University of Calcutta (informally known as Calcutta University or CU) is a collegiate public state university located in Kolkata, West Bengal, India.&nbsp;Within India it is recognized as a &quot;Five-Star University&quot; and accredited &quot;A&quot; Grade by National Assessment and Accreditation Council.

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The University of Calcutta has secured the Fifth position among the Universities of India in the prestigious &quot;Indian University Ranking 2019&quot; list, released by the NIRF of the Ministry of Human Resource Development, Government of India.

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It was established on 24 January 1857, and was one of the first institutions in Asia to be established as a multidisciplinary and Western-style university. Its alumni and faculty include several heads of state, heads of government, social reformers, prominent artists, only academy award winner and Dirac medal winner in India, many Fellows of the Royal Society and five Nobel laureates as of 2019 which is highest in South Asia.

University Of Calcutta

Automatic electrocardiogram analysis using different signal processing technique is one of the prominent areas of research in biomedical engineering. This paper illustrates a simple approach for time plane feature extraction in the QT segment. At first, the R peaks are accurately determined using a simple derivative-based approach and hence heart rate is calculated. Next, the baseline points of all cardiac cycles in the dataset are determined in the TP segment and the baseline modulation in the signal is eliminated by an empirical formula. Finally, the characteristic points Q, Qoffset, S, S-offset, T-onset, T and T-offset are calculated for all cycles using a magnitude and slope threshold based method. Hence, QRS width, ST segment, QT segment and (QT)c are determined. ECG data for 30 second interval from MIT-PTB diagnostic database is used for testing the algorithm. © 2011 IEEE.

Applied Physics

World University root node

Proceedings - 2nd International Conference on Emerging Applications of Information Technology, EAIT 2011

A derivative-based approach for QT-segment feature extraction in digitized ECG record

This paper illustrates a simple algorithm for real time QRS detection from ECG data. The algorithm is implemented on Xilinx field programmable gate array using very small number of memory cells. Single lead Synthetic ECG using ptb-db database (from Physionet) is generated from a personal computer using the parallel port (LPT1) at 1 ms sampling interval and delivered to the FPGA (Field Programmable Gate Array) board. At first, from the first 1500 samples, the QRS detection algorithm calculates some characteristic amplitude and slope based signatures which are used to form a rule base. These rules are used for detecting the next incoming QRS regions accurately. The index points of R-peaks are determined and shown in the LEDs using switch-based commands. © 2011 IEEE.

2011 2nd International Conference on Computer and Communication Technology, ICCCT-2011

An FPGA implementation of real-time QRS detection

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%. © 2011 Elsevier Ltd.

Computers in Biology and Medicine

A statistical approach for determination of time plane features from digitized ECG

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. © 2011 IEEE.

Proceedings - 2011 Annual IEEE India Conference: Engineering Sustainable Solutions, INDICON-2011

An ECG compression technique for telecardiology application

International conference on Biomedical Engineering and Assistive {\ldots}

Time Plane feature extraction from digitized ECG using D-ECG approach

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. © 2010 Elsevier Ltd. All rights reserved.

Measurement: Journal of the International Measurement Confederation

Development of an embedded system and MATLAB-based GUI for online acquisition and analysis of ECG signal

This paper illustrates a low cost novel method for ECG signal acquisition, display and storage using a Graphical User Interface (GUI), which provides a userfriendly front end by using MATLAB-based toolsets. At first, analog ECG has been converted to its digital equivalent with the help of an ADC. Microcontrollers converted this data to a serial (RS232) format and transmit to the PC for serial acquisition. The developed GUI performs the acquisition for its future processing. © 2009 IEEE.

ACT 2009 - International Conference on Advances in Computing, Control and Telecommunication Technologies

Development of a state-of-the art ECG DAS for storing, processing and analysis using MATLAB-based GUI and microcontroller

This paper describes a portable diagnostic telecardiology system, aimed to benefit the rural people of a third world country like India. The designed system consists of two major blocks; the first one is required to be carried to the patient home, named ¿Portable Telecardiology Kit¿. The second one, named ¿Automated Cardiac Signal Processor¿, a PC based system, to be permanently placed at the nearest rural health care center. The ¿Portable Telecardiology Kit¿ contains a portable ECG machine, a dedicated microcontroller-based full duplex communication system, both interfaced, in a single enclosure. This kit will convert the ECG signal along with a tag page (containing different information regarding patient¿s health and history of illness) to a digitized serial electromagnetic wave. The signal may be transmitted over a distance of about 7-10 km through a cordless phone under full duplex mode. The PC-based system, after receiving the transmitted signal from patient site, extract the ECG signal after proper filtering, and then pass the signal through an in-built knowledge-base. Finally, a rule-based rough set decision system is generated for the development of an inference engine for disease identification from these time-plane features. The system will generate a report indicating the preliminary level abnormalities, and the precautions that can be adopted at an early stage. The entire report is then sent to the Portable kit at the patient bed-site. © 2007 IEEE.