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

共 310 条记录，以下是61-70 订阅

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Enhanced smart-Shoe System for Gait Analysis with Real-Time Monitoring and Optimized Sampling

Enhanced Smart-Shoe System for Gait Analysis with Real-Time ...

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IEEE India conference (INDICON)

作者： Madhavan Bharanidivya Samiappan Dhanalakshmi Department of Electronics and Communication Engineering College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Chennai India

ISBN: (数字)9798350391282

ISBN: (纸本)9798350391299

Gait analysis plays a vital role in medical diagnostics, with applications spanning treatment, rehabilitation, therapy, and physical training. However, conventional gait analysis typically requires a specialized laboratory setting, limiting accessibility and failing to capture natural gait patterns. In this study, we introduce an innovative approach to enhance the accuracy and efficiency of gait monitoring systems, particularly for knee osteoarthritis (KOA) detection. Our innovation, the smart Insole, is a wearable device designed to overcome the limitations of traditional inertial measurement unit (IMU) methods. It offers superior feature extraction, real-time visualization, and advanced age-group classification. The device, which resembles an insole, is engineered to monitor pressure and inertial data from both feet, providing a discreet, lightweight, and user-friendly option for continuous gait analysis in everyday environments. we have developed a smartphone-based graphical user interface that displays real-time sensor data via a Wi-Fi module. The device's performance has been rigorously validated through a series of experiments and user trials, where it was benchmarked against traditional gait analysis techniques. Our evaluation also focused on the smart Insole's comfort and usability for regular wear, particularly for KOA detection. Using sensor data and a deep learning algorithm, our method achieved an accuracy of 94.74% in disease prediction.

关键词： Knee Accuracy Inertial sensors Data visualization Real-time systems Osteoarthritis biomedical monitoring Gait recognition Monitoring Diseases

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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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Design and Development of an Autonomous smart Stick Framework for Assisting Visually Impaired People 9th

Design and Development of an Autonomous Smart Stick Framewor...

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9th EAI International conference on Advancement of Science and technology, ICAST 2021

作者： Mengistu, Tesfahunegn Minwuyelet Habtie, Ayalew Belay Mengistu, Fikreselam Gared Bahir Dar University Bahir Dar Ethiopia Addis Ababa University Addis Ababa Ethiopia

ISBN: (纸本)9783030937089

Visually Impaired People (VIP) face numerous obstacles and troubles like physiological, psychological, social, and economic outcomes in their daily life. This work brings an intelligent and comprehensive stick framework aimed to assist VIP and navigate where to go. To increase sensing mechanisms wireless network is used to communicate between system components, enhance battery life. Global Positioning System (GPS) with General Packet Radio Service (GPRS)/Global System for Mobile communication (GSM) plays a vital role to get the location of visually impaired people with a short message service to rescuer them and adding buzzer timer to activate a buzzer in a specific duration with control buttons. It has a high range of obstacle detection, meticulous information conveyed, endowed sensor alert notification, sustainable power supply, short and multimedia messaging service (MMS), face and voice recognition, wireless system component connection, and its foldability gave the smart stick easy to keep and comfort for the VIP when they hold in addition to its robustness. © 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Global positioning system

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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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Analysis of Contrast and Correlation between Deep Learning Algorithms for Diagnosis of COVID 19 from Lung Ultrasonography 1

Analysis of Contrast and Correlation between Deep Learning A...

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1st International conference on Technologies for smart Green Connected Society 2021, ICTSGS 2021

作者： Goswami, Radha Debal Tiwari, Rajat Sabhapandit, Eshan Sivakumar, R. Soangra, Rahul Department of Sensor and Biomedical Technology School of Electronics Engineering Vellore Institute of Technology Tamil Nadu Vellore632014 India Department of Physical Therapy Chapman University OrangeCA92866 United States

ISBN: (纸本)9781607685395

Although identification of COVID-19 in patients from chest Computed Tomography (CT) scan has been the most prevalent approach, it exposes the patient to x-ray radiations and is not a suitable approach for frequent monitoring. Computer analysis of ultrasound pulmonary images is a relatively modern approach that shows promising ways to diagnose pulmonary states, which is a profitable and safer alternative to CT scan. Deep learning techniques for computerized study of Lung Ultrasound (LUS) images offer promising opportunities for identifying and diagnosing COVID-19. This paper aims to bring up a Convolution Neural Networking (CNN) model, which accurately predicts the condition of COVID-19 via the output produced lung ultrasound. Three models were developed using various parameters and were tested on the same dataset in order to compare each on standard statistical procedures. The best model achieved an accuracy of 94.67%, sensitivity 55% and specificity of 60% on the test data. © The Electrochemical Society

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Dehydration measurement using sweat sensor patch and pulse sensor

Dehydration measurement using sweat sensor patch and pulse s...

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International conference on Novel Approaches and Developments in biomedical Engineering 2021, ICNADBE 2021

作者： Manimegala, P. Anitha Mary, x. Biji, Neha Selshia Shiny, V. Department of Biomedical Engineering Karunya Institute of Technology and Science India

technology has increased visibly large. People find ways to easily detect their conditions. Heartbeat and dehydration level is one of the most common among people especially athletes. Athletes are drifted towards wearable technologies to track their training and recovery. Usually a dehydrated person sweats more. The sweat contains various physiological substance and health data. Based on studies sweat consists of salts and ions like [Na+], [K+], [Cl] lactate, glucose and ammonia. We are developing a wearable sweat analyser that can detect the raise in concentration of sodium and potassium. The sweat patch consist of a counter electrode created by screen printing Silver Chloride (AgCl) nanoparticles on Polydimithylsiloxane (PDMS) material and reference electrode (RE) created on the patch material by adding a platinum nanoparticle. This sweat sensor patch is connected to a microcontroller along with a temperature sensor and a Bluetooth module. The data which is collected by the sweat patch and the temperature sensor is sent via Bluetooth to mobile application were the data is displayed. © Published under licence by IOP Publishing Ltd.

关键词： Chlorine compounds

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Microgels-based In Vivo Biosensor for Continuous Blood Glucose Monitoring

Microgels-based In Vivo Biosensor for Continuous Blood Gluco...

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

作者： Zheng Gong xiang Chen Muhammad Ali Shanaz x. Chen Yifan Chen Yangtze Delta Region Institute (Quzhou) University of Electronic Science and Technology of China Quzhou China Yangtze Delta Region Institute (Huzhou) University of Electronic Science and Technology of China Huzhou China School of Engineering University of Waikato Hamilton New Zealand St Paul’s Collegiate School Hamilton New Zealand School of Life Science and Technology University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Microgel-based in vivo biosensor is an innovative technological concept that focuses on creating nano- and/or micro-scale sensors for health monitoring. Microgel-based sensor (MBS) enables highly sensitive detection of a phenomenon-of-interest through electromagnetic characteristics. This paper presents a novel MBS for implantable health monitoring, and the research contributions can be summarized into two main aspects. Firstly, a novel synthesis method for microgel nanoparticles designed for blood glucose detection is proposed, and a new MBS sensitive to the in vivo microenvironment conditions is successfully synthesized. Comprehensive material characterization is conducted, including analyzing the material’s performance in different blood glucose environments and its temporal variations. Secondly, for this material, its dielectric constant is detected to respond to physiological signals in the human body. MBS is employed as in vivo sensors, converting biological signals within the body into morphological changes of microgel particles (i.e., switching between expansion and contraction forms). Through dielectric constant probes, we detect the dielectric properties of MBS for sensing applications, providing crucial insights for potential biomedical uses of microgels. To discuss the response of the proposed MBS to changes in blood glucose, we consider scenarios of high and low blood sugar. At 2 GHz, it is observed that the dielectric constant is 60.27 during low blood sugar and 20.13 during high blood sugar. These results indicate a high sensitivity of MBS to changes in blood glucose levels.

关键词： In vivo Dielectric constant Sensitivity sensor phenomena and characterization Glucose Biosensors biomedical monitoring Probes Blood Monitoring

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MediBot: IoT-Driven Healthcare for Remote Communities

MediBot: IoT-Driven Healthcare for Remote Communities

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Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA), International conference on

作者： Ramprabu J Nandhini D Electrical and Electronics Engineering Kumaraguru College of Technology Coimbatore India

ISBN: (数字)9798331525439

ISBN: (纸本)9798331525446

It is a new IoT-included healthcare application for remote supervision of patients’ health overseeing signs and notifying in case of detecting possible health issues with the help of advanced sensor technology. Plan C: MediBot to use sensors to take measurements of remote patients' body temperature, pulse, SpO2, movements, and environment; MediBot acquires real-time health data, with data displayed at the local level as well as in the cloud through an ESP32 microcontroller. This allows users to remotely choose, recommend their vitals, and schedule appointments with healthcare providers using MediBot based on specialists, the latter can monitor in real-time patient-shared vitals and data and may prescribe drugs online. Using live data classification, MediBot accurately identifies potential health deteriorations such as fever, hypoxia, stress, sleep apnea, and dehydration and opportunities for medical interference. The subset connects the patient and doctor by closing the loop and continued screening so that the availability and effectiveness of services are improved. MediBot is a smart healthcare system applied to IoT with the help of sensors and machine learning to predict the health state of patients. Real-time physiological indices such as body temperature, pulse rate, blood oxygen saturation, movement, and environmental conditions are captured through sensors mounted on MediBot and presented on a local interface as well as the ESP32 microcontroller uploading data to the cloud. Using al; machine learning algorithms, MediBot in real-time and historical data to assess health risks such as fever, hypoxia, stress, sleep apnea, and dehydration, allowing for timely alerts for the patient’s immediate medical attention. Thus it creates a channel of constant supervision, and preliminary and effective interaction as well as improves the organization and effectiveness of managing the patients’ and doctors’ encounters.

关键词： Temperature sensors Temperature measurement Temperature distribution Microcontrollers Medical services Real-time systems Sleep apnea biomedical monitoring Stress Monitoring

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Enhanced Driver Safety: IoT Based Anti-Sleep Alarm and Automatic Braking System Using Eye Blink sensor

Enhanced Driver Safety: IoT Based Anti-Sleep Alarm and Autom...

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IEEE India conference (INDICON)

作者： Abhishek Kumar Apoorva Bapuram M. Akila Devi Yakub Banoth Santosh K. Dwivedi Amarjit Kumar National Institute of Technology Warangal India GNITC Hyderabad India

ISBN: (数字)9798350391282

ISBN: (纸本)9798350391299

Globally, driver drowsiness plays a major role in traffic accidents. In order to tackle this problem, we introduce the development and deployment of an Anti-Sleep Alarm System (ASAS) with the goal of averting sleep-related driving accidents. In order to identify indicators of weariness and send out appropriate notifications, this study presents a novel method that blends sophisticated signal processing techniques with real-time physiological signal monitoring of drivers. This system is designed to be comfortable and convenient for prolonged usage, utilising a wearable gadget that is integrated into a driver's headset. Worldwide, one of the main causes of road accidents is fatigued drivers. To address this issue, we propose the creation and implementation of an Anti-Sleep Alarm System (ASAS) with the intention of preventing driving accidents caused by sleepiness. This work proposes a novel approach that combines advanced signal processing techniques with real-time physiological signal monitoring of drivers to detect signs of exhaustion and give out relevant messages. Fatigued drivers are a major contributing factor in traffic accidents worldwide. In order to reduce sleepiness-related driving accidents, we suggest developing and implementing an Anti-Sleep Alarm System (ASAS) as a solution to this problem. In order to identify indicators of fatigue and deliver pertinent instructions, this work suggests a novel method that blends cutting-edge signal processing techniques with real-time physiological signal monitoring of drivers.

关键词： Sleep Alarm systems Signal processing Fatigue Real-time systems Safety biomedical monitoring Monitoring Vehicles Accidents

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