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Author

Rajarshi Gupta

Bio: Rajarshi Gupta is an academic researcher from University of Calcutta. The author has contributed to research in topic(s): Discrete wavelet transform & Wavelet. The author has an hindex of 14, co-authored 62 publication(s) receiving 712 citation(s).
Papers
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Journal ArticleDOI
01 Apr 2012-Measurement
TL;DR: A multiresolution approach along with an adaptive thresholding is used for the detection of R-peaks and the T wave is detected in the QT segment of digitized electrocardiograph recordings.
Abstract: A discrete wavelet transform (DWT) based feature extraction technique in the QT segment of digitized electrocardiograph recordings is proposed. At first, the signal is denoised by decomposing it using DWT technique and discarding the coefficients corresponding to the noise components. A multiresolution approach along with an adaptive thresholding is used for the detection of R-peaks. Then Q, S peak, QRS onset and offset points are identified. Finally, the T wave is detected. By detecting the baseline of the ECG data, height of R, Q, S and T wave are calculated. For R-peak detection, proposed algorithm yields sensitivity and positive predictivity of 99.8% and 99.6% respectively with MIT BIH Arrhythmia database, 99.84% and 99.98% respectively with PTB diagnostic ECG database. For time plane features, an average coefficient of variation of 3.21 is obtained over 150 leads tested from PTB data, each with 10,000 samples.

126 citations


Journal ArticleDOI
01 Nov 2010-Measurement
TL;DR: A low-cost method for online acquisition of ECG signal for storage and processing using a MATLAB-based Graphical User Interface (GUI) to perform online analysis on the ECG data to compute the different time-plane features and display the same on the GUI along with theECG signal plot.
Abstract: This paper illustrates a low-cost method for online acquisition of ECG signal for storage and processing using a MATLAB-based Graphical User Interface (GUI). The single lead ECG is sampled at a rate of 1 kHz and after digitization, fed to a microcontroller-based embedded system to convert the ECG data to a RS232 formatted serial bit-stream. This serial data stream is then transmitted to a desktop Personal Computer at a rate of 19.2 kbps and a state-of-the art developed software stores it automatically in a temporary data file. The original ECG data is reconstructed from the digital data set by a conversion formula. The MATLAB-based GUI is designed to perform online analysis on the ECG data to compute the different time-plane features and display the same on the GUI along with the ECG signal plot.

70 citations


Proceedings ArticleDOI
Rajarshi Gupta1, Madhuchhanda Mitra1Institutions (1)
01 Dec 2011-
TL;DR: An offline ECG compression technique, based on encoding of successive sample differences is proposed, which is presently being implemented in a wireless telecardiology system using a standalone embedded system.
Abstract: An offline ECG compression technique, based on encoding of successive sample differences is proposed. The encoded elements are generated through four stages, viz., down sampling of raw samples, normalization of successive sample differences; data grouping; magnitude and sign encoding; and finally zero element compression. Initially, the compression algorithm is validated with short duration raw ECG samples from PTB database under Physionet. MATLAB simulation results using ptb-db data with 8-bit quantization results a compression ratio (CR) of 9.02 and percentage root mean square difference (PRD) of 2.51. With mit-db these figures are 4.68 and 0.739 respectively. The algorithm is presently being implemented in a wireless telecardiology system using a standalone embedded system.

67 citations


Book
11 Sep 2013-
TL;DR: ECG Acquisition and Automated Remote Processing - Libros de Medicina - Electrocardiografia - 99,99
Abstract: ECG Acquisition and Automated Remote Processing - Libros de Medicina - Electrocardiografia - 99,99

50 citations


Journal ArticleDOI
TL;DR: A method for time-plane feature extraction from digitized ECG sample using statistical approach, broadly based on relative comparison of magnitude and slopes of ECG samples is illustrated.
Abstract: This paper illustrates a method for time-plane feature extraction from digitized ECG sample using statistical approach. The algorithm detects the position and magnitude of the QRS complex, P and T wave for a single lead ECG dataset. The processing is broadly based on relative comparison of magnitude and slopes of ECG samples. Then the baseline modulation in the dataset is removed. The R-peak detection and baseline modulation is tested MIT-BIH arrhythmia database as well as 12-lead datasets in MIT-PTB database (PTBDB) and available under Physionet. The overall accuracy obtained is more than 99%.

37 citations


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01 Jan 2016-
TL;DR: This bioelectrical signal processing in cardiac and neurological applications helps people to face with some infectious bugs inside their computer, instead of enjoying a good book with a cup of tea in the afternoon.
Abstract: Thank you for downloading bioelectrical signal processing in cardiac and neurological applications. Maybe you have knowledge that, people have search hundreds times for their chosen books like this bioelectrical signal processing in cardiac and neurological applications, but end up in malicious downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they are facing with some infectious bugs inside their computer.

225 citations


Journal ArticleDOI
Swati Banerjee1, Madhuchhanda Mitra1Institutions (1)
TL;DR: The proposed algorithm analyzes ECG data utilizing XWT and explores the resulting spectral differences and heuristically determined mathematical formula extracts the parameter(s) from the WCS and WCOH that are relevant for classification of normal and abnormal cardiac patterns.
Abstract: In this paper, we use cross wavelet transform (XWT) for the analysis and classification of electrocardiogram (ECG) signals. The cross-correlation between two time-domain signals gives a measure of similarity between two waveforms. The application of the continuous wavelet transform to two time series and the cross examination of the two decompositions reveal localized similarities in time and frequency. Application of the XWT to a pair of data yields wavelet cross spectrum (WCS) and wavelet coherence (WCOH). The proposed algorithm analyzes ECG data utilizing XWT and explores the resulting spectral differences. A pathologically varying pattern from the normal pattern in the QT zone of the inferior leads shows the presence of inferior myocardial infarction. A normal beat ensemble is selected as the absolute normal ECG pattern template, and the coherence between various other normal and abnormal subjects is computed. The WCS and WCOH of various ECG patterns show distinguishing characteristics over two specific regions R1 and R2, where R1 is the QRS complex area and R2 is the T-wave region. The Physikalisch-Technische Bundesanstalt diagnostic ECG database is used for evaluation of the methods. A heuristically determined mathematical formula extracts the parameter(s) from the WCS and WCOH. Empirical tests establish that the parameter(s) are relevant for classification of normal and abnormal cardiac patterns. The overall accuracy, sensitivity, and specificity after combining the three leads are obtained as 97.6%, 97.3%, and 98.8%, respectively.

222 citations


Journal ArticleDOI
TL;DR: A study of the existing laws regulating these aspects in the European Union and the United States, a review of the academic literature related to this topic, and a proposal of some recommendations for designers in order to create mobile health applications that satisfy the current security and privacy legislation are presented.
Abstract: In a world where the industry of mobile applications is continuously expanding and new health care apps and devices are created every day, it is important to take special care of the collection and treatment of users' personal health information. However, the appropriate methods to do this are not usually taken into account by apps designers and insecure applications are released. This paper presents a study of security and privacy in mHealth, focusing on three parts: a study of the existing laws regulating these aspects in the European Union and the United States, a review of the academic literature related to this topic, and a proposal of some recommendations for designers in order to create mobile health applications that satisfy the current security and privacy legislation. This paper will complement other standards and certifications about security and privacy and will suppose a quick guide for apps designers, developers and researchers.

212 citations


Journal ArticleDOI
TL;DR: The results of the review suggest that most research in wearable ECG monitoring systems focus on the older adults and this technology has been adopted in aged care facilitates and it is shown that how mobile telemedicine systems have evolved and how advances in wearable wireless textile-based systems could ensure better quality of healthcare delivery.
Abstract: Wearable health monitoring is an emerging technology for continuous monitoring of vital signs including the electrocardiogram (ECG). This signal is widely adopted to diagnose and assess major health risks and chronic cardiac diseases. This paper focuses on reviewing wearable ECG monitoring systems in the form of wireless, mobile and remote technologies related to older adults. Furthermore, the efficiency, user acceptability, strategies and recommendations on improving current ECG monitoring systems with an overview of the design and modelling are presented. In this paper, over 120 ECG monitoring systems were reviewed and classified into smart wearable, wireless, mobile ECG monitoring systems with related signal processing algorithms. The results of the review suggest that most research in wearable ECG monitoring systems focus on the older adults and this technology has been adopted in aged care facilitates. Moreover, it is shown that how mobile telemedicine systems have evolved and how advances in wearable wireless textile-based systems could ensure better quality of healthcare delivery. The main drawbacks of deployed ECG monitoring systems including imposed limitations on patients, short battery life, lack of user acceptability and medical professional's feedback, and lack of security and privacy of essential data have been also discussed.

202 citations


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Performance
Metrics

Author's H-index: 14

No. of papers from the Author in previous years
YearPapers
20213
20208
20197
20185
20174
20166