Kunal Mankodiya

University of Rhode Island | URI · Department of Electrical, Computer, and Biomedical Engineering

Background The recent growth of eHealth is unprecedented, especially after the COVID-19 pandemic. Within eHealth, wearable technology is increasingly being adopted because it can offer the remote monitoring of chronic and acute conditions in daily life environments. Wearable technology may be used to monitor and track key indicators of physical and...

Biopotential electrodes play an integral role within smart wearables and clothing in capturing vital signals like electrocardiogram (ECG), electromyogram (EMG), and electroencephalogram (EEG). This study focuses on dry e-textile electrodes (E1–E6) and a laser-cut knit electrode (E7), to assess their impedance characteristics under varying contact f...

Caring for someone with dementia can be stressful and less than 3% of effective psychosocial caregiver interventions have been translated for larger scale dissemination, possibly due to barriers (such as lack of personnel or limited time) that limit access. Technology-based interventions may increase accessibility. The current study obtained initia...

Near-infrared spectroscopy (NIRS) is a promising research tool that found its way into the field of brain-computer interfacing (BCI). BCI is crucially dependent on maximized usability thus demanding lightweight, compact, and low-cost hardware. We designed, built, and validated a hybrid BCI system incorporating one optical and two electrical modalit...

Parkinson’s disease (PD) is a neurological progressive movement disorder, affecting more than 10 million people globally. PD demands a longitudinal assessment of symptoms to monitor the disease progression and manage the treatments. Existing assessment methods require patients with PD (PwPD) to visit a clinic every 3–6 months to perform movement as...

The future generation of the Internet of Things (IoT) systems is characterized by the fusion of technologies—from edge–fog–cloud computing to artificial intelligence (AI) and blockchain—closing the gap between the physical and digital worlds [A1]. Although these technologies have been developed separately over time, the synergy among them has taken...

BACKGROUND The recent growth of eHealth is unprecedented, especially after the COVID-19 pandemic. Within eHealth, wearable technology is increasingly being adopted because it can offer the remote monitoring of chronic and acute conditions in daily life environments. Wearable technology may be used to monitor and track key indicators of physical and...

The advancement of smart textiles has led to significant interest in developing wearable textile sensors (WTS) and offering new modalities to sense vital signs and activity monitoring in daily life settings. For this, textile fabrication methods such as knitting, weaving, embroidery, and braiding offer promising pathways toward unobtrusive and seam...

Approximately 10 million people worldwide live with Parkinson's disease (PD), a progressive and incurable neurological movement disorder. Symptomatic treatment is available for PD but requires patients to make periodic clinic visits (2–3 times per year) for symptom assessment. Advanced telehealth technologies can enhance clinical care for PD but wa...

Objective: Stigma is common in people with epilepsy (PWE), detracting from quality of life. Yet, no effective anti-stigma self-management programs exist for PWE. Here, we showcase a multidisciplinary team’s effort to create a telehealth-accessible anti-stigma intervention. Method: Systematic review of empirical and theoretical research on epilepsy...

According to WHO, 15 millions babies are born preterm each year globally. Preterm infant (born before 37 weeks of gestation) are at a significantly higher risk of medical and surgical morbidity in comparison to babies born at term (around 37 weeks). Innovative solutions are warranted to meet the increased requirements of Neonatal Intensive Care Uni...

p>The digital transformation is characterized by the convergence of technologies — from the Internet of Things (IoT) to Edge-Fog-Cloud computing, Artificial Intelligence (AI), and Blockchain — in multiple dimensions blurring the lines between the physical and digital worlds. Although these innovations have evolved independently over time, they are...

p>The digital transformation is characterized by the convergence of technologies — from the Internet of Things (IoT) to Edge-Fog-Cloud computing, Artificial Intelligence (AI), and Blockchain — in multiple dimensions blurring the lines between the physical and digital worlds. Although these innovations have evolved independently over time, they are...

Lower limb amputation affects an estimated 1.71 million people in the US. The lack of sensory feedback and proprioception often causes loss of balance which heightens the risk of falls and injury. In this presented paper, a haptic feedback system named HapticLink was developed based on the weight distribution of the prosthetic foot to increase the...

The world is witnessing a rising number of preterm infants who are at significant risk of medical conditions. These infants require continuous care in Neonatal Intensive Care Units (NICU). Medical parameters are continuously monitored in premature infants in the NICU using a set of wired, sticky electrodes attached to the body. Medical adhesives us...

The digital transformation is characterized by the convergence of technologies -from the Internet of Things (IoT) to Edge-Fog-Cloud computing, Artificial Intelligence (AI), and Blockchain -in multiple dimensions blurring the lines between the physical and digital worlds. Although these innovations have evolved independently over time, they are incr...

This is a literature review paper covering state-of-the-art sleep technologies to measure sleep and clinical sleep disorders. This paper addresses an interdisciplinary audience from a variety of subdomains in engineering and medicine. We reviewed 120 scientific papers, 15 commercial mobile apps, and 4 commercial devices. We selected the papers from...

Objective Muscle clinical metrics are crucial for spastic cocontraction management in children with Cerebral Palsy (CP). We investigated whether the ankle plantar flexors cocontraction index (CCI) normalized with respect to the bipedal heel rise (BHR) approach provides more robust spastic cocontraction estimates during gait than those obtained thro...

Background Dementia caregivers are at risk for negative health outcomes. Caregiver interventions to address this risk are limited by time and personnel constraints. Mobile technology is one means of reaching many caregivers while mitigating these constraints. The aim of the current project was to obtain initial data from a month‐long beta test of a...

Portable functional near-infrared spectroscopy (fNIRS) systems have the potential to image the brain in naturalistic settings. Experimental studies are essential to validate such fNIRS systems. Working memory (WM) is a short-term active memory that is associated with the temporary storage and manipulation of information. The prefrontal cortex (PFC)...

The cortical role of the motor symptoms reflected by kinematic characteristics in Parkinson’s disease (PD) is poorly understood. In this study, we aim to explore how PD affects cortico-kinematic interactions. Electroencephalographic (EEG) and kinematic data were recorded from seven healthy participants and eight participants diagnosed with PD durin...

This book chapter is a tutorial-driven hands-on guide on data analytics for wearable sensor signals. The chapter takes an example of smart gloves integrated with flex/bend sensors on fingers measuring the angular movement of the knuckles. The gloves are designed to measure the motor symptoms of Parkinson’s disease. The movements of the fingers are...

Recent evidence increasingly associates network disruption in brain organization with multiple neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS), a rare terminal disease. However, the comparability of brain network characteristics across different studies remains a challenge for conventional graph theoretical methods. One su...

Caring for a person with dementia is associated with negative outcomes. Few caregiver interventions have been implemented in community settings. Mobile technology is one method for reaching many caregivers. This project translated two empirically-supported interventions for dementia caregivers into a mobile health application. A team of clinical re...

Objective: Amyotrophic lateral sclerosis (ALS) is a complex neurodegenerative disease that causes the progressive loss of voluntary muscle control. Recent studies have reported conflicting results on alterations in resting-state functional brain networks in ALS by adopting unimodal techniques that measure either electrophysiological or vascular-he...

A Mild traumatic brain injury (mTBI) or concussion has become a public health problem in the United State. Sports and recreational activities are major sources of concussions; with the most incidents connected to American football. Recently, many companies and research institutions have started studying concussions and introduced some means of prot...

Functional connectivity between the brain and body kinematics has largely not been investigated due to the requirement of motionlessness in neuroimaging techniques such as functional magnetic resonance imaging (fMRI). However, this connectivity is disrupted in many neurodegenerative disorders, including Parkinson’s Disease (PD), a neurological prog...

! Objective: Brain-computer interface (BCI) based communication remains a challenge for people with later-stage amyotrophic lateral sclerosis (ALS) who lose all voluntary muscle control. Although recent studies have demonstrated the feasibility of functional near-infrared spectroscopy (fNIRS) to control BCIs primarily for healthy cohorts, these s...

Geospatial data analysis using cloud computing platform is one of the promising areas for analysing, retrieving, and processing volumetric data. Fog computing paradigm assists cloud platform where fog devices try to increase the throughput and reduce latency at the edge of the client. In this research paper, the authors discuss two case studies on...

This review presents a practical primer for functional near-infrared spectroscopy (fNIRS) with respect to technology, experimentation, and analysis software. Its purpose is to jump-start interested practitioners considering utilizing a non-invasive, versatile, nevertheless challenging window into the brain using optical methods. We briefly recapitu...

Parkinsons disease has no known cure, but there do exist treatment plans which help those affected to slow the progression of the disease. These treatments are determined by the doctor's subjective observations of the patient during clinical visits. However, these visits are limited to just a few times a year. This paper attempts to migrate the sub...

Objective: Despite the high prevalence of non-motor impairments reported in patients with amyotrophic lateral sclerosis (ALS), little is known about the functional neural markers underlying such dysfunctions. In this study, a new dual-task multimodal framework relying on simultaneous electroencephalogram (EEG) and functional near-infrared spectros...

Linear and non-linear measures of heart rate variability (HRV) are widely investigated as non-invasive indicators of health. Stress has a profound impact on heart rate, and different meditation techniques have been found to modulate heartbeat rhythm. This paper aims to explore the process of identifying appropriate metrices from HRV analysis for so...

15-minute presentation on the accepted paper, "A Comparative Characterization of Textile Pressure Sensors".

Brain computer interfaces (BCI) using EEG, fNIRS and body motion (MoCap) data are getting more attention due to the fact that fNIRS and MoCap are not prone to movement artifacts similar to other brain imaging techniques such as EEG. Advancements in deep learning (neural networks) would allow the use of raw data for efficient feature extraction with...

This research study investigates the impact of various insulating textile materials on the performance of smart textile pressure sensors made of conductive threads and piezo resistive material. We designed four sets of identical textile-based pressure sensors – each of them integrating a different insulating textile substrate material. Each of thes...

Abstract—Smart textiles are becoming more popular in the last decade. This demo paper demonstrates the design and testing of a smart cushion integrated with e-textile pressure sensors to monitor activities on a chair including occupancy, sitting duration, and body posture and orientation. Our demo paper reports our initial results on the performanc...

Functional Diffuse Optical Tomography (fDOT) has the potential to provide the functional status of tissue by mapping 3D distribution of chromophores concentration in deep tissue non-inversely. Region-of-Interest (ROI) DOT, we presented earlier, uses optical patch using only a few NIR light sources and detectors arranged in a circular pattern for th...

Communication based on brain-computer interface (BCI) systems is still a challenge. Although most popular classes of BCIs heavily rely on electroencephalography (EEG), recent studies have demonstrated the feasibility of using functional near-infrared spectroscopy (fNIRS) as a reliable control signal in BCI systems. However, due to the inherent late...

Despite great advances in state-of-the-art brain-computer interfaces (BCIs), most BCIs do not consider users’ cognitive status during operation, which might have a critical role in BCI performance. This study proposes a novel multimodal BCI to concurrently measure electrical and hemodynamic activities using electroencephalography (EEG) and function...

Functional Near-infrared Spectroscopy (fNIRS) is an optical brain imaging technology based on mapping blood oxygenation levels on the cortical surface of the brain. fNIRS has the potential to become a point-of-care brain monitoring system for localized brain measurements in various medical conditions including brain injury and concussion. Although...

Spatial Data Infrastructure (SDI) is an important framework for sharing geospatial big data using the web. Integration of SDI with cloud computing led to emergence of Cloud-SDI as a tool for transmission, processing and analysis of geospatial data. Fog computing is a paradigm where embedded computers are employed to increase the throughput and redu...

The cloud and fog computing paradigms are developing area for storing, processing, and analysis of geospatial big data. Latest trend is mist computing which boost fog and cloud concepts for computing process where edge devices are used to help increase throughput and reduce latency to support at client edge. The present research article discussed t...

Big data analytics with the cloud computing are one of the emerging area for processing and analytics. Fog computing is the paradigm where fog devices help to reduce latency and increase throughput for assisting at the edge of the client. This article discusses the emergence of fog computing for mining analytics in big data from geospatial and medi...

This chapter proposes and develops a cloud-computing-based SDI model named as TCloud for sharing, analysis, and processing of spatial data particularly in the Temple City of India, Bhubaneswar. The main purpose of TCloud is to integrate all the spatial information such as tourism sites which include various temples, mosques, churches, monuments, la...

This work introduces Wearable deep learning (WearableDL) that is a unifying conceptual architecture inspired by the human nervous system, offering the convergence of deep learning (DL), Internet-of-things (IoT), and wearable technologies (WT) as follows: (1) the brain, the core of the central nervous system, represents deep learning for cloud compu...

Functional Near-Infrared Spectroscopy (fNIRS) has emerged as an effective brain monitoring technique to measure the hemodynamic response of the cortical surface. Its wide popularity and adoption in recent time attribute to its portability, ease of use, and flexibility in multi-modal studies involving electroencephalography (EEG). While fNIRS is sti...

Wrist-bands such as smartwatches have become an unobtrusive interface for collecting physiological and contextual data from users. Smartwatches are being used for smart healthcare, telecare, and wellness monitoring. In this paper, we used data collected from the AnEAR framework leveraging smartwatches to gather and store physiological data from pat...

This chapter proposes and develops a cloud-computing-based SDI model named as TCloud for sharing, analysis, and processing of spatial data particularly in the Temple City of India, Bhubaneswar. The main purpose of TCloud is to integrate all the spatial information such as tourism sites which include various temples, mosques, churches, monuments, la...

This book chapter discusses the concept of edge-assisted cloud computing and its relation to the emerging domain of “Fog-of-things (FoT)”. Such systems employ low-power embedded computers to provide local computation close to clients or cloud. The discussed architectures cover applications in medical, healthcare, wellness and fitness monitoring, ge...

Wearable photoplethysmography has recently become a common technology in heart rate (HR) monitoring. General observation is that the motion artifacts change the statistics of the acquired PPG signal. Consequently, estimation of HR from such a corrupted PPG signal is challenging. However, if an accelerometer is also used to acquire the acceleration...

The smart health paradigms employ Internet-connected wearables for tele-monitoring, diagnosis providing inexpensive healthcare solutions. Mist computing reduces latency and increases throughput by processing data near the edge of the network. In the present paper, we proposed a secure mist Computing architecture that is validated on recently releas...

Big data analytics with the cloud computing are one of the emerging area for processing and analytics. Fog computing is the paradigm where fog devices help to reduce latency and increase throughput for assisting at the edge of the client. This article discusses the emergence of fog computing for mining analytics in big data from geospatial and medi...

We report depth sensitivity enhancement of a region-of-interest optical tomographic system. Two optode configurations, 25 and 50 mm separations are used to construct a noise model. A regression technique isolates the functional activity of deep tissue layer.

The present manuscript concentrates on the application of Fog computing to a Smart Grid Network that comprises of a Distribution Generation System known as a Microgrid. It addresses features and advantages of a smart grid. Two computational methods for on-demand processing based on shared information resources is discussed. Fog Computing acts as an...

Geospatial data analysis with the help of cloud and fog computing are one of the emerging area for processing, storing and analysis of geospatial data. Mist computing is also one of the paradigm where fog devices help to reduce the latency period and increase throughput for assisting at the near of edge device of the client. It discusses the emerge...

The smart health paradigms employ Internet-connected wearables for tele-monitoring, diagnosis providing inexpensive healthcare solutions. Mist computing reduces latency and increases throughput by processing data near the edge of the network. In the present paper, we proposed a secure mist Computing architecture that is validated on recently releas...