Papers by Sucharita Mitra
A comparative study of vein pattern recognition for biometrie authentication
In informational age there are many information crucial to a individual. To protect the data from... more In informational age there are many information crucial to a individual. To protect the data from the unwanted use we proposed the biometric system of vein recognition as today's world demand for a easy and accurate biometric system to protect our data. The biometric system is accurate and easy to use as every individual has a unique vein pattern. In this paper we have studied various method used by different people to achieve the goal to secure world and give the reader a brief prospective of this technology.
Automatic feature extraction of ECG signal based on adaptive window dependent differential histogram approach and validation with CSE database
International Journal of Computational Systems Engineering
A very simple and novel idea based on adaptive window dependent differential histogram approach h... more A very simple and novel idea based on adaptive window dependent differential histogram approach has been proposed for automatic detection and identification of ECG waves with its characteristic features. To facilitate the estimation of the waves, the normalised signal has been divided into a few small windows by an adaptive window selection technique. By counting the number of changes between successive samples as frequency, the differential histogram has been plotted. Some of the zones having an area more than a pre-defined threshold are depicted as QRS zones. The local maxima of these zones are referred as the R-peaks. T and P peaks are also detected. Baseline point and clinically significant time plane features have been computed and validated with reference values of the CSE database. The proposed technique achieved better performance in comparison with CSE groups. Its accuracy is achieved in sensitivity (99.86%), positive productivity (99.76%) and detection accuracy (99.8%).
International Journal of Web-Based Learning and Teaching Technologies
This paper illustrates the cloud-based telemonitoring framework that implements healthcare automa... more This paper illustrates the cloud-based telemonitoring framework that implements healthcare automation system for myocardial infarction (MI) disease classification. For this purpose, the pathological feature of ECG signal such as elevated ST segment, inverted T wave, and pathological Q wave are extracted, and MI disease is detected by the rule-based rough set classifier. The information system involves pathological feature as an attribute and decision class. The degree of attributes dependency finds a smaller set of attributes and predicted the comprehensive decision rules. For MI decision, the ECG signal is shared with the respective cardiologist who analyses and prescribes the required medication to the first-aid professional through the cloud. The first-aid professional is notified accordingly to attend the patient immediately. To avoid the identity crisis, ECG signal is being watermarked and uploaded to the cloud in a compressed form. The proposed system reduces both data storage...
International Journal on Smart Sensing and Intelligent Systems
Software based efficient lossless Electrocardiogram compression and transmission scheme is propos... more Software based efficient lossless Electrocardiogram compression and transmission scheme is proposed here. The algorithm has been tested to various ECG data taken from PTB Diagnostic ECG Database. The compression scheme is such that it outputs only ASCII characters. These characters are transmitted using Global System for Mobile Communication based Short Message Service system and at the receiving end original ECG signal is brought back using the reverse logic of compression. It is observed that the proposed algorithm offers a
An automated data extraction system from 12 lead ECG images
Computer Methods and Programs in Biomedicine, Jan 5, 2003
A software based normalized ECG data acquisition system is developed for both normal and abnormal... more A software based normalized ECG data acquisition system is developed for both normal and abnormal ECG records. This system can transfer wave data recorded on paper to the digital time database. A flatbed scanner is used to form an image database of each 12 lead ECG signal. These TIF formatted gray tone images are then converted into two tone binary images with the help of histogram analysis. Smearing runlength technique is used to remove the vertical and horizontal line segments of graphical papers. Thinning algorithm is applied to each image to obtain the skeleton (1 pixel representation) of each image, which is essential to avoid excess data points in the database. After extracting pixel to pixel co-ordinate information of images of each of the signal of 12 lead ECG records, the data are sorted to regenerate the signal. From standard deviation of the database a graphical analysis is performed to examine the consistency of our database.
Ieee Transactions on Instrumentation and Measurement, Dec 1, 2006
In this paper, a rule-based rough-set decision system for the development of a disease inference ... more In this paper, a rule-based rough-set decision system for the development of a disease inference engine is described. For this purpose, an offline-data-acquisition system of paper electrocardiogram (ECG) records is developed using image-processing techniques. The ECG signals may be corrupted with six types of noise. Therefore, at first, the extracted signals are fed for noise removal. A QRS detector is also developed for the detection of R-R interval of ECG waves. After the detection of this R-R interval, the P and T waves are detected based on a syntactic approach. The isoelectric-level detection and base-line correction are also implemented for accurate computation of different attributes of P, QRS, and T waves. A knowledge base is developed from different medical books and feedbacks of reputed cardiologists regarding ECG interpretation and essential time-domain features of the ECG signal. Finally, a rule-based rough-set decision system is generated for the development of an inference engine for disease identification from these time-domain features.
ECG Data Compression via ASCII Character Encoding and Feature Extraction Using Hilbert Transform based Approach
Preliminary Level Cardiac Abnormality Detection Using Wireless Telecardiology System
First International Conference on the Digital Society (ICDS'07), 2007
This paper describes a portable diagnostic telecardiology system, aimed to benefit the rural peop... more 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
ASCII Conversion of ECG data- A Simplified Compression Technique
ECG Feature Extraction: Lagrange Five Point Interpolation and Hilbert Transform Based Approach
2011 International Conference on Computer, Communication and Electrical Technology (ICCCET), 2011
Efficient and reliable electrocardiogram (ECG) compression system can increase the processing spe... more Efficient and reliable electrocardiogram (ECG) compression system can increase the processing speed of realtime ECG transmission as well as reduce the amount of data storage in long-term ECG recording. In the present paper, a software based effective ECG data compression algorithm is proposed. The whole algorithm is written in C-platform. The algorithm is tested on various ECG data of all the 12 leads taken from PTB Diagnostic ECG Database (PTB-DB). In this compression methodology, all the R-Peaks are detected at first by differentiation technique and QRS regions are located. To achieve a strict lossless compression in QRS regions and a tolerable lossy compression in rest of the signal, two different compression algorithms have developed. In lossless compression method a difference array has been generated from the corresponding input ECG "Voltage" values and then those are multiplied by a considerably large integer number to convert them into integer. In the next step, theses integer numbers are grouped in both forward and reverse direction maintaining some logical criteria. Then all the grouped numbers along with sign bit and other necessary information (position of critical numbers, forward/reverse grouping etc.) are converted into their corresponding ASCII characters. Whereas in lossy area, first of all, the sampling frequency of the original ECG signal is reduced to one half and then, only the "Voltage" values are gathered from the corresponding input ECG data and those are amplified and grouped only in forward direction. Then all the grouped numbers along with sign bit and other necessary information are converted into their corresponding ASCII characters. It is observed that this proposed algorithm can reduce the file size significantly. The data reconstruction algorithm has also been developed using the reversed logic and it is seen that data is reconstructed preserving the significant ECG signal morphology.
Lecture Notes in Computer Science, 2007
An automated approach for computation of the frontal plane QRS vector and an important observatio... more An automated approach for computation of the frontal plane QRS vector and an important observation of its clinical significance is described in this paper. Frontal plane QRS vector is computed from the six frontal plane leads (Standard leads I, II, III , AVR, AVL and AVF). The R-R interval of each ECG wave is detected by square derivative technique. The baseline or isoelectric level of every ECG wave is determined. After that the net positive or net negative deflection (NQD) of QRS complex is detected. Net positive or net negative deflection in any lead is obtained by subtracting the smaller deflection (+ve or-ve) from the larger deflection (-ve or +ve). An algorithm is developed for computation of the exact angle,amplitude and direction of the frontal plane QRS vector from maximum and minimum NQD. In the present work, the PTB diagnostic ECG database of normal and Myocardial Infarction (MI) subjects is used for computation of the QRS vector. An interesting clinical observation that, the rotation of QRS axis for MI data may significantly detect the region of the infarcted cardiac wall, is reported in this paper.
An Approach to a Rough Set Based Disease Inference Engine for ECG Classification
Lecture Notes in Computer Science, 2006
An inference engine for classification of ECG signals is developed with the help of a rule based ... more An inference engine for classification of ECG signals is developed with the help of a rule based rough set decision system. For this purpose an automated ECG data extraction system from ECG strips is being developed by using few image processing techniques. Filtering techniques are used for removal of noises from recorded ECG. A knowledge base is developed after consultation of different medical books and feedback of reputed cardiologists regarding ECG interpretation and selection of essential time-plane features of ECG signal. An algorithm for extraction of different time domain features is also developed with the help of differentiation techniques and syntactic approaches. Finally, a rule-based roughest decision system is generated from these time-plane features for the development of an inference engine for disease classification.
A Simple Histogram Based Approach for Detection of Baseline and QRS of ECG
IFMBE Proceedings, 2007
ABSTRACT
A Software Based Approach for Detection of QRS Vector of ECG Signal
IFMBE Proceedings, 2007
... In another scheme a QRS complex detector based on the dyadic wavelet transform (Dy WT), which... more ... In another scheme a QRS complex detector based on the dyadic wavelet transform (Dy WT), which is robust to time varying QRS complex morphology and to noise, has also ... Another approach for QRS detection is an adaptive matched filtering algorithm based upon an ...
A Simple Online Histogram and Pattern Recognition Based ECG Analyzer
IETE Journal of Research, 2008
... performance of the developed QRS and baseline detector is satisfactory in noisy environment a... more ... performance of the developed QRS and baseline detector is satisfactory in noisy environment and we ... F Jager, RG Mark, G В Moody & S Divjak, Analysis of transient ST ... the first Indian language Bharati Braille system for the blind, a successful Bangla speech synthesis system as ...
Pattern classification of time plane features of ECG wave from cell-phone photography for machine aided cardiac disease diagnosis
2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014
This article reports a robust technique for extracting time plane features of Electrocardiogram (... more This article reports a robust technique for extracting time plane features of Electrocardiogram (ECG) from digital images of ECG paper strips. We concluded this article reporting performance evaluation of the system developed for machine aided cardiac disease detection. Mostly paper based ECG recordings are used in developing countries and digital photographs of different leads could easily be taken and sent with a mediocre cellular phone set. Apart from extracting the features, the proposed system detects cardiac axis deviation and diagnose if Left or Right Bundle Branch Blockage (LBBB or RBBB) is present while fed with the digital photographs of different leads of ECG strips. Preprocessing of the low-resolution images involves background grid line noise removal, adaptive image binarization by Sauvola's method and Bresenham's line joining algorithm to link the ECG signature, if broken. Pattern extraction mainly delineate the time plane features like P wave, QRS complex and T wave using water reservoir based pattern recognition techniques and Discrete Wavelet Transform (DWT). Cardiac axis deviation detection is done by checking the overall voltage levels of QRS complexes of lead I, II and III. Having the knowledge of cardiac axis completes the requirements to comment on the cardiac blockage like Left or Right Bundle Branch Blockage (LBBB or RBBB). Thus, the proposed algorithm is primarily developed for machine aided diagnosis of LBBB or RBBB from the digital photographs of ECG paper strips.
ECG Data Compression via ASCII Character Encoding and Feature Extraction Using Hilbert Transform Based Approach
ECG Compression Technique Using ASCII Character Encoding and Transmission Using GSM Transmitter
ECG signal processing: Lossless compression, transmission via GSM network and feature extraction using Hilbert transform
ABSTRACT Software based new, efficient and reliable lossless ECG data compression, transmission a... more ABSTRACT Software based new, efficient and reliable lossless ECG data compression, transmission and feature extraction scheme is proposed here. The compression and reconstruction algorithm is implemented on C-platform. The compression scheme is such that the compressed file contains only ASCII characters. These characters are transmitted using internet based Short Message Service (SMS) system and at the receiving end, original ECG signal is brought back using just the reverse logic of compression. Reconstructed ECG signal is de-noised and R peaks are detected using Lagrange Five Point Interpolation formula and Hilbert transform. ECG baseline modulation correction is done and Q, S, QRS onset-offset points are identified. The whole module has been applied to various ECG data of all the 12 leads taken from PTB diagnostic ECG database (PTB-DB). It is observed that the compression module gives a moderate to high compression ratio (CR=7.18), an excellent Quality Score (QS=312.17) and the difference between original and reconstructed ECG signal is negligible (PRD=0.023%). Also the feature extraction module offers a good level of Sensitivity and Positive Predictivity (99.91%) of R peak detection. Measurement errors in extracted ECG features are also calculated.
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Papers by Sucharita Mitra