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Conducting Yarn based Capacitive Humidity Sensor

Conducting Yarn based Capacitive Humidity Sensor

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Applied Sensing Conference (APSCON), IEEE

作者： Anupam Kumari Ajay Agarwal Angan Sengupta Yuvraj Garg Interdisciplinary Research Program of Space Science and Technology IIT Jodhpur Jodhpur India Dept. of Electrical Engineering IIT Jodhpur Jodhpur India Dept. of Chemical Engineering IIT Jodhpur Jodhpur India National Institute of Fashion Technology IIT Jodhpur Jodhpur India

Increasing demand for wearable sensors for multipurpose applications have made it an essential part of our everyday life. In such a scenario; reusability, flexibility, cost effectiveness, and integrability of such sensors are among the top desirable features. Using our casual clothing as sensors can be one of the most effective ways for various therapeutic, diagnostic, and continuous monitoring functionalities. Conducting yarns, possibly, have the capability to deeply influence the 4th industrial revolution and rule the e-textile based smart wearables for wide range applications. Herein, we present a comparative experimental study of three different capacitive sensor structures for humidity sensing applications. These structures have been explored using conducting yarns having tungsten metal as core conducting materials.

关键词： Wearable computers Tungsten Humidity Sensor phenomena and characterization Capacitive sensors Fourth Industrial Revolution Yarn

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Deep Learning Approach for EEG Classification in Lower-Limb Movement Phases: Towards Enhanced Brain-Computer Interface Control

Deep Learning Approach for EEG Classification in Lower-Limb ...

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IEEE/ASME International Conference on Mechtronic and Embedded Systems and Applications, MESA

作者： Cristian Felipe Blanco-Diaz Cristian David Guerrero-Mendez Guilherme Rangel Furtado Teodiano Bastos-Filho Rafhael Milanezi de Andrade Dept. of Excellence and AI The BioRobotics Institute Scuola Superiore Sant’Anna Pisa Italy Dept. Electronics and Biomedical Engineering Universidade Estadual de Campinas Campinas SP Brazil Dept. of Electrical Engineering Universidade Federal do Espírito Santo Vitória ES Brazil Posgraduate Program in Electrical Engineering Universidade Federal do Espírito Santo Vitória ES Brazil Graduate Program in Mechanical Engineering Universidade Federal do Espírito Santo Vitória ES Brazil

ISBN: (数字)9798331516239

ISBN: (纸本)9798331516246

Embedded Brain-Computer Interfaces (BCI) have emerged as an alternative for rehabilitation/assistance of people with neuromotor impairments. Data-driven methods are usually implemented to design controllers to (de)activate these systems using electroencephalography (EEG), which may limit usability and degrees of freedom. Thus, the development of more adaptive classifiers remains a challenge. This study focuses on the implementation of a Deep Learning (DL) method to classify EEG signals during different phases of gait and pedaling. To address this, public and in-house databases were used, which contain information on EEG and kinematic data during walking on a treadmill and pedaling on a minibike. Kinematic labels of the phases were extracted using k-means and classified by a Convolutional Neural Network (CNN), which demonstrated accuracy above 60%. Furthermore, a negative correlation was found between velocities and classifier performance metrics, suggesting that faster movements can hinder EEG decoding. Our proposal is a starting point to identify current states of lower-limb movement, which can be used for designing state machine-based controllers of robotic BCIs with rehabilitation or assistance purposes, such as motorized mini exercise bikes or leg exoskeletons.

关键词： Legged locomotion Deep learning Mechatronics Kinematics Electroencephalography Brain-computer interfaces Convolutional neural networks Proposals Usability Robots

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Using textile capacitive sensors to train synchronized movement of hands

Using textile capacitive sensors to train synchronized movem...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Chang-Ming Yang Shu-Cing Wu Shih-Hung Chen Ze-We Wu Kuo-Cheng Liao Chi-Chun Chen Ming Young Biomedical Corp. Miaoli Taiwan Program Prospective Technology of Electrical Engineering and Computer Science National Chin-Yi University of Technology Taichung Taiwan Dept. of Computer Science and Information Engineering National Chin-Yi University of Technology Taichung Taiwan Dept. of Electronic Engineering National Chin-Yi University of Technology Taichung Taiwan

This study introduced a capacitive sensing interactive game platform aimed at promoting emotional stability, which we have named the “Sunrise and Sunset” game. This game primarily consists of two pieces of regular textile fabric enveloping conductive silver fabric. A microcontroller was employed to extract the sensed capacitive values, and a game named “Sunrise and Sunset” is designed to complement the slow raising and lowering of both hands. The development of this gaming platform has the potential to offer a novel method of emotional management, particularly in high-stress living environments. It can serve as an effective relaxation tool, aiding individuals in emotional balance, anxiety reduction, and stress alleviation. Simultaneously, this platform can contribute to the promotion of mental well-being, providing an engaging and beneficial means for people to manage their emotions and moods.

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The Community Human Development Index (CHDI) as a Precision Public Health Vulnerability Metric and Risk Indicator for Predictive Analytics

The Community Human Development Index (CHDI) as a Precision ...

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2023 IEEE Conference on Technologies for Sustainability, SusTech 2023

作者： Sheth, Suraj Bettencourt, Luis Pritzker School of Medicine and Interdisciplinary Scientist Training Program United States Biomedical Informatics Precision Medicine and Global Health Mansueto Institute for Urban Innovation University of Chicago ChicagoIL United States Mansueto Institute for Urban Innovation United States Ecology and Evolution United States University of Chicago Dept. of Sociology ChicagoIL United States External of Complex Systems Santa Fe Institute United States

ISBN: (纸本)9798350345483

Accurately assessing and measuring population vulnerability across geographic scales is critical for health risk management of sustainable communities. Currently, the most widely used metric for vulnerability analysis in the United States is the Centers for Disease Control and Prevention's Social Vulnerability Index (SVI), a metric which has proven its utility in a number of circumstances. However, at times, its structure limits its use in international contexts and longitudinal studies. We propose the use of the Community Human Development Index (CHDI), a scalable and predictive tool, to address these gaps. Based on the setting, the CHDI can work either as a complementary metric alongside the SVI or as an alternative vulnerability metric. In our comprehensive study of over 70,000 census tracts in the United States, we found that CHDI correlates well with SVI at the neighborhood scale, while also capturing uniquely different information about the vulnerability of populations. We also found that the CHDI predicts community health outcomes as well or better than the SVI, and can be used as a proxy to measure changes in overall health risks to communities. As a Precision Public Health metric for population health vulnerability analysis and as a performance indicator of community health, CHDI can be used to provide an analytical basis for policy decision making. CHDI can be utilized to promote health equity across a broad range of communities through more accurate health risk assessments leading to strategic, targeted, and timely interventions for better health outcomes. © 2023 IEEE.

关键词： Risk management

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Sensory-Targeted Intraspinal Microstimulation for Spinal Cord Injury Rehabilitation

Sensory-Targeted Intraspinal Microstimulation for Spinal Cor...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Gerson N. Moreno Romero Maria F. Bandres Jacob G. McPherson Dept. of Biomedical Engineering Program in Physical Therapy Washington University in St. Louis St. Louis USA Dept. of Anesthesiology Prog. Neurosciences Dept. of Biomed. Eng. Washingon Univ. Pain Ctr Prog. Physical Therapy Washington University School of Medicine St. Louis USA

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Spinal Cord Injury (SCI) alters the excitability of neurons below the lesion, contributing to sensorimotor impairments. Less commonly acknowledged is SCI-related neuropathic pain (SCI-NP) that develops during the chronic phase of SCI, whose neural mechanisms are not yet fully understood. Previous work has demonstrated that electrical intraspinal microstimulation (ISMS) delivered amidst the spinal motor pools inside the ventral spinal gray matter causes an unexpected depression of sensory neuron responsiveness to nociceptive transmissions [1]. Given the lack of efficacious therapeutics for SCI-NP, we explored whether ISMS delivered in the sensory-dominant dorsal horn of the spinal cord could drive more robust depressive effects on pain-related transmission. Preliminary outcomes looked at population-level and single neuron-level modulatory actions of ISMS on neural transmission throughout the gray matter of a single segment of the lumbar enlargement in vivo in rats. Our preliminary results suggest dorsal ISMS may be less efficacious than motor-targeted ISMS at reducing spinal responsiveness to nociceptive sensory feedback. Future work will be required to determine the consistency of this finding and, if warranted, to optimize the stimulation parameters for multi-modal and/or pain-related applications.

关键词： In vivo Neurons Grey matter Motors Depression Spinal cord injury Lesions engineering in medicine and biology Neuropathic pain

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Chronic Spinal Cord Injury Increases Spontaneous Intraspinal Neural Transmission and Spike Train Variability

Chronic Spinal Cord Injury Increases Spontaneous Intraspinal...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Maria F. Bandres Jacob G. McPherson Dept. of Biomedical Engineering Program in Physical Therapy Washington University School of Medicine St. Louis USA Dept. of Anesthesiology Prog. Neurosciences Dept. of Biomed. Eng. Prog. Physical Therapy Washingon Univ. Pain Ctr Washington University School of Medicine St. Louis USA

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Spinal cord injury (SCI) often leads to increased spontaneous activity (SpAP) and responsiveness to sensory feedback. This hyperexcitable state contributes to the development and maintenance of SCI-related neuropathic pain (SCI-NP). In general, characterizations of SpAP in the context of SCI-NP focus on the dorsal horns and sensory-processing neurons. As a result, changes in SpAP in the integrative intermediate gray and the motor-dominant ventral horn after SCI are considerably less understood. Thus, it is unclear whether altered firing dynamics in SpAP throughout the dorso-ventral extent of the spinal gray matter contribute to SCI-NP. Here we characterize the firing dynamics of dorsal and ventral interneurons in vivo in neurologically intact rats and rats with chronic SCI with and without SCI-NP. We find (1) robust SpAP throughout the dorsoventral extent of the spinal gray matter after chronic SCI and chronic SCI-NP; (2) that animals with SCI-NP showed higher spontaneous discharge rates compared to the other animal groups, particularly in the ventral horns; and (3) that animals with chronic SCI exhibited higher neuronal variability compared to neurologically intact animals. Together, the results suggest that increased SpAP in dorsal and ventral neurons may further exacerbate pathological sensory transmission after SCI and be a component of SCI-NP.

关键词： Pathology In vivo Firing Neurons Grey matter Rats Maintenance Spinal cord injury engineering in medicine and biology Neuropathic pain

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Nonlinear Firing Dynamics in Spinal Interneurons May Delineate the Presence or Absence of Spinal Cord Injury-related Neuropathic Pain

Nonlinear Firing Dynamics in Spinal Interneurons May Delinea...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Avery R. Twyman Maria F. Bandres Jacob G. McPherson Dept. of Biomedical Engineering Program in Physical Therapy Washington University in St. Louis St. Louis USA Dept. of Anesthesiology Prog. Neurosciences Dept. of Biomed. Eng. Prog. Physical Therapy Washingon Univ. Pain Ctr Washington University School of Medicine St. Louis USA

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Spinal cord injury (SCI) often results in hyperexcitability of sensory-dominant regions of the spinal cord, leading to muscle spasms, spasticity, and SCI-related neuropathic pain (SCI-NP). In part, these symptoms are due to injury-induced alterations in neuromodulatory drive. Altered neuromodulatory drive changes a neuron’s input-output function, increasing or decreasing its sensitivity to a given excitatory or inhibitory input through actions on metabotropic receptors on the dendrites. Many of these actions result in downstream effects on the voltage-gated ion channels that mediate persistent inward currents (PICs), which can markedly exaggerate the gain of a given spinal neuron to a synaptic input(s). Here, we hypothesize that SCI-NP is associated with altered neuromodulatory drive, revealed through the firing dynamics of sensory interneurons in the spinal cord. We find evidence of altered PICs and associated self-sustained firing as well as firing state changes in rats with and rats without SCI-NP, however we find a greater prevalence of features associated with altered neuromodulation in animals with SCI-NP than those without.

关键词： Sensitivity Firing Rats Muscles Ions Dendrites (neurons) Spinal cord injury Neuromodulation engineering in medicine and biology Neuropathic pain

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Electronically Scanned Large Apertures for Interventional and Diagnostic Liver

Electronically Scanned Large Apertures for Interventional an...

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IEEE Symposium (IUS) Ultrasonics

作者： Robert Wodnicki Junhang Zhang Qifa Zhou Josquin Foiret Christophe Notard Katherine W. Ferrara Dept. of Biomedical Engineering University of Southern California Los Angeles CA USA Molecular Imaging Program at Stanford University Stanford CA Vermon S.A. Tours France

We have developed a handheld 1,024-element large area 2D array probe integrated with high voltage multiplexing ASIC modules with row-multiplexed imaging in orthogonal azimuthal and elevational planes with image data computed and displayed on a commercially available 32 channel configurable ultrasound system. Here we demonstrate real-time orthogonal imaging of small structures at high resolution in water with the 1,024-element array. We have also integrated modular imaging electronics with a newly designed 4,096-element 4 times larger aperture acoustic array (83 mm × 16 mm aperture with 650 µm azi. × 500 µm elev. element pitch) with 128 elements in azimuth and 32 rows in elevation. The two arrays were interfaced to an open-platform ultrasound imaging system using custom-designed multiplexing ASICs and imaged with plane waves at Fc = 2.5 MHz.

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Spinal Noradrenergic Alpha-2 Receptors Mediate the Antinociceptive Effects of Therapeutic Intraspinal Microstimulation

Spinal Noradrenergic Alpha-2 Receptors Mediate the Antinocic...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Javier Lucas-Romero Maria F. Bandres Jacob G. McPherson Program in Physical Therapy Washington University School of Medicine St. Louis USA Dept. of Biomedical Engineering Program in Physical Therapy Washington University School of Medicine St. Louis USA Dept. of Anesthesiology Prog. Neurosciences Dept. of Biomed. Eng. Prog. Physical Therapy Washingon Univ. Pain Ctr Washington University School of Medicine St. Louis USA

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

This study investigates the role of noradrenergic signaling in the antinociceptive effects of intraspinal microstimulation intended to restore movement after spinal cord injury. Two rat cohorts, intact and with chronic spinal cord injury, underwent intraspinal microstimulation (ISMS), and the multiunit neuronal response to peripheral noxious stimulation was examined at the spinal cord level. The observed effects were compared with those after blocking alpha-2 adrenergic receptors using RX821002. SCI heightened the nociceptive response to pinch stimulation, but ISMS exhibited clear antinociceptive effects in both intact and injured groups. These effects were nullified by blocking alpha-2 receptors, highlighting their involvement in the depression of nociceptive processing induced by ISMS.

关键词： Depression Spinal cord injury engineering in medicine and biology

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AI In Healthcare: Using Bayesian Networks To Predict Response To Immune Checkpoint Blockades

AI In Healthcare: Using Bayesian Networks To Predict Respons...

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National Conference on Radio Science (NSRC)

作者： Ahmed H. Saadawy Aly F. Hissam Eman Badr Omar M. Fahmy Biomedical Sciences Program Zewail City of Science and Technology Giza Egypt Faculty of Computers and Artificial Intelligence Cairo University Giza Egypt Omar Mamdouh Fahmy Electrical Engineering Dept. Badr University in Cairo Giza Egypt

Cancer remains a leading cause of death worldwide, with its heterogeneous and patient-specific nature complicating treatment. Immunotherapy, especially immune checkpoint blockades (ICB), shows promising potential by reactivating the immune system to detect and destroy cancer cells. However, their effectiveness largely depends on the patient’s clinical and molecular characteristics, making them unsuitable for everyone. This highlights the importance of developing predictive and interpretable models that could distinguish potential responders from non-responders. This study aims to utilize gene expression data to predict patients’ responses to ICB and identify key genes whose expression is associated with treatment outcome using probabilistic Bayesian networks (BNs). To address the high-dimensional nature of gene expression data, we propose and compare the use of machine learning-based feature selection (FS) and clustering by weighted gene co-expression network analysis (WGCNA). To our knowledge, this is the first study to apply BNs along with FS and WGCNA dimensionality reduction techniques to tackle ICB response using transcriptomic data. We achieved a maximal classification accuracy of 75% and identified eight genes and two gene clusters directly influencing ICB response. These results may offer more biological insights and mechanisms underlying ICB response. The proposed pipeline will contribute to guiding treatment decisions, minimizing harmful side effects, and reducing the financial costs associated with ineffective treatments.

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