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Publications (79)
Objectives: In this paper, the features of physiological signals of healthy dataset are extracted using the linear and non-linear techniques, and a comparison has been made on healthy young and old subjects to study the aging and gender-related changes in the contribution of Heart Rate (HR), Blood Pressure (BP), and Respiration (RESP).
Methods: To...
In the proposed work, the redundancy reduction-based two-dimensional (2D) electrocardiogram (ECG) data compression technique is performed wherein the inter-beat and intra-beat ECG samples were exploited to reduce their amplitudes. The resultant samples showed significant reduction in amplitudes out of which few variations with relatively high magni...
Many physiological signals such as heart rate (HR), blood pressure (BP), and respiration (RESP) affect each other, and the inter-relation within and between these signals can be linear or nonlinear. Therefore, this paper’s main aim is to extract the relevant features using the information domain coupling technique based on conditional transfer entr...
The process of uncontrolled fatal growth of tissue that invades its surrounding parts is called cancer. The cancer in breast is the most commonly encountered cancer among women. It accounts for millions of deaths around the globe. Early detection of breast cancer by ultrasound (US)-based diagnosis can have major positive influence on life expectanc...
Electrical activity in plants undergoes potential changes in interpreting the plant's physiological state. These electrical signals show arbitrary and probabilistic dynamics in which stress can be detected and analysed in the early stages of symptom appearance in plants. Evaluation of uncertainty in plant signals by signal strength enhancement is s...
Plants leave testimonies of undergoing physical state by depicting distinct variations in their electrophysiological data. Adequate nutrition of plants signifies their role in the growth and a plentiful harvest. Plant signal data carries enough information to detect and analyse nutrient deficiency. Classification of nutrient deficiencies through si...
The low quality of diagnostic Ultrasound (US) images makes structural identification challenging. It is crucial to enhance these images before application in Computer-Aided Detection (CAD). This study aims to ease breast lesion identification in US images by introducing a novel echo-texture-based technique. We used the basic notion that the unique...
Deep Learning (DL) algorithms, especially Convolutional Neural Network (CNN) have outperformed in medical image classification tasks and have achieved human-competitive performance. This has become possible because CNN learns image features through backpropagation. However, the strategy for designing a CNN model with the highest accuracy for a spec...
Ultrasound in diagnostic imaging is well known for its safety and accessibility. But its efficiency for diagnosis is always limited by the presence of noise. So, in this study, a Log-Exponential shrinkage technique is presented for denoising of ultrasound images. A Combinational filter was designed for the removal of additive noise without losing a...
Due to COVID-19, demand for Chest Radiographs (CXRs) have increased exponentially. Therefore, we present a novel fully automatic modified Attention U-Net (CXAU-Net) multi-class segmentation deep model that can detect common findings of COVID-19 in CXR images. The architectural design of this model includes three novelties: first, an Attention U-net...
Abstract The proliferation of tele‐healthcare services at an accelerated rate raises concerns over the management,security and privacy of the patient's confidential data (an individual's personal details and medical biography) during its transmission and storage. To resolve these issues, amalgamation of three fundamental techniques of remote health...
A novel idea of exploiting the chaotic sequences for substitution in the DCT coefficients of ECG signal according to the secret data is proposed in this work. The chaotic values are selected as per the decimal number generated from a bundle of secret bits. The selected chaotic values sensibly manipulates only the low- energy DCT coefficients, thus...
Electrocardiogram (ECG) is essentially a significant physiological signal required in the diagnosis of cardiac disorders. For remote healthcare assistance, ECG signal along with patient’s meta-data is communicated over the public network. During communication, security and privacy of patient’s sensitive information is a major issue. Presently, a co...
In modern time, emotions affect people in many aspects of life. Long-term emotional problems lead to mental and physical problems such as depression. Wrist pulse contains the information regarding the physiological and pathological state of an individual. Overall mental and physical status of human can be checked with the wrist pulse through pulse...
Ultrasound imaging technique finds crucial application in clinical diagnosis of breast cancer. Presence of noise in ultrasound image due to different factor degrades the image quality and so the accuracy of diagnosis. Wavelet thresholding have been used from very beginning for de-noising of ultrasound image. Here in this paper we propose an interve...
In recent decades, the concept of complex physiological systems has become more and more popular. The evaluation of the biological time series' dynamic complexity is an essential subject with possible applications such as the characterization of physiological states i.e. HRV, BP, and RESP signals and pathological disorders to the measurement of dia...
The bioelectrical activity like ECG, EMG and EEG provides the health condition of heart, muscles, and brain in human beings. In plants, the sensible measurements of physical activity are in their infant phase. Substitution of technology used in biomedical field (human medicine) might consequently provide an understanding about electrophysiological...
In this paper, a novel feature selection method is proposed for the categorization of electrocardiogram (ECG) heartbeats. The proposed technique uses the Fisher ratio and BAT optimization algorithm to obtain the best feature set for ECG classification. The MIT-BIH arrhythmia database contains sixteen classes of the ECG heartbeats. The MIT-BIH ECG a...
The most important factor involved in heart rate variability (HRV) analysis is cardiac input signal, which is achieved in the form of electrocardiogram (ECG). The ECG signal is used for identifying many electrical defects associated with the heart. In this chapter, many issues involved while ECG recording such as type of the recording instrument, v...
In e-healthcare paradigm, the physiological signals along with patient’s personal information need to be transmitted to remote healthcare centres. Before sharing this sensitive information over the unsecured channel, it is prerequisite to protect it from unauthorised access. The proposed method explores ECG signal as the cover signal to hide patien...
Plants have an electrical signal, which is a weak signal. These signals vary during the growth of plants, the stress of plant. Environment changes are observed by their electrophysiological signals. Four plants of different species have been connected to channel of BIOPAC MP36 set-up individually at different instant of time, then the signal variat...
In the chapter, dynamic time domain features are extracted in the proposed approach for the accurate classification of electrocardiogram (ECG) heartbeats. The dynamic time-domain information such as RR, pre-RR, post-RR, ratio of pre-post RR, and ratio of post-pre RR intervals to be extracted from the ECG beats in proposed approach for heartbeat cla...
In this chapter, the BAT-optimized fuzzy k-nearest neighbor (FKNN-BAT) algorithm is proposed for discrimination of the electrocardiogram (ECG) beats. The five types of beats (i.e., normal [N], right bundle block branch [RBBB], left bundle block branch [LBBB], atrial premature contraction [APC], and premature ventricular contraction [PVC]) are taken...
The upsurge in the communication infrastructure and development in internet of things (IoT) has promoted e-healthcare services to provide remote assistance to homebound patients. It, however, increases the demand to protect the confidential information from intentional and unintentional access by unauthorized persons. This chapter is focused on ste...
In this chapter, different approaches are presented for removal of fog from video footage taken in moving cars. The methodology uses different approaches, namely dark channel prior, contrast limited adaptive histogram equalization (CLAHE), the combination of two approaches (dark channel prior and CLAHE), and RETINEX algorithm combined with DWT. The...
The electrocardiogram (ECG) non-invasively monitors the electrical activities of the heart to diagnose the heart-related diseases. The baseline wandering noise affects the diagnosis of the heart diseases. In this paper, the baseline wandering noise removal is done using forward–backward Riemann Liouville (RL) fractional integral-based empirical wav...
The electrocardiogram (ECG) non-invasively monitors the electrical activities of the heart. During the process of recording and transmission, ECG signals are often corrupted by various types of noises. Minimizations of these noises facilitate accurate detection of various anomalies. In the present paper, Alexander fractional differential window (AF...
Since the QRS complex varies with different cardiac health conditions, therefore efficient and automatic detection of QRS complex and is essential for reliable health condition monitoring. In this work an empirical wavelet transform (EWT)-based algorithm has been used for accurate detection of QRS complex. EWT is one of the adaptive time-frequency...
Plant responses to changes in environment are allied with electrical excitability, signaling and are observed by their electrophysiological signals. Similarly communication in between various plants is noticed by continuous monitoring of their electrophysiological signals at same instant comparatively. Signal acquisition is done with help of BIOPAC...
Every woman experiences an extensive fluctuation in HRV during her menstrual cycle and even after menopause. A woman who lives long enough will experience menopause as a normal physiologic event. The study of the influence of premenopausal and postmenopausal symptoms on HRV has not been adequate. During this period, health management is an importan...
Heart rate variability (HRV) plays an important role in regulation of cardiac functioning during the menstrual and menopausal stages of women life. There are limited studies which considered the combined effect of ageing and postural changes on HRV of women. The objective of this study is: 1) to analyse and reveal the cardiac autonomic status of pr...
The study was intended to analyze the effect of three types of music, namely Indian classical music, Bhajan (spiritual anthem) music and rock music, on the electroencephalogram (EEG) activity for two different age groups, viz. young subjects (23–27 years) and elder subjects (40–55 years). We recorded EEG in 10 healthy elder subjects and 10 healthy...
An algorithm is presented for designing a new class of wavelets matched to the Heart Rate Variability (HRV) signals of the menstrual cycle. The proposed wavelets are used to find HRV variations between phases of menstrual cycle. The method finds the signal matching characteristics by minimising the shape feature error using Least Mean Square method...
Postmenopause is the naturally occurring stage in woman’s life after the permanent cessation of the menstruation longer than 12 months. The transition from the young to the postmenopausal stage impacts the variation in the heart rate. It is important to analyze and detect the variation in Heart Rate Variability (HRV) between young and postmenopausa...
Telecardiology includes variety of applications and is one of the fastest-growing fields in telemedicine. In telecardiology the amount of recorded ECG data is very much high, hence the necessity of efficient data compression methods for biomedical signals is currently widely recognized. In this paper improved version of existing ASCII character enc...
Electrocardiogram (ECG) compression can significantly reduce the storage and transmission burden in telemedicine applications. In this paper, an improved ECG data compression method using ASCII character encoding is proposed. A QRS detection algorithm firstly applied to separate QRS and non-QRS region. Then, the QRS regions of ECG signal are compre...
Correlation dimension (CD) is used for analysing the chaotic behaviour of the nonlinear heart rate variability (HRV) time series. In CD, the autocorrelation function is used to calculate the time delay. However, it does not provide optimum values of time delays, which leads to an inaccurate estimation of the HRV between phases of the menstrual cycl...
Transmission of biomedical signals over telephone lines or other communication channels is currently an important issue for the telemedicine applications. An efficient compression algorithm is needed to achieve a reduced information rate, for the storage and transmission purposes. In this paper, empirical wavelet transform (EWT) along with discrete...
Abstract The aim of an automated Electrocardiogram (ECG) delineation system is the reliable detection of the characteristic waveforms and determination of peaks and limits of individual QRS-complex, P- and T-waves. In this paper, a classical statistical pattern recognition algorithm characterized with high accuracy and stability, i.e., K-Nearest Ne...
This paper, presents a competent feature extraction technique, i.e., Bidimensional Empirical Mode Decomposition (BEMD) for mammogram images. The EMD is fully adaptive and data driven technique. BEMD is used to extract features at numerous scales or spatial frequencies in form of Intrinsic Mode Functions (IMFs). By using these IMFs five statistical...
Detection and delineation of QRS-complexes, P and T-waves, are important issues in the analysis and interpretation of Electrocardiogram (ECG) signals. In t his paper, a classifier motivated from statistical learning theory, i.e., Support Vector Machine (SVM), has been explored for detection and delineation of these wave components. Digital filterin...
The performance of computer aided ECG analysis depends on the precise and accurate delineation of QRS-complexes. This paper presents an application of K-Nearest Neighbor (KNN) algorithm as a classifier for detection of QRS-complex in ECG. The proposed algorithm is evaluated on two manually annotated standard databases such as CSE and MIT-BIH Arrhyt...
Detection of the boundaries of electrocardiogram (ECG) characteristic waves with a reasonable accuracy has been a difficult task. As a classical statistical pattern recognition algorithm characterized with high accuracy and stability, KNN has been proposed for locating the waveform boundaries (the onsets and offsets of P, QRS, and T waves) in ECG s...
The automatic detection of ECG wave is important for cardiac disease diagnosis. A good performance of an automatic ECG analysing system depends upon the accurate and reliable detection of the QRS complex. This paper presents an application of K-nearest neighbour (KNN) algorithm for detection of QRS-complex in ECG. Here, the ECG signal was filtered...
Detection of QRS-complex is an important issue in the analysis and interpretation of electrocardiogram (ECG) signals. In this work, a classifier motivated from statistical learning theory, i.e., support vector machine (SVM), has been explored for detection of QRS-complex. Here, a raw ECG signal is band-pass filtered to remove base line wander and p...
In this paper, the classification of RR-interval and blood pressure series for two different physical activities postures has been performed using support vector machine (SVM). Without understanding the changes in these features from lying to standing posture in the same subject it is not possible to decipher the hidden dynamics of cardiovascular c...
Code division multiple access (CDMA) is a rapidly expanding data transmission technique in the emerging universal mobile telecommunication system. Digital matched filter (DMF) in a CDMA system is used for correlating the received data with the transmitted data. The key issues in the design of a DMF are speed and power. This paper presents the desig...
