Faculty Publications
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Publications by NITK Faculty
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Item Reliable transmission of retinal fundus images with patient information using encryption, watermarking, and error control codes(World Scientific Publishing Co., 2011) Nergui, M.; Sripati, A.U.; Acharya, A.U.; Yu, W.; Dua, S.[No abstract available]Item AR modeling of heart rate signals(Institute of Electrical and Electronics Engineers Inc., 2004) Nayak, J.; Subbanna Bhat, P.; Acharya, A.U.; Niranjan, U.C.; Sing, O.W.The electrocardiogram (ECG) is a representative signal containing information about the condition of the heart. The shape and size of the P-QRS-T wave, the time intervals between its various peaks etc may contain useful information about the nature of disease afflicting the heart. However, the human observer can not directly monitor these subtle details. Besides, since bio-signals are highly subjective, the symptoms may appear at random in the time scale. Therefore, the heart rate variability signal is used as the base signal for the highly useful in diagnostics. This paper deals with the analysis of eight cardiac abnormalities using Auto Regressive (AR), modeling technique. The results are tabulated below for specific example. © 2004 IEEE.Item Reliable and robust transmission and storage of medical images with patient information(2004) Nayak, J.; Subbanna Bhat, P.; Kumar, M.S.; Acharya, A.U.A new method for compact storage and transmission of medical images with concealed patient information in noisy environment is evinced. Digital Watermarking is the technique adapted here for interleaving patient information with medical images. The patient information, which comprises of text data and signal graph, is encrypted to prevent unauthorized access of data. The latest encryption algorithm (Rijndael) is used for encrypting the text information. Signal graphs (ECG, EEG EMG etc.) are compressed using DPCM technique. To enhance the robustness of the embedded information, the patient information is coded by Error Correcting Codes (ECC) such as (7,4) Hamming, Bose-Chaudhuri-Hocquenghem (BCH) and Reed Solomon (RS) codes. The noisy scenario is simulated by adding salt and pepper (S&P) noise to the embedded image. For different Signal to Noise Ratio (SNR) of the image, Bit Error Rate (BER) and Number of Character Altered (NOCA) for text data and percentage distortion (PDIST) for the signal graph are evaluated. The performance comparison based on the above parameters is conducted for three types of ECC. It is elicited that coded systems can perform better than the uncoded systems. © 2004 IEEE.Item Reliable transmission and storage of medical images with patient information using error control codes(2004) Nayak, J.; Subbanna Bhat, P.; Kumar, M.S.; Acharya, A.U.A new method for compact storage and transmission of medical Images with concealed patient Information in noisy environment if evinced. Digital Watermarking is the technique adapted here for interleaving patient Information with medical images. The patient information, which comprises of text data and signal graph, is encrypted to prevent unauthorized access of data. The latest encryption algorithm (Rijndael) is used for encrypting the text information. Signal graphs (ECG, EEG EMG etc.) are compressed using DPCM technique. To enhance the robustness of the embedded information, the patient Information Is coded by Error Correcting Codes (ECC) Reed Solomon (RS) codes. The noisy scenario Is simulated by adding salt and pepper (S&P) noise to the embedded Image. For different Signal to Noise Ratio (SNR) of the image, Bit Error Rate (BER) and Number of Character Altered (NOCA) for text data and percentage distortion (PDIST) for the signal graph is evaluated. It Is elicited that coded systems can perform better than the uncoded systems. © 2004 IEEE.Item Cardiac health diagnosis using wavelet transformation and phase space plots(2005) Acharya, A.U.; Subbanna Bhat, P.; Kannathal, N.; Lim, C.M.; Laxminarayan, S.Analysis of heart rate variation (HRV) has become a popular noninvasive tool for assessing the activities of the autonomic nervous system (ANS). HRV analysis is based on the concept that fast fluctuations may specifically reflect changes of sympathetic and vagal activity. It shows that the structure generating the signal is not simply linear, but also involves nonlinear contributions. These signals are essentially nonstationary; may contain indicators of current disease, or even warnings about impending diseases. The indicators may be present at all times or may occur at random in the time scale. However, to study and pinpoint abnormalities in voluminous data collected over several hours is strenuous and time consuming. This paper presents the continuous time wavelet analysis of heart rate variability signal for disease identification. Phase space plots of heart rate signal for a chosen embedding dimension are compared with the wavelet analysis patterns. © 2005 IEEE.Item Transmission and storage of medical images with patient information(Elsevier Ltd, 2003) Acharya, A.U.; Subbanna Bhat, S.; Kumar, M.S.; Min, L.C.Digital watermarking is a technique of hiding specific identification data for copyright authentication. This technique is adapted here for interleaving patient information with medical images, to reduce storage and transmission overheads. The text data is encrypted before interleaving with images to ensure greater security. The graphical signals are interleaved with the image. Two types of error control-coding techniques are proposed to enhance reliability of transmission and storage of medical images interleaved with patient information. Transmission and storage scenarios are simulated with and without error control coding and a qualitative as well as quantitative interpretation of the reliability enhancement resulting from the use of various commonly used error control codes such as repetitive, and (7,4) Hamming code is provided. © 2003 Elsevier Science Ltd. All rights reserved.Item Digital watermarking is a technique of hiding specific identification data for copyright authentication. This technique is adapted here for interleaving patient information with medical images to reduce storage and transmission overheads. The text data are encrypted before interleaving with images to ensure greater security. The graphical signals are compressed and subsequently interleaved with the image. Differential pulse-code-modulation and adaptive-delta-modulation techniques are employed for data compression, and encryption and results are tabulated for a specific example.(Compact storage of medical images with patient information) Acharya, A.U.; Anand, D.; P, S.B.; C, N.U.2001Item A novel visualization technique for voluminous ECG data acquired over several hours is presented. The classified data is displayed in a sector graph, with a menu driven hierarchical display strategy, which progressively unfolds greater details for chosen intervals. A color code is employed to identify different types of abnormalities. Provision is made for fine tuning the classification. © 2002 Elsevier Science Ltd. All rights reserved.(Comprehensive visualization of cardiac health using electrocardiograms) Acharya, A.U.; Subbanna Bhat, P.; Niranjan, U.C.2002Item The electrocardiogram is a representative signal containing information about the condition of the heart. The shape and size of the P-QRS-T wave, the time intervals between its various peaks, etc. may contain useful information about the nature of disease afflicting the heart. However, these subtle details cannot be directly monitored by the human observer. Besides, since bio-signals are highly subjective, the symptoms may appear at random in the time scale. Therefore, the signal parameters, extracted and analysed using computers, are highly useful in diagnostics. This paper deals with the classification of certain diseases using artificial neural network (ANN) and fuzzy equivalence relations. The heart rate variability is used as the base signal from which certain parameters are extracted and presented to the ANN for classification. The same data is also used for fuzzy equivalence classifier. The feedforward architecture ANN classifier is seen to be correct in about 85% of the test cases, and the fuzzy classifier yields correct classification in over 90% of the cases. © 2002 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.(Classification of heart rate data using artificial neural network and fuzzy equivalence relation) Acharya, A.U.; Subbanna Bhat, P.; Iyengar, S.S.; Rao, A.; Dua, S.2003Item The heart rate is a non-stationary signal, and its variation can contain indicators of current disease or warnings about impending cardiac diseases. The indicators can be present at all times or can occur at random, during certain intervals of the day. However, to study and pinpoint abnormalities in large quantities of data collected over several hours is strenuous and time consuming. Hence, heart rate variation measurement (instantaneous heart rate against time) has become a popular, non-invasive tool for assessing the autonomic nervous system. Computer-based analytical tools for the in-depth study and classification of data over day-long intervals can be very useful in diagnostics. The paper deals with the classification of cardiac rhythms using an artificial neural network and fuzzy relationships. The results indicate a high level of efficacy of the tools used, with an accuracy level of 80-85%. © IFMBE: 2004.(Classification of cardiac abnormalities using heart rate signals) Acharya, A.U.; Kumar, A.; Subbanna Bhat, P.; Lim, C.M.; Iyengar, S.S.; Kannathal, N.; Krishnan, S.M.2004