Feasibility and acceptability of an online epilepsy stigma self-management program.

Introduction: Stigma is a prevalent source of distress in people with epilepsy. We developed a self-paced online stigma self-management program for adults with epilepsy (Reducing Internalized Stigma in Epilepsy: A Behavioral Online Video Education, RISE ABOVE).

Materials And Methods: Twenty socio-demographically diverse participants completed RISE ABOVE over an average of 3.

Leveraging Trauma Informed Care for Digital Health Intervention Development in Opioid Use Disorder.

Digital health refers to the use of information and communication technologies in medicine (including smartphone apps, wearables, other non-invasive sensors, informatics and telehealth platforms) to prevent illness, deliver treatment, and promote wellness. This rapidly proliferating group of technologies has the potential to reduce harm for people with opioid use disorder (OUD) and facilitate the recovery process; however, development in this space for OUD has been slower compared to that for other medical conditions. Unique issues with OUD management surrounding patient provider relationships, interaction with the healthcare system, autonomy and trust sometimes hinder care approaches, including those in digital health.

Designing a Clinician-Centered Wearable Data Dashboard (CarePortal): Participatory Design Study.

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 psychological stress in daily life settings, providing helpful information for clinicians.

Characterizing the Impedance Properties of Dry E-Textile Electrodes Based on Contact Force and Perspiration.

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 forces and moisture conditions. Synthetic perspiration was applied using a moisture management tester and impedance was measured before and after exposure, followed by a 24 h controlled drying period.

A case for hybrid BCIs: combining optical and electrical modalities improves accuracy.

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 modalities ameliorating usability issues.

iTex Gloves: Design and In-Home Evaluation of an E-Textile Glove System for Tele-Assessment of Parkinson's Disease.

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 assessments conducted by trained clinicians.

Textile Knitted Stretch Sensors for Wearable Health Monitoring: Design and Performance Evaluation.

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 seamless sensing for WTS applications. Specifically, the knitted sensor has a unique intermeshing loop structure which is currently used to monitor repetitive body movements such as breathing (microscale motion) and walking (macroscale motion).

HapticLink: A Force-based Haptic Feedback System for Single and Double Lower-Limb Amputees.

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.

A modified surface EMG biomarker for gait assessment in spastic cerebral palsy.

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 through the widely accepted standard maximal isometric plantar flexion (IPF).

Methods: Ten control and 10 CP children with equinus gait pattern performed the BHR and IPF testing and walked barefoot 10-m distance.

An E-Textile Respiration Sensing System for NICU Monitoring: Design and Validation.

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.

The Validation of a Portable Functional NIRS System for Assessing Mental Workload.

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.

Frontal Functional Network Disruption Associated with Amyotrophic Lateral Sclerosis: An fNIRS-Based Minimum Spanning Tree Analysis.

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 suggested method to address this issue is minimum spanning tree (MST) analysis, which provides a less biased comparison.

Electrical and Hemodynamic Neural Functions in People With ALS: An EEG-fNIRS Resting-State Study.

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-hemodynamic neural functions. However, no study to date has explored simultaneous electrical and vascular-hemodynamic changes in the resting-state brain in ALS.

Merging fNIRS-EEG Brain Monitoring and Body Motion Capture to Distinguish Parkinsons Disease.

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 Parkinsons Disease (PD), a neurological progressive disorder characterized by movement symptoms including slowness of movement, stiffness, tremors at rest, and walking and standing instability. In this study, brain activity is recorded through functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG), and body kinematics were captured by a motion capture system (Mocap) based on an inertial measurement unit (IMU) for gross movements (large movements such as limb kinematics), and the WearUp glove for fine movements (small range movements such as finger kinematics).

Enhancing Communication for People in Late-Stage ALS Using an fNIRS-Based BCI System.

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 successfully control BCIs primarily for healthy cohorts, these systems are yet inefficient for people with severe motor disabilities like ALS. In this study, we developed a new fNIRS-based BCI system in concert with a single-trial Visuo-Mental (VM) paradigm to investigate the feasibility of enhanced communication for ALS patients, particularly those in the later stages of the disease.

A Comparative Characterization of Smart Textile Pressure Sensors.

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 these sensors underwent a series of tests that linearly increased and decreased a uniform pressure perpendicular to the surface of the sensors.

A Newcomer's Guide to Functional Near Infrared Spectroscopy Experiments.

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 recapitulate relevant anatomical and optical foundations and give a short historical overview.

WearLight: Toward a Wearable, Configurable Functional NIR Spectroscopy System for Noninvasive Neuroimaging.

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 multimodal studies involving electroencephalography. While fNIRS is still emerging on various fronts including hardware, software, algorithm, and applications, it still requires overcoming several scientific challenges associated with brain monitoring in naturalistic environments where the human participants are allowed to move and required to perform various tasks stimulating brain behaviors.

Hand Motion Detection in fNIRS Neuroimaging Data.

As the number of people diagnosed with movement disorders is increasing, it becomes vital to design techniques that allow the better understanding of human brain in naturalistic settings. There are many brain imaging methods such as fMRI, SPECT, and MEG that provide the functional information of the brain. However, these techniques have some limitations including immobility, cost, and motion artifacts.

Mobile Phonocardiogram Diagnosis in Newborns Using Support Vector Machine.

Phonocardiogram (PCG) monitoring on newborns is one of the most important and challenging tasks in the heart assessment in the early ages of life. In this paper, we present a novel approach for cardiac monitoring applied in PCG data. This basic system coupled with denoising, segmentation, cardiac cycle selection and classification of heart sound can be used widely for a large number of the data.

Designing and testing a wearable, wireless fNIRS patch.

Optical brain monitoring using near infrared (NIR) light has got a lot of attention in order to study the complexity of the brain due to several advantages as oppose to other methods such as EEG, fMRI and PET. There are a few commercially available functional NIR spectroscopy (fNIRS) brain monitoring systems, but they are still non-wearable and pose difficulties in scanning the brain while the participants are in motion. In this work, we present our endeavors to design and test a low-cost, wireless fNIRS patch using NIR light sources at wavelengths of 770 and 830nm, photodetectors and a microcontroller to trigger the light sources, read photodetector's output and transfer data wirelessly (via Bluetooth) to a smart-phone.

WearSense: Detecting Autism Stereotypic Behaviors through Smartwatches.

Autism is a complex developmental disorder that affects approximately 1 in 68 children (according to the recent survey conducted by the Centers for Disease Control and Prevention-CDC) in the U.S., and has become the fastest growing category of special education.

Multimodal 2D Brain Computer Interface.

In this work we used multimodal, non-invasive brain signal recording systems, namely Near Infrared Spectroscopy (NIRS), disc electrode electroencephalography (EEG) and tripolar concentric ring electrodes (TCRE) electroencephalography (tEEG). 7 healthy subjects participated in our experiments to control a 2-D Brain Computer Interface (BCI). Four motor imagery task were performed, imagery motion of the left hand, the right hand, both hands and both feet.