Ramakrishnan Swaminathan

• PhD
• Indian Institute of Technology Madras

Muscle fiber type proportion is a key determinant of fatigue, force generation, and functions of different skeletal muscles. Analysis of muscle fiber type composition aids in the assessment of athletic abilities and individualization of training methods. This study attempts to non-invasively analyze the muscle fiber type composition in the soleus (...

Electroencephalography (EEG) based emotional state assessment is widely preferred due to its noninvasiveness and non-radiation approach. However, these signals are highly non-stationary and multi-component, demonstrating large intra-subject variability. Extracting time and frequency information simultaneously from EEG addresses these challenges to...

Detection of early mild cognitive impairment (EMCI) is clinically challenging as it involves subtle alterations in multiple brain sub-anatomic regions. Among different brain regions, the corpus callosum and lateral ventricles are primarily affected due to EMCI. In this study, an improved deep canonical correlation analysis (CCA) based framework is...

Alzheimer’s disease (AD) is a progressive outcome resulting from two pathological alterations, specifically the formation of neurofibrillary tangles and the presence of extracellular amyloid plaques. It leads to the degeneration of neural structures, including the fornix. In this study, a systematic literature review is conducted to examine the cha...

Alzheimer’s disease (AD) is a progressive neurodegenerative brain disorder that primarily affects elderly individuals. Mild cognitive impairment (MCI) represents an intermediate stage between normal cognitive functioning and the onset of AD. During this transition state, various subanatomic structures of the brain, including fornix, undergo patholo...

Emotion influences the daily activity of human life. The complex interaction between the central nervous system (CNS) and peripheral nervous system (PNS) contributes to emotional experiences. Various studies have investigated this interaction during sleep, meditation, deception, and cognition. However, research focusing exclusively on emotion-relat...

Neuromuscular fatigue can be monitored using complexity domain analysis of surface electromyography (sEMG) signals. This study provides a technique to detect fatigue induced change in signal complexity using the entropic measurements of its recurrence pattern. For this purpose, fifteen participants have been recruited to perform isometric fatiguing...

Alzheimer's disease (AD) is a prevalent neurodegenerative form of dementia that progressively affects individuals. Alterations in the fornix region are significant biomarkers of AD. In this letter, an approach is proposed to distinguish mild cognitive impairment (MCI) from normal cognition (NC) and AD subjects using structural magnetic resonance (s...

Given impulsivity's multidimensional nature and its implications across various aspects of human behavior, a comprehensive understanding of functional brain circuits associated with this trait is warranted. In the current study, we utilized whole‐brain resting‐state functional connectivity data of healthy males (n = 156) to identify a network of co...

Alzheimer's disease (AD) is a progressive brain disorder that affects elderly individuals. Globally, around 50 million patients are affected by AD, and the prevalence is expected to reach 152 million by 2050. AD is characterized by the presence of amyloid plaques and neurofibrillary tangles, which affects sub-anatomical brain structures and leads t...

The T1-weighted brain sMR images of normal cognitive (NC), MCI and AD subjects are obtained from public database. Preprocessing steps including skull stripping, removal of non-brain tissues, intensity normalization, and image registration are performed using the FreeSurfer pipeline. The Fornix structure is delineated using level set evolution witho...

Successful identification of estrum or other stages in a cycling bitch often requires a combination of methods, including assessment of its behavior, exfoliative vaginal cytology, vaginoscopy, and hormonal assays. Vaginoscopy is a handy and inexpensive tool for the assessment of the breeding period. The present study introduces an innovative method...

Emotion influences human life and impacts daily life activities. During emotional processes, physiological signals interact with each other instead of functioning separately. Although unimodal and multimodal approaches have been explored for emotion classification, there is a lack of inclusion of central and peripheral nervous system signal interac...

Emotion influences human life and impacts daily life activities. The central nervous system (CNS) and peripheral nervous system (PNS) interact intricately to produce emotional experiences. There are various studies related to the interaction of the CNS-PNS during psychophysiological states. However, emotion-oriented, CNS-PNS phase synchronisation s...

Mild cognitive impairment (MCI) and Alzheimer’s disease (AD) are known to cause geometrical changes in the integrity of the fornix, which plays a crucial role in memory formation and retrieval. The objective of this study is to analyse structural variations in the fornix region using structural magnetic resonance (sMR) images and geometrical featur...

In this research work, free volume theory (FVT) is employed to analyze the diffusion of synthetic antimicrobial agents that are utilized for wound healing applications. For this purpose, polyvinyl alcohol (PVA) hydrogel is considered as a matrix for the diffusion of the therapeutic compounds. The diffusion characteristics are studied using a comput...

Segmentation of nuclei and cytoplasm in cellular images is essential for estimating the prognosis of lung cancer disease. The detection of these organelles in the unstained brightfield microscopic images is challenging due to poor contrast and lack of separation of structures with irregular morphology. This work aims to carry out semantic segmentat...

The interaction between the central nervous system (CNS) and peripheral nervous system (PNS) governs various physiological functions, influences cognitive processes and emotional states. It is necessary to unravel the mechanisms governing the interaction between the brain and the body, enhancing our understanding of physical and mental well-being....

Automated emotion recognition is crucial in identifying and monitoring psychological disorders. Although several electroencephalography (EEG)-based methods have been explored for emotion recognition, capturing the subtle oscillations within EEG signals associated with distinct emotional states remains a persistent challenge. Non-linear phase-based...

Investigating the fluctuations of uterine contractions is an indispensable diagnostic practice to evaluate the onset of labor. This work aims to differentiate the fluctuations associated with Term (gestation ≥ 37 weeks) pregnancies during varied gestational ages using electrohysterography (EHG) signals. The signals in the second and third trimester...

Surface electromyography (sEMG) is a non-invasive technique to characterize muscle electrical activity. The analysis of sEMG signals under muscle fatigue play a crucial part in the branch of neurorehabilitation, sports medicine, biomechanics, and monitoring neuromuscular pathologies. In this work, a method to transform sEMG signals to complex netwo...

Preterm birth (gestational age < 37 weeks) is a public health concern that causes fetal and maternal mortality and morbidity. When this condition is detected early, suitable treatment can be prescribed to delay labour. Uterine electromyography (uEMG) has gained a lot of attention for detecting preterm births in advance. However, analyzing uEMG is c...

Detection of emotional states plays a prominent role in affective computing, decision-making, and healthcare. Physiological signals are an ideal target for continuous and objective assessment of emotional states. Electrodermal activity (EDA) is considered one of the most effective and widely used markers of sympathetic activation. However, emotiona...

Mild Cognitive Impairment (MCI) is a transitional phase between Normal Cognitive (NC) aging and several neurodegenerative diseases. The pathological manifestations due to MCI occur in different brain sub-anatomic structures, including fornix. Studies suggest that atrophy in fornix analysed using Magnetic Resonance (MR) images is a reliable indicato...

Emotions play an essential role in human life as they are linked to well-being and markers of various diseases. Physiological signals can be used to assess emotions objectively and continuously. Electrodermal activity (EDA) is particularly interesting to assess emotions due to its relationship with the sympathetic nervous system. EDA signals are co...

The selection of proper measurement systems and signal processing methods is crucial while analyzing complex physiological signals like surface electromyography (sEMG). Reassignment technique is a powerful signal analysis method that enables efficient cross-term suppression in time-frequency distributions and provides excellent time-frequency resol...

This study attempts to detect and differentiate Multi Drug Resistant (MDR) - Tuberculosis (TB) and Drug Sensitive (DS)-TB Chest Radiographs (CXR) using local texture descriptors and Ensemble Learning method. Studies report that CXR images contain likelihood information of the drug resistance which can be utilized computationally. Initially, CXR ima...

Fluorescence microscopy based cell painting technique profiles the morphological characteristics of specific cell organelles with high resolution. However, photo toxicity, photo bleaching and advanced instrumentation limits its utility for comprehensively annotating the cell structure. Generating cell painted organelles from simple and least invasi...

The present research work aims to comprehensively analyze the effect of swelling of polyethylene glycol (PEG) hydrogel on its diffusion properties for wound healing applications. For this study, a computational model based on three fundamental theories namely, equilibrium swelling theory, rubber elasticity theory and free volume theory has been imp...

The co-occurrence of diabetes, hypertension, and cardiovascular diseases together can make clinical management and treatment more complex. Early detection of comorbid conditions can help in creating personalized treatment plans. Multiple fluid biomarkers can be used to enhance the diagnostic accuracy of identifying comorbidity. This study aims to d...

In this study, irregularity measures in MR images of corpus callosal brain structures in healthy and Mild Cognitive Impairment (MCI) conditions are extracted and their association with Cerebrospinal Fluid (CSF) biomarkers are analyzed. For this, MR images of healthy controls, Early MCI (EMCI) and Late MCI (LMCI) subjects are considered from a publi...

Fluid biomarkers extracted from many types of body fluids provide significant information that serve as indicators of the underlying physiological and pathological conditions of the human body. Analysis of multiple fluid biomarkers could help improve the early identification and progression of comorbid conditions to enhance the diagnostic accuracy,...

Cell painting technique provides large amount of potential information for applications such as drug discovery, bioactivity prediction and cytotoxicity assessment. However, its utility is restricted due to the requirement of advanced, costly and specific instrumentation protocols. Therefore, creating cell painted images using simple microscopic dat...

This work aims to analyze the complexity of surface electromyography (sEMG) signals under muscle fatigue conditions using Hjorth parameters and bubble entropy (BE). Signals are recorded from the biceps brachii muscle of 25 healthy males during dynamic and isometric contraction exercises. These signals are filtered and segmented into 10 equal parts....

Uterine electromyography (uEMG) measures the electrical activity of the uterus noninvasively and is a promising technique for detecting preterm birth. Nevertheless, uterine contractions are irregular during pregnancy and may not present during standard 30-min recording. Hence, this study analyzes the noncontraction of uEMG signals for predicting pr...

Investigation of drug-induced structural changes in cell lines at different concentrations using microscopic images is essential to understand their cytotoxic effects. In this study, geometric shape descriptors to evaluate the toxicity effects of a particular drug in cell images are formulated. For this, fluorescence microscopic images of drug-untr...

The analysis of surface electromyography (sEMG) signals is significant in the detection of muscle fatigue. These signals exhibit a great degree of complexity, nonlinearity, and chaos. Also, presence of high degree of fluctuations in the signal makes its analysis a difficult task. This study aims to analyze the nonlinear dynamics of muscle fatigue c...

In this work, an attempt is made to investigate the association of geometric changes in mediastinum and lungs with Coronavirus Disease-2019 (COVID-19) using chest radiographic images. For this, the normal and COVID-19 images are considered from a public database. Reaction-diffusion level set is employed to segment the lung fields. Further, Chan Ves...

The present work aims to comprehensively analyze the diffusion of plant metabolites from the polyethylene glycol (PEG) hydrogels for controlled release applications. For this study, a mathematical model based on free volume theory has been utilized to simulate the diffusion of low molecular weight plant metabolites. The results demonstrate that the...

Monitoring of the physiological function during exercise can provide insights on the quality of the training and prevent injury. Specifically, the signals from the muscle sensors (Surface Electromyography) are difficult to interpret and limited attempts have been made to develop effective algorithms for the real-time monitoring of muscle fatigue. I...

Impulsivity is a multidimensional construct often associated with unfavorable outcomes. Previous studies have implicated several electroencephalography (EEG) indices to impulsiveness, but results are heterogeneous and inconsistent. Using a data-driven approach, we identified EEG power features for the prediction of self-reported impulsiveness. To t...

Artificial Intelligence is a tool poised to transform healthcare, with use in diagnostics and therapeutics. The widespread use of digital pathology has been due to the advent of whole slide imaging. Cheaper storage for digital images, along with unprecedented progress in artificial intelligence, have paved the synergy of these two fields. This has...

Emotion is a psycho-physiological phenomenon that influence cognitive and affective processes. Emotional state analysis can provide relevant information to diagnose various mental health disorders. Electrodermal activity (EDA) is a widely used physiological signal to assess emotional states due to its non-invasiveness. In this study, differentiatio...

In this work, an attempt has been made to analyze the shape variations in mediastinum for differentiation of Coronavirus Disease-2019 (COVID-19) and normal conditions in chest X-ray images. For this, the images are obtained from a publicly available dataset. Segmentation of mediastinum from the raw images is performed using Reaction Diffusion Level...

In this work, an attempt has been made to analyze the influence of pathological changes in eye globe dimensions towards the mechanical responses of optic nerve head tissues during eye adductions. For this study, a 3D baseline model geometry of posterior ocular tissues has been constructed. The eye globe diameters of the model are modified to mimic...

Alzheimer’s Disease (AD) is a progressive fatal neurodegenerative disorder that causes cognitive decline in affected people. Image processing of brain MR images can aid in identifying significant imaging biomarkers for detection of AD and its prodromal stage Mild Cognitive Impairment (MCI). Bidimensional multiscale entropy-based texture analysis is...

Breast cancer causes more deaths among all types of cancers. Efforts have been put to study the change in temperature distribution profile of the breast in presence of an abnormality. By applying Pennes's bio-heat equation, a 2D finite element model is developed for the heat transfer mechanism. Surface temperature gradients due to the presence of a...

The umbilical cord is the link between fetus and the placenta. It consists of one vein and two arteries, encased inside Wharton's jelly. In this study, the influence of morphological parameters of umbilical arteries, namely the wall-lumen ratio and lumen diameter, on the stress distribution in Wharton's jelly is analyzed using a 3D finite element m...

In-vehicle health monitoring allows for continuous vital sign measurement in everyday life. Eventually, this could lead to early detection of cardiovascular diseases. In this work, we propose non-contact heart rate (HR) monitoring utilizing near-infrared (NIR) camera technology. Ten healthy volunteers are monitored in a realistic driving simulator...

Muscle fatigue analysis is important in the diagnosis of neuromuscular diseases. Analysis of surface electromyography (sEMG) signals by non-linear probabilistic approach is useful in studying their transitions and thus the neuromuscular system. In this study, a method to visualize sEMG signals using Markov transition field (MTF) under fatigue condi...

In this work, an attempt has been made to characterize arousal and valence emotional states using Electroencephalogram (EEG) signals and Phase lag index (PLI) based functional connectivity features. For this, EEG signals are considered from a publicly available DEAP database. Signals are decomposed into four frequency bands, namely theta (θ, 4-7 Hz...

In this study, an attempt has been made to analyze the effect of the Extreme Learning Machine (ELM) classifier and its variants in the differentiation of Healthy Controls (HC) and Alzheimer's Disease (AD) using structural MR images. For this, sub-anatomic brain structures, namely Corpus Callosum (CC) and Lateral Ventricles (LV) are segmented and ch...

In this study, an explainable Bayesian Optimized (BO) LightGBM model is employed to differentiate the Corpus Callosal (CC) image features of Healthy Controls (HC) and Mild Cognitive Impairment (MCI). For this, Magnetic Resonance (MR) brain images obtained from a public database are pre-processed and CC is segmented using spatial fuzzy clustering-ba...

Accurate diagnosis of Alzheimer's disease (AD) in early stage can control the disease progression. Enlargement of Lateral Ventricles (LV) is one of the significant imaging biomarkers for the differentiation of Alzheimer's conditions. However, segmentation of accurate LV for analysis is still challenging. In this work, an attempt is made to segment...

Differentiation of cell organelle characteristics from microscopic images is a challenging task due to its intricate structural details. In this work, an attempt has been made to categorize Endoplasmic Reticulum (ER) and cytoplasm using orthogonal Zernike moments and Multilayer Perceptron (MLP). For this, Cell painted public source dataset comprisi...

Early-stage detection of cardiac autonomic neuropathy (CAN) is important for better management of the disease and prevents hospitalization. This study has investigated the complex nature of PR, QT, RR, and ST time segments of ECG signals by computing the fractal dimension (FD) of all segments from 20 min ECG recordings of people with different seve...

In recent years, noncontact measurements of vital signs using cameras received a great amount of interest. However, some questions are unanswered: (i) Which vital sign is monitored using what type of camera? (ii) What is the performance and which factors affect it? (iii) Which health issues are addressed by camera-based techniques? Following the pr...

Discriminating the cell organelles from microscopic images is a challenging task due to their high similarity in image appearance. In this work, an attempt has been made to differentiate nuclei, Endoplasmic Reticulum (ER) and cytoplasm using a texture pattern descriptor and Random Forest classifier. For this, Cell Painted public dataset from Broad...

In this work, an attempt has been made to classify arousal and valence states of emotion using time-domain features extracted from the Wavelet Packet Transform. For this, Electroencephalogram (EEG) signals from the publicly available DEAP database are considered. EEG signals are first decomposed using wavelet packet decomposition into θ, α, β, and...

In this work, an analysis based on complex demodulation is proposed to classify dichotomous emotional states using Electrodermal activity (EDA) signals. For this, annotated happy and sad EDA is obtained from an online public database. The sympathetic activity indices, namely Time-varying (TVSymp) and Modified TVSymp, are computed from the reconstru...

Viscoelastic properties of skeletal muscle tissue are known to be impacted by fatiguing contractions. In this study, an attempt has been made to utilize myotonometry for analyzing the relationship between muscle viscoelasticity and contractile behaviors in a fatiguing task. For this purpose, thirteen young healthy volunteers are recruited to perfor...

In this work, an attempt has been made to classify dichotomous emotional states using Electrodermal activity (EDA) and geometric features. For this, the annotated happy and sad EDA is obtained from the online public database. The EDA is subjected to discrete Fourier transform, and Fourier coefficients in the complex plane are obtained. The envelope...

The Corpus Callosum (CC) is a large white matter bundle that connects the left and right cerebral hemispheres of the human brain. It is susceptible to atrophy as Alzheimer’s disease progresses. The robust segmentation of CC allows quantitative investigation of its structural changes. However, deep learning-based CC segmentation is less explored. In...

Alzheimer’s Disease (AD) is a progressive irreversible neurodegenerative disorder which involves the deformations in brain sub-anatomic regions. Recent studies suggest that these deformations could be characterized using bi-planar information extracted from structural Magnetic Resonance (MR) image features. However, analysis and fusion of these b...

Background and Objective The rise of Drug Resistant Tuberculosis (DR TB), particularly Multi DR (MDR), and Extensively DR (XDR) has reduced the rate of control of the disease. Computer aided diagnosis using Chest X-rays (CXRs) can help in mass screening and timely diagnosis of DR TB, which is essential to administer proper treatment regimens. In CX...

In this work, an attempt has been made to analyze the influence of tissue viscoelasticity on the fatiguing behavior of skeletal muscle. For this purpose, myotonometry and surface electromyography (sEMG) signals are recorded from the biceps brachii muscle of adult volunteers. Viscoelastic characterization of muscle is carried out using two parameter...

Pedicle screw fixations are widely used to provide support and improve stability for the treatment of spinal pathologies. The effectiveness of treatment depends on the anchorage strength between the screw and bone. In this study, the influence of pedicle screw half-angle and bone quality on the displacement of fixation and stress transfer are analy...

Computer-assisted tools can aid in the detection of Alzheimer disease (AD) which is a progressive neurodegenerative disorder that can lead to cognitive impairments and eventually death. The accumulated effects due to AD can cause changes in the appearance of grey matter, white matter and cerebrospinal fluid in brain Magnetic Resonance (MR) images....