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检索条件"任意字段=Conference on Smart Biomedical and Physiological Sensor Technology XIX"

共 128 条记录，以下是21-30 订阅

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smart Health Monitoring for Comatose Patients: Integrating IoT and Real-Time Alerts

Smart Health Monitoring for Comatose Patients: Integrating I...

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International conference of Electronics, Communication and Aerospace technology (ICECA)

作者： K Thivyabrabha C Saranya R Aakash T Abishek S Mohamed Hussain Department of Biomedical Engineering Nandha Engineering College Erode India

ISBN: (数字)9798350367904

ISBN: (纸本)9798350367911

This research study develops a specialized monitoring and warning system tailored for coma patients to ensure timely and accurate assessment of their health status. The system integrates various physiological markers, including temperature, heart rate, urine level, finger movement, and blink frequency, using non-invasive sensors. Alongside critical indicators, it continuously monitors these parameters to enable rapid caregiver and medical specialist responses to significant changes in the patient’s condition. Additionally, the system incorporates email and phone notifications for immediate alerts. A computer vision-based eye blink monitoring module tracks and evaluates neurological activity through blink frequency analysis. Furthermore, a real-time urine level monitoring system employs sensors to gather and transmit data, facilitating early detection of potential health issues. Future work includes leveraging AI and machine learning for predictive analytics and enhancing interoperability with other medical devices for comprehensive healthcare management.

关键词： Temperature sensors Temperature measurement Accuracy Tracking Fingers sensor systems Real-time systems Reliability biomedical monitoring Monitoring

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Optimized Stacked Sparse Autoencoder for IoT-Cloud smart Healthcare Networks

Optimized Stacked Sparse Autoencoder for IoT-Cloud Smart Hea...

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Sentiment Analysis and Deep Learning (ICSADL), International conference on

作者： Baba Fakruddin Ali B H L. Guganathan Prasanta Kumar Parida D. Samundeeswari Sridhar S Department of CSE Nagarjuna College of engineering and technology Bengaluru Karnataka India Department of Physics Saveetha School of Engineering Saveetha Insitute of Medical and Technical science (SIMATS) Thandalam Chennai Tamil Nadu India School of Rural Management KIIT University Bhubaneswar Odisha India Department of Mathematics Panimalar Engineering College Chennai Tamil Nadu India Department of Research Rajalakshmi Institute of Technology (Autonomous) Chennai Tamil Nadu India

ISBN: (数字)9798331523923

ISBN: (纸本)9798331523930

IoT technology growth in healthcare has been a revolution, and that is exciting, with the monitoring of real-time critical physiological and clinical parameters from real-time data: data-driven, personalized healthcare solutions. Even with such potential, health IoT faces challenges such as heterogeneity in data, noise, and inconsistent feature extraction that leads to suboptimal decision-making. Methods have to be developed efficiently for preprocessing and feature extraction to analyze data so that this disease can be predicted or monitored correctly. The motivation is to design a solid framework that bridges such gaps by making sure reliable, accurate predictions fit the smart healthcare application. Testing the proposed system with IoT-enabled wearable devices and clinical electronic health records (EHR), physiological metrics were collected from IoT sensors, supplemented by medical history and diagnostic data retrieved from cloud databases for blood pressure, heart rate, glucose levels, and oxygen saturation. The pre-processing step utilized Global-Local Depth Normalization (GLDN), which normalizes global structures and local variances to remove noise and scale variations. These features were analyzed using a Stacked Sparse Autoencoder (SSAE), optimized by Cat Hunting Optimization (CHO) to enhance prediction accuracy and computational efficiency. Experimental results validate the system with a remarkable 99.7% accuracy, 98.1% precision, and 97.5% recall and reduces computation time by 22% compared to the existing techniques. This shows the robustness and feasibility of the proposed approach in applications of smart healthcare. In conclusion, this framework represents an effective solution for smart healthcare systems that deals with data heterogeneity and the challenge of feature optimization for better patient care and resource management in IoT-driven environments.

关键词： Cloud computing Accuracy Autoencoders Medical services sensor systems Real-time systems biomedical monitoring Optimization Monitoring Diseases

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Hybrid sensor Insole for Wearable Ballistocardiography in Remote Health Monitoring

Hybrid Sensor Insole for Wearable Ballistocardiography in Re...

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IEEE International conference on Flexible and Printable sensors and Systems (FLEPS)

作者： Bastian Latsch Omar Ben Dali Benedikt Hench Romol Chadda Youssef Sellami Alexander A. Altmann Niklas Schäfer Julian Seiler Mario Kupnik Measurement and Sensor Technology Group Technische Universität Darmstadt Germany

ISBN: (数字)9798350383263

ISBN: (纸本)9798350383270

Remote health monitoring improves the quality of life by enabling an early condition detection. The human heartbeat qualifies as physiological measure for body vitality and can be acquired through unobtrusive ballistocardiography (BCG). Current wearable BCG devices lack customizability and posture detection of the wearer. In this work, we present a hybrid insole concept with piezoelectric ferroelectrets and piezoresistive Velostat sensors to complement their properties. The Velostat sensor is evaluated in a universal testing machine with an applied load up to 50 N, resulting in a sensitivity of 200 Ohm/N and 80% resistance change. It reliably activates the BCG once the insole wearer maintains a stable posture. The experiment involves three participants in upright posture on the smart insole, at resting pulse and after physical activity. We apply a continuous wavelet transform to the ferroelectret sensor data to enhance feature detection. The heart rate is extracted from the peak distance and, for resting pulse, aligns with the reference heartbeat acquired from a chest strap. Thus, our hybrid insole system proves suitable as a wearable heart rate detector for health monitoring.

关键词： Sensitivity Heart beat sensor systems Reliability biomedical monitoring Intelligent sensors Wearable sensors

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smart Savior: A Life Jacket Integrated IoT Emergency Response System Utilizing TTGO T-Call ESP32 and Advanced sensor Technologies

Smart Savior: A Life Jacket Integrated IoT Emergency Respons...

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International conference on Robotics,Electrical and Signal Processing Techniques (ICREST)

作者： Md. Jakarea Debopom Sutradhar Ariful Islam Talukder S.M. Azizul Hoque Sourov Ripon Kumar Debnath Md Shifat Karim Md. Tamzidul Islam Nion Tania Akter Helena Bulbul Department of EEE United International University Dhaka Bangladesh Department of CSE United International University Dhaka Bangladesh Department of BBA United International University Dhaka Bangladesh

ISBN: (数字)9798331530952

ISBN: (纸本)9798331530969

Life jackets are crucial for aquatic safety, preventing drowning and aiding in rescue. However, locating survivors can be challenging. The smart Savior life jacket, enhanced with IoT technology, integrates advanced sensors into a wristband and jacket to monitor environmental and physiological data. Key components include the NEO-6M GPS module, heart rate and body temperature sensors, and the ESP32 microprocessor. Data is transmitted via ESP-NOW for real-time monitoring and analysis. Rescue teams access a dynamic dashboard to prioritize rescue efforts based on geolocation and critical health indicators. The system's performance, evaluated against industry standards, shows faster GPS connectivity, real-time data synchronization, and improved accuracy in heart rate monitoring (98%) and water temperature sensing (±0.5 ∘ C). This integration offers a robust and effective approach to enhancing safety and responsiveness during aquatic disasters, making it a vital tool in saving lives.

关键词： Temperature sensors Heart rate Geology Robot sensing systems Real-time systems sensor systems biomedical monitoring Intelligent sensors Monitoring Global Positioning System

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Multimodal sensor-based identification of stress and compulsive actions in children with obsessive-compulsive disorder for telemedical treatment 44

Multimodal sensor-based identification of stress and compuls...

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44th Annual International conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)

作者： Thierfelder, Annika Primbs, Jonas Severitt, Bjorn Hohnecker, Carolin S. Kuhnhausen, Jan Alt, Annika K. Pascher, Anja Worz, Ursula Passon, Helene Seemann, Jens Ernst, Christian Lautenbacher, Heinrich Holderried, Martin Kasneci, Enkelejda Giese, Martin A. Bulling, Andreas Menth, Michael Barth, Gottfried M. Ilg, Winfried Hollmann, Karsten Renner, Tobias J. Univ Tubingen Hertie Inst Clin Brain Res Sect Theoret Sensorimotor Control Tubingen Germany Univ Tubingen Dept Comp Sci Commun Networks Tubingen Germany Univ Tubingen Dept Comp Sci Human Comp Interact Tubingen Germany Univ Hosp Tubingen Psychiat Psychosomat & Psychotherapy Childhood & Tubingen Germany Univ Hosp Tubingen Sect Informat Technol Tubingen Germany Univ Hohenheim Inst Healthcare & Publ Management Stuttgart Germany Univ Tubingen Dept Strateg Med Dev & Qual Management Tubingen Germany Univ Stuttgart Inst Visualisat & Interact Syst Stuttgart Germany

ISBN: (数字)9781728127828

ISBN: (纸本)9781728127828

In modern psychotherapy, digital health technology offers advanced and personalized therapy options, increasing availability as well as ecological validity. These aspects have proven to be highly relevant for children and adolescents with obsessive-compulsive disorder (OCD). Exposure and Response Prevention therapy, which is the state-of-the-art treatment for OCD, builds on the reconstruction of everyday life exposure to anxious situations. However, while compulsive behavior pre-dominantly occurs in home environments, exposure situations during therapy are limited to clinical settings. Telemedical treatment allows to shift from this limited exposure reconstruction to exposure situations in real life. In the SSTeP KiZ study (smart sensor technology in telepsychotherapy for children and adolescents with OCD), we combine video therapy with wearable sensors delivering physiological and behavioral measures to objectively determine the stress level of patients. The setup allows to gain information from exposure to stress in a realistic environment both during and outside of therapy sessions. In a first pilot study, we explored the sensitivity of individual sensor modalities to different levels of stress and anxiety. For this, we captured the obsessive-compulsive behavior of five adolescents with an ECG chest belt, inertial sensors capturing hand movements, and an eye tracker. Despite their prototypical nature, our results deliver strong evidence that the examined sensor modalities yield biomarkers allowing for personalized detection and quantification of stress and anxiety. This opens up future possibilities to evaluate the severity of individual compulsive behavior based on multi-variate state classification in real-life situations.

关键词： Pediatrics Sensitivity Tracking Anxiety disorders Medical treatment Behavioral sciences biomedical monitoring

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Wireless sensor Networks for Sports Injury Management and Player Safety Enhancement

Wireless Sensor Networks for Sports Injury Management and Pl...

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Self Sustainable Artificial Intelligence Systems (ICSSAS), International conference on

作者： K. Bashkaran S. Selvarasu S. Valarmathy K. Radhika M. Muthulekshmi Department of Biomedical Engineering Kongunadu College of Engineering and Technology Thottium Tamil Nadu India Department of Electronics and Communication Engineering Sri Shanmugha College of Engineering and Technology Salem Tamil Nadu India Department of Electronics and Communication Engineering Vinayaka Mission's Kirupananda Variyar Engineering College Salem Tamil nadu India Department of Electronics and Communication Engineering Muthayammal Engineering College Rasipuram Tamil Nadu India Department of Biomedical Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India

Injuries in sports may be better managed, and player safety can be improved by using wireless sensor networks. All aspects of a player's performance may be tracked in realtime because of these networks' capacity for collecting, analyzing, and communicating data. Heart rate, body temperature, acceleration, and joint movement are just a few of the physiological and biomechanical factors investigated in this paper and relates to the use of wearable sensors and smart devices to monitor these variables. The data are sent wirelessly to a central system where sophisticated analytics are used to identify risks for injuries, track trends in performance, and allow for prompt action. Given the potential benefits to players' health and performance, the proposed system might bring to sports medicine, it's easy to view why it's getting so much attention. It suggests wireless sensor networks and the Internet of Things may work together to improve sports safety and injury prevention.

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Monitoring Vital Parameters of Comatose Patients using smart sensors Integrated with Cloud Storage

Monitoring Vital Parameters of Comatose Patients using Smart...

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International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)

作者： P. Sinthia Malathi. M Sripriya. T Rahul Krishnan Gurumoorthy. G K. Jalaldeen Dept. of Biomedical Engineering Saveetha Engineering College Chennai India Dept. of ECE Rajalakshmi Institute of Technology Chennai India Dept. of ECE Jeppiaar Institute of Technology Chennai India Dept. of ECE SRM Institute of Science and Technology Chennai India Dept. of Medical Electronics Saveetha Engineering College Chennai India Dept. of ECE Solamalai College of Engineering Chennai India

ISBN: (数字)9798350376425

ISBN: (纸本)9798350376432

The monitoring of comatose patients is critical for identifying adverse changes in their physiological state and ensuring timely medical intervention. This research presents a novel IoT-based system for remotely monitoring and assessing vital signs in comatose patients. The proposed system utilizes various IoT sensors to measure pulse, respiratory rate, and eye movement, transmitting data to a centralized database and connected devices for real-time monitoring by healthcare professionals and family members. This approach offers a significant improvement over traditional observation methods, which can be time-consuming and prone to human error. By providing up-to-date information about the patient's vital signs and body movements, the IoT-based system enhances the quality of care and improves patient outcomes. This paper discusses the system's characteristics, building blocks, and implementation challenges based on existing research in this area.

关键词： Temperature sensors Cloud computing Pulse measurements Medical services sensor systems Real-time systems Reliability smart devices Monitoring Intelligent sensors

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IoMT & ML Model to Detect Stress in Human

IoMT & ML Model to Detect Stress in Human

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International conference on Computational and Characterization Techniques in Engineering & Sciences (CCTES)

作者： Bhaludra R Nadh Singh Sindhura Ghanta Thokala SaiShivani Basingala Sai Vaishnavi Polishetty Sravya Shaik Shifa Department of Computer Science and Engineering Bhoj Reddy Engineering College for Women Hyderabad India Department of Computer Science and Engineering Bhoj Reddy Engineering College Hyderabad India Department of Computer Science and Engineering Bhoj Reddy Engineering College Hyderabad Telangana India Department of Information Technology (IT) Bhoj Reddy Engineering College Hyderabad India

ISBN: (数字)9798350364699

ISBN: (纸本)9798350364705

Today's fast-moving surroundings cause stress for heaps. Real-time stress administration may be troublesome, regardless of the allure of negative effects on tangible and insane fitness. ML, IoMT, and AI abilities change how we live and work and solve this question. "A smart biomedical Healthcare System to Detect Stress Utilizing IoT, Machine Learning and Artificial Intelligence," intends to utilize physiological sensors like soul rate, hotness, dampness (sweat) sensors and first verbalizations to detect stress. The submitted approach can path and categories folk into "difficult" and "non-tense" circumstances. Our classification results manifest the advantage of our approach in certain-occasion stress identification. The main aim of the original search out supports a novel procedure of identifying early stress something did surroundings, knowledge atmospheres, and administrative settings to support laborers’ and scholars' welfare and someday increase productivity

关键词： Temperature sensors Temperature measurement Anxiety disorders Real-time systems sensor systems Biosensors biomedical monitoring Intelligent sensors Stress Monitoring

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IIoTHRT: Experimental Analysis of Heart Rate Tracking Methodology Using Intelligent sensors and Internet of Things Assistance

IIoTHRT: Experimental Analysis of Heart Rate Tracking Method...

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Sustainable Computing and smart Systems (ICSCSS), International conference on

作者： P. Pakutharivu P. Mahalakshmi Bhushan P. Saoji A. Padmashree R. Thiagarajan S. Arun Department of Computer Science Anna Adarsh College For Women Chennai India Department of CSE Jerusalem College of Engineering Chennai India Dept of Instrumentation Engineering Bharati Vidyapeeth college of Engineering Navi Mumbai India Department of CSBS Bannari Amman Institute of Technology Sathyamangalam India Department of IT Prathyusha Engineering College Chennai Tamilnadu India Department of ECE Jerusalem College of Engineering Chennai India

ISBN: (数字)9798350379990

ISBN: (纸本)9798350391558

Improvements in disease prevention and patient health maintenance made possible by technological advancements have given rise to new areas of study, including systems for monitoring. Vital signs, such as heart rate, indicate how healthy a person's cardiovascular system is. Multiple physiological states are reflected in heart rate, which is defined as the number of beats per minute. These states include biological workload, tension at work and attention on tasks, lethargy, and the heightened state of activity of the nervous system that controls breathing. The electrocardiogram (ECG) waveform or the sensation of the pulse (the regulated enlargement and constriction of an artery caused by the periodic contractions of the heart) is two ways to quantify it. In places where the blood vessel is near to the skin, one may feel the pulse. In order to assess the efficacy of the suggested model, this study details a method for measuring heart rate using an Arduino and the Internet of Things (IoT) known as Intelligent IoT based Heart Rate Tracker (IIoTHRT). The physiological status of a person may be studied by counting the heart beats per minute. This can tell us a lot about their stress levels, how active their autonomic nervous system is, how fatigued they are, and how hard they are working. There is a shift in the blood volume inside the finger artery because the heart is pumping blood throughout the body when it beats. Around the fingertip, there is an optical sensor system that may detect this blood fluctuation. With the help of serial port messages, the signal may be enhanced and transmitted to Arduino. The proposed program allows for the monitoring and calculation of heart rates. The sensor components are photodiode and infrared LED. The infrared light from the LED is reflected back into the fingertip by the blood in the finger arteries. The outcomes demonstrate that this app can read heart rate values and show them on an Android screen. It just takes around 5 or 6 secon

关键词： Heart rate Fingers Message services Light emitting diodes Control systems Internet of Things biomedical monitoring

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μ-Phone: Accessible Microscope Attachment for smartphones

μ-Phone: Accessible Microscope Attachment for Smartphones

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International Workshop on Wearable and Implantable Body sensor Networks (BSN)

作者： Kefan Song Sixuan Wu Ruijia Peng Jason Cobb Alexander T Adams Wallace H. Coulter Department of Biomedical Engineering Georgia Institute of Technology Atlanta GA USA School of Interactive Computing Georgia Institute of Technology Atlanta GA USA School of Computer Science Georgia Institute of Technology Atlanta GA USA Renal Medicine Emory University School of Medicine Atlanta GA USA

ISBN: (数字)9798331530143

ISBN: (纸本)9798331530150

Point-of-care (POC) technologies have the potential to greatly improve the clinical lab testing and diagnostics process since they significantly reduce the wait time before getting the results. Microscope, as a very important instrument widely used in clinical testing, is a key component to be adapted to POC scenarios, and there have been various attempts to do so by replacing conventional microscopes with smartphone-attached systems. However, these attempts all utilized components that are either expensive or bulky, which greatly limits the widespread adaptation and utilization of these devices, especially in areas with limited resources. Thus we propose a design and prototype of $\mu$ -Phone, an accessible microscope attachment for smartphones using cheap and easily accessible components to minimize the obstacles to resource availability. The proposed system has a depth of field of 5.25 micrometers, a pixel resolution of 26.3 pixels per micrometer and a spatial resolution of 2.19 micrometers, which makes it powerful enough to capture microscopic images for identification and analysis at a cellular level. With some future developments, this system has great potential to be deployed worldwide for quick and accurate POC analysis of physiological samples.

关键词： Micrometers Optical microscopy Red blood cells Microscopy Ultraviolet sources Prototypes Production Spatial resolution smart phones Testing

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