square difference (PRD) criterion. Simulated results indicate that optimal value of wavelet function is db7 at 8th decomposition level for removal of artificially added baseline wander with PRD of 0.1636%, coif2 at 5th decomposition level for removal of artificially added power line interference with PRD of 0.3980% and db7 at 8th decomposition level for removal of artificially added muscle tremor with PRD of 0.8959% in selected records of European ST-T database (EDB). The proposed method shows better performance than existing methods in terms of lower PRD. Moreover it also addresses to the issues of conventional methods.

Robust Multi-resolution Wavelet Analysis & Window Search Based Approach for Electrocardiogram Features Delineation

Statistical Analysis of ST Segments for Ischemia Detection in ECG Signals

A novel method has been proposed for the detection of ischemia using statistical features resulti... more A novel method has been proposed for the detection of ischemia using statistical features resulting from ST segment deviations in Electrocardiogram (ECG) signals. The method consists of five stages: pre-processing, region of interest (ROI), measurement of ST segment deviation, thresholding and statistical analysis. The mean threshold of ST segment deviation is used to classify the ischemic beats from normal beats and then ischemic episode recognition is made through enduring beats. The statistical analysis has been performed, which involves coefficient of variation (COV), kurtosis and form factor. A bell shaped normal distribution is generated for stable and reliable measured ST segments for normal, depressed and elevated records. The preprocessing and delineation algorithms have been implemented in MATLAB 2012a and IBM SPSS 22 has been used for statistical analysis. The results show 97.83% average sensitivity (S E ) and 97.56% average specificity (S P ) for 86,384 segments of annotated European ST-T database (EDB) after validation. These results are significantly better than the available methods in the literature. The proposed algorithm covers the advantages of automatic discarding of irrelevant data, noisy beats.

Ischemia Detection using Isoelectric Energy Function

A novel method has been proposed for the detection of ischemia using an isoelectric energy functi... more A novel method has been proposed for the detection of ischemia using an isoelectric energy function (IEEF) resulting from ST segment deviations in ECG signals. The method consists of five stages: pre-processing, delineation, measurement of isoelectric energy, a beat characterization algorithm and detection of ischemia. The isoelectric energy threshold is used to differentiate ischemic beats from normal beats for ischemic episode detection. Then, ischemic episodes are classified as transmural or subendocardial. The method is validated for recordings of the annotated European ST-T database (EDB). The results show 98.12% average sensitivity (SE) and 98.16% average specificity (SP). These results are significantly better than those of existing methods cited in the literature. The advantage of the proposed method includes simplicity, ruggedness and automatic discarding of noisy beats.

Comparative Analysis Of Image Segmentation Using Hough Transform

Abstract: Image segmentation, a way of extracting and representing information from an image is t... more Abstract: Image segmentation, a way of extracting and representing information from an image is to group pixels together into regions of similarity. We would group pixels together according to the rate of change of their intensity over a region or the rate of change of depth in the image, corresponding to pixels lying on the same surface such as a plane, cylinder, sphere etc.

Real Time Monitoring System for ECG Signal Using Virtual Instrumentation

by Amit manocha and Lillie Dewan

ABSTRACT: The paper introduces the designed aspects of the real time monitoring of the ECG signal... more ABSTRACT: The paper introduces the designed aspects of the real time monitoring of the ECG signal on virtual cardiograph. The designed system is consisting of four parts as below. ✓ Data acquisition of ECG signal ✓ Filtering of data logger ✓ Representations of Acquired ECG signal on virtual graphs. ✓ Making the data logger. The 6013 E Analog card is used for the acquisition of ECG signal from ECG simulator and LabVIEW 7.0 professional development tool is used to designed the system.

Smart Grid–Internet of Future Technology for Electrical Energy

Abstract: Power Grid systems are essential for the economical growth of India. The Grid System is... more Abstract: Power Grid systems are essential for the economical growth of India. The Grid System is continuously evolving. It is keeping pace with the available technologies. Smart Grid is based on the technology of Internet. It aims at,“SAVE ENERGY→ SAVE MONEY”. It increases reliability. It provides choices to the consumers. It protects them from possible outages. It makes power system to protect itself from cyber attacks and natural disasters.

PERFORMANCE CALCULATION OF WAVELET TRANSFORMS FOR REMOVAL OF BASELINE WANDER FROM ECG

by Amit manocha and Geeta Kaushik

International Journal of …, Jan 1, 2012

As change in ST segment is an indication of ischemia in ECG and usually baseline wanders which ar... more As change in ST segment is an indication of ischemia in ECG and usually baseline wanders which are low frequency component of 0.5 to 1 Hz signal overlaps the ST segment in ECG, when the ECG is recorded by the electrodes from the chest of the patient. So Baseline wanders may makes wrong interpretation for the detection of ischemia and removal of baseline wander may cause another loss of important clinical information. This paper is to present the wavelet transform for estimation of baseline wanders in ECG and to find the effectiveness of this method by the Percent Root Mean Square Difference (PRD). Obtained results show that the wavelet transform approach performs successfully removal of baseline wanders. To test the proposed method, ECG signals obtained from European ST-T database have been used.

An Overview of Ischemia Detection Techniques

ijser.org

In recent years several researchers have put great efforts in biomedical engineering for improvin... more In recent years several researchers have put great efforts in biomedical engineering for improving the diagnostic techniques used by the physiologists. A lot of research has been done in biomedical signal processing which includes the signal enhancement, signal compression, artifacts and noise removal like power line interference removal, base line drift removal. For detection of cardiac arrhythmia and ischemia using ECG signal, many emerging techniques and algorithms have been proposed. Ischemia is one of the cardiovascular diseases which are responsible for almost 20% of the deaths around the world. Some of the recently developed algorithms by these researchers have given remarkable results for ischemia. In this paper we review these existing algorithms for detection of ischemia in terms of their performance and capabilities with respect to standard databases available worldwide.

Three Axis Aircraft Autopilot Control Using Genetic Algorithms: An Experimental Study

Advance Computing Conference, …, Jan 1, 2009

The behavior of an aircraft can be described with a set Pfth

accurate delineation of ECG characteristics points using window search and wavelet transform

Automatic and accurate delineation of ECG characteristic's points play a pivotal role in computer... more Automatic and accurate delineation of ECG characteristic's points play a pivotal role in computerized electrocardiography for prognosis of heart diseases. The paper presents an algorithm research for removal of artifacts& noises and delineation of ECG characteristics points based on wavelet transform. The multi-resolution, thresholding, minima/maxima pairs with window searching feature of wavelet transform has been used for the implementation of algorithm. The measured values of characteristics waves of ECG are validated for European ST-T database records. The result shows over 100% accurate detection rate in terms of amplitude and occurrence with respect to time for P wave, QRS complex & T wave and also can be easily distinguished even contaminated with baseline drift and artifacts.

Application of Digital Signal Processing to ECG Signal

Improved Method for ECG Denoising Using Wavelet Transform

The Electrocardiogram (ECG) is a recording of heart’s contractile activity in electrical potentia... more The Electrocardiogram (ECG) is a recording of heart’s contractile activity in electrical potentials which is consist of P, QRS and T waves. The ECG is recorded by placing the electrodes at specific positions on patient’s skin. The artifacts are generated either by patient's motion or by other electrical devices attached during the recording. Two important noises are noticed; one of them is low amplitude muscle tremor that mimics the baseline seen in atrial fibrillation and another one is power line interference (PLI) which distorts the normal segments of ECG. The goal of noise removal in ECG is to facilitate easy and accurate interpretations. This paper aims at de-noising the simulated muscle tremors and power line interference while preserving the amplitude and frequency component present in ECG. The proposed method performs the de-noising of ECG in a better manner as compared to the existing methods. The performance of various wavelets for de-noising has been checked by calcul...

An Improved Method for ECG Denoising Using Wavelet Transform

ABSTRACT The Electrocardiogram (ECG) is a recording of heart’s contractile activity in electrical... more ABSTRACT The Electrocardiogram (ECG) is a recording of heart’s contractile activity in electrical potentials which is consist of P, QRS and T waves. The ECG is recorded by placing the electrodes at specific positions on patient’s skin. The artifacts are generated either by patient&#39;s motion or by other electrical devices attached during the recording. Two important noises are noticed; one of them is low amplitude muscle tremor that mimics the baseline seen in atrial fibrillation and another one is power line interference (PLI) which distorts the normal segments of ECG. The goal of noise removal in ECG is to facilitate easy and accurate interpretations. This paper aims at de-noising the simulated muscle tremors and power line interference while preserving the amplitude and frequency component present in ECG. The proposed method performs the de-noising of ECG in a better manner as compared to the existing methods. The performance of various wavelets for de-noising has been checked by calculating the percentage root mean square difference (PRD) for European ST-T Database.

Compensation scheme for power quality improvement in present power system

2014 Recent Advances in Engineering and Computational Sciences (RAECS), 2014

The power quality (PQ) management is the key issue in electrical power system and industries are ... more The power quality (PQ) management is the key issue in electrical power system and industries are facing this issues around the world. The hybrid filter configuration with PI Controller is more efficient scheme for the improvement of power quality in power system. The main purpose of this work is to reduce the effects of Harmonics in a cost effective by mitigating both voltage and current harmonics generated in an electrical power system owing to the presence of non linear loads. This paper shows comparative study of a simple filter circuit, circuit with hybrid filter and a circuit with hybrid filter using P-I controller. The systems are modeled by using SIMULINK in MATLAB and performance is observed. The simulation results reveal that the proposed method of hybrid filter with PI controller is the better solution for improving power quality.

Optimal Selection of Wavelet Function and Decomposition Level for Removal of ECG Signal Artifacts

Electrocardiogram (ECG) signals are used for prognosis of anatomic heart functions in clinical ro... more Electrocardiogram (ECG) signals are used for prognosis of anatomic heart functions in clinical routine. During recording, ECG is contaminated with artifacts owing to specific reasons, which makes accurate delineation and interpretation of ECG more difficult. The commonly noticed artifacts include; baseline wanders, power line interference and muscle tremors. This paper aims at elucidation for the algorithms for optimal selection of wavelet function and decomposition level for removal of these artifacts in ECG, while preserving the diagnostic information. The features of wavelet transforms viz. multi-resolution, information in time and frequency, and thresholding have been employed for the implementation of algorithms in MATLAB. The performance of wavelet functions at various decomposition levels has been evaluated using percentage root mean square difference (PRD) criterion. Simulated results indicate that optimal value of wavelet function is db7 at 8th decomposition level for removal of artificially added baseline wander with PRD of 0.1636%, coif2 at 5th decomposition level for removal of artificially added power line interference with PRD of 0.3980% and db7 at 8th decomposition level for removal of artificially added muscle tremor with PRD of 0.8959% in selected records of European ST-T database (EDB). The proposed method shows better performance than existing methods in terms of lower PRD. Moreover it also addresses to the issues of conventional methods.

Robust Multi-resolution Wavelet Analysis & Window Search Based Approach for Electrocardiogram Features Delineation

Statistical Analysis of ST Segments for Ischemia Detection in ECG Signals

A novel method has been proposed for the detection of ischemia using statistical features resulti... more A novel method has been proposed for the detection of ischemia using statistical features resulting from ST segment deviations in Electrocardiogram (ECG) signals. The method consists of five stages: pre-processing, region of interest (ROI), measurement of ST segment deviation, thresholding and statistical analysis. The mean threshold of ST segment deviation is used to classify the ischemic beats from normal beats and then ischemic episode recognition is made through enduring beats. The statistical analysis has been performed, which involves coefficient of variation (COV), kurtosis and form factor. A bell shaped normal distribution is generated for stable and reliable measured ST segments for normal, depressed and elevated records. The preprocessing and delineation algorithms have been implemented in MATLAB 2012a and IBM SPSS 22 has been used for statistical analysis. The results show 97.83% average sensitivity (S E ) and 97.56% average specificity (S P ) for 86,384 segments of annotated European ST-T database (EDB) after validation. These results are significantly better than the available methods in the literature. The proposed algorithm covers the advantages of automatic discarding of irrelevant data, noisy beats.

Ischemia Detection using Isoelectric Energy Function

A novel method has been proposed for the detection of ischemia using an isoelectric energy functi... more A novel method has been proposed for the detection of ischemia using an isoelectric energy function (IEEF) resulting from ST segment deviations in ECG signals. The method consists of five stages: pre-processing, delineation, measurement of isoelectric energy, a beat characterization algorithm and detection of ischemia. The isoelectric energy threshold is used to differentiate ischemic beats from normal beats for ischemic episode detection. Then, ischemic episodes are classified as transmural or subendocardial. The method is validated for recordings of the annotated European ST-T database (EDB). The results show 98.12% average sensitivity (SE) and 98.16% average specificity (SP). These results are significantly better than those of existing methods cited in the literature. The advantage of the proposed method includes simplicity, ruggedness and automatic discarding of noisy beats.

Comparative Analysis Of Image Segmentation Using Hough Transform

Abstract: Image segmentation, a way of extracting and representing information from an image is t... more Abstract: Image segmentation, a way of extracting and representing information from an image is to group pixels together into regions of similarity. We would group pixels together according to the rate of change of their intensity over a region or the rate of change of depth in the image, corresponding to pixels lying on the same surface such as a plane, cylinder, sphere etc.

Real Time Monitoring System for ECG Signal Using Virtual Instrumentation

by Amit manocha and Lillie Dewan

ABSTRACT: The paper introduces the designed aspects of the real time monitoring of the ECG signal... more ABSTRACT: The paper introduces the designed aspects of the real time monitoring of the ECG signal on virtual cardiograph. The designed system is consisting of four parts as below. ✓ Data acquisition of ECG signal ✓ Filtering of data logger ✓ Representations of Acquired ECG signal on virtual graphs. ✓ Making the data logger. The 6013 E Analog card is used for the acquisition of ECG signal from ECG simulator and LabVIEW 7.0 professional development tool is used to designed the system.

Smart Grid–Internet of Future Technology for Electrical Energy

Abstract: Power Grid systems are essential for the economical growth of India. The Grid System is... more Abstract: Power Grid systems are essential for the economical growth of India. The Grid System is continuously evolving. It is keeping pace with the available technologies. Smart Grid is based on the technology of Internet. It aims at,“SAVE ENERGY→ SAVE MONEY”. It increases reliability. It provides choices to the consumers. It protects them from possible outages. It makes power system to protect itself from cyber attacks and natural disasters.

PERFORMANCE CALCULATION OF WAVELET TRANSFORMS FOR REMOVAL OF BASELINE WANDER FROM ECG

by Amit manocha and Geeta Kaushik

International Journal of …, Jan 1, 2012

As change in ST segment is an indication of ischemia in ECG and usually baseline wanders which ar... more As change in ST segment is an indication of ischemia in ECG and usually baseline wanders which are low frequency component of 0.5 to 1 Hz signal overlaps the ST segment in ECG, when the ECG is recorded by the electrodes from the chest of the patient. So Baseline wanders may makes wrong interpretation for the detection of ischemia and removal of baseline wander may cause another loss of important clinical information. This paper is to present the wavelet transform for estimation of baseline wanders in ECG and to find the effectiveness of this method by the Percent Root Mean Square Difference (PRD). Obtained results show that the wavelet transform approach performs successfully removal of baseline wanders. To test the proposed method, ECG signals obtained from European ST-T database have been used.

An Overview of Ischemia Detection Techniques

ijser.org

In recent years several researchers have put great efforts in biomedical engineering for improvin... more In recent years several researchers have put great efforts in biomedical engineering for improving the diagnostic techniques used by the physiologists. A lot of research has been done in biomedical signal processing which includes the signal enhancement, signal compression, artifacts and noise removal like power line interference removal, base line drift removal. For detection of cardiac arrhythmia and ischemia using ECG signal, many emerging techniques and algorithms have been proposed. Ischemia is one of the cardiovascular diseases which are responsible for almost 20% of the deaths around the world. Some of the recently developed algorithms by these researchers have given remarkable results for ischemia. In this paper we review these existing algorithms for detection of ischemia in terms of their performance and capabilities with respect to standard databases available worldwide.

Three Axis Aircraft Autopilot Control Using Genetic Algorithms: An Experimental Study

Advance Computing Conference, …, Jan 1, 2009

The behavior of an aircraft can be described with a set Pfth