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4th IEEE International Flexible Electronics technology conference

作者： Zhao, Y. Li, Y. Zhou, J. He, G. Liu, Y. Zhao, J. Zhao, B. Lin, M. Wang, x. Qian, Z. Chen, S. Wan, T. Lian, Y. Shanghai Jiao Tong Univ Dept Micronano Elect Shanghai Peoples R China Univ Elect Sci & Technol China Sch Informat & Commun Engn Chengdu Peoples R China Chinese Acad Sci Inst Microelect Beijing Peoples R China Shenzhen Univ Coll Phys & Optoelect Engn Shenzhen Peoples R China Zhejiang Univ Sch Micronano Elect Hangzhou Peoples R China Shanghai Univ Sch Commun & Informat Engn Shanghai Peoples R China Qingdao Tianzhuo Technol Invest Holding Ltd Co Qingdao Peoples R China

ISBN: (数字)9781665469685

ISBN: (纸本)9781665469685

Flexible electronics has the great potential for healthcare applications, especially for prevention-oriented healthcare and personalized medicine. An essential block in the flexible biomedical sensor is the smart interface circuit that facilitates signal recording, decision making, and wireless transmission. This paper presents an ultra-low power system architecture for flexible sensors that is configurable for different types of biomedical signals and capable of extracting information from raw data while facilitates communications among multiple sensors using secure body channel communication (BCC).

关键词： Wireless communication Wireless sensor networks Precision medicine Systems architecture Medical services sensor systems Recording

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Development of an Implantable Capacitive Pressure sensor for biomedical Applications

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MICROMACHINES 2023年第5期14卷 975-975页

作者： Roh, Ji-Hyoung Shin, Kyu-Sik Song, Tae-Ha Kim, Jihong Lee, Dae-Sung Daegu Gyeongbuk Med Innovat Fdn Med Device Dev Ctr Daegu 41061 South Korea Korea Elect Technol Inst Smart Sensor Res Ctr Seongnam 13509 South Korea Yeungnam Univ Dept Elect Engn Gyongsan 38541 South Korea

In this study, a subminiature implantable capacitive pressure sensor is proposed for biomedical applications. The proposed pressure sensor comprises an array of elastic silicon nitride (SiN) diaphragms formed by the application of a polysilicon (p-Si) sacrificial layer. In addition, using the p-Si layer, a resistive temperature sensor is also integrated into one device without additional fabrication steps or extra cost, thus enabling the device to measure pressure and temperature simultaneously. The sensor with a size of 0.5 x 1.2 mm was fabricated using microelectromechanical systems (MEMS) technology and was packaged in needle-shaped metal housing that is both insertable and biocompatible. The packaged pressure sensor immersed in a physiological saline solution exhibited excellent performance without leakage. The sensor achieved a sensitivity of approximately 1.73 pF/bar and a hysteresis of about 1.7%, respectively. Furthermore, it was confirmed that the pressure sensor operated normally for 48 h without experiencing insulation breakdown or degradation of the capacitance. The integrated resistive temperature sensor also worked properly. The response of the temperature sensor varied linearly with temperature variation. It had an acceptable temperature coefficient of resistance (TCR) of approximately 0.25%/?.

关键词： capacitive pressure sensor microelectromechanical system biomedical applications

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Design of a Multi-sensor Wearable physiological Parameters Monitoring System Using Machine Learning Algorithm

Design of a Multi-Sensor Wearable Physiological Parameters M...

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smart Electronics and Communication Systems (ISENSE), International conference on

作者： Aarthy Prabakaran Elizabeth Rufus School of Electronics Engineering Vellore Institute of Technology Vellore India

ISBN: (数字)9798331528126

ISBN: (纸本)9798331528133

An aging population and changing lifestyles have led to an increase in health problems, necessitating a robust and scalable medical system. A healthy society can be fostered by implementing a comprehensive health tracking system that enables early disease detection and continuous remote healthcare monitoring. This can be achieved by employing a wearable healthcare monitoring system, that can assist the medical sector in reducing hospitalizations and facilitating early diagnosis. To address this need, a Wearable physiological Monitoring System (W-PMS) is proposed in this study. A prototype has been developed with the capability to record electrocardiography (ECG), photoplethysmography (PPG), and body temperature, and calculate crucial vital parameters such as heart rate, saturation of peripheral oxygen (SpO2) level, and blood pressure (BP). The W-PMS comprises three sensor modules integrated with a microcontroller to collect the physiological data. The acquired physiological data are processed by the microcontroller to calculate certain parameters such as heart rate and SpO2 level. The acquired data are pushed to the cloud to estimate the BP through an indigenous Android application. The data transmission between the microcontroller and the application occurs via Bluetooth communication. The final results are visualized on a mobile device, enabling users to track their health status. In conclusion, wearable devices incorporating biomedical sensors have the potential to remotely monitor an individual's health condition.

关键词： Temperature measurement Temperature sensors Heart rate Microcontrollers Medical services Electrocardiography biomedical monitoring Wearable devices Monitoring Medical diagnostic imaging

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Power efficient machine learning-based hardware architectures for biomedical applications

Power efficient machine learning-based hardware architecture...

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作者： Hassan, Omiya University of Missouri

学位级别：博士

The future of critical health diagnosis will involve intelligent and smart devices that are low-cost, wearable, and lightweight, requiring low-power, energy-efficient hardware platforms. Various machine learning models, such as deep learning architectures, have been employed to design intelligent healthcare systems. However, deploying these sophisticated and intelligent devices in real-time embedded systems with limited hardware resources and power budget is complex due to the requirement of high computational power in achieving a high accuracy rate. As a result, this creates a significant gap between the advancement of computing technology and the associated device technologies for healthcare applications. Power-efficient machine learning-based digital hardware design techniques have been introduced in this work for the realization of a compact design solution while maintaining optimal prediction accuracy. Two hardware design approaches, DeepSAC and SABiNN have been proposed and analyzed in this work. DeepSAC is a shift-accumulator-based technique, whereas SABiNN is a 2's complement-based binarized digital hardware technique. Neural network models, such as feedforward, convolutional neural nets, residual networks, and other popular machine learning and deep neural networks, are selected to benchmark the proposed model architecture. Various deep compression learning techniques, such as pruning, n-bit (n = 8,16) integer quantization, and binarization on hyper-parameters, are also employed. These models significantly reduced the power consumption rate by 5x, size by 13x, and improved the model latency. For efficient use of these models, especially in biomedical applications, a sleep apnea (SA) detection device for adults is developed to detect SA events in real-time. The input to the system consists of two physiological sensor data, such as ECG signal from the chest movement and SpO2 measurement from the pulse oximeter to predict the occurrence of SA episodes. In the

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An Integrated System of Blood Pressure and Electrocardiograph Recordings for smart Home Healthcare Network 15

An Integrated System of Blood Pressure and Electrocardiograp...

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15th IEEE International conference on ASIC, ASICON 2023

作者： Zou, Feng Huang, Hai Yuan, Ye Cheng, Yuhua Hangzhou Mixchips Microelectronics Co. Ltd. Hangzhou China Peking University Shanghai Research Institute of Microelectronics Shanghai China Peking University School of Software & Microelectronics Beijing China Peking University School of Integrated Circuits Beijing China

ISBN: (纸本)9798350312980

In this paper, we proposed an integrated system of electronic blood pressure (BP) estimation and electrocardiogram (ECG) recording (2 in 1), which could be connected to smart phones and other sensor devices through a smart home healthcare network (SHHN). This device can collect two physiological parameters (PPs): BP&ECG, and can establish a SHHN network through Bluetooth Low Energy (BLE) technology. The collected PPs of the user are firstly transmitted to the smartphone by BLE. Then preliminary calculation and analysis based on collected data are performed by smart devices. Both analysis results and raw data are transmitted to the cloud platform control center through the Internet for further processing. After the cloud platform collects all user data, data learning and mining are required to establish a data connection path between users and medical institutions. Finally, the system realizes BP detection and R wave peak detection on ECG, which makes the system meet the daily monitoring needs of universal home healthcare, especially cardiovascular diseases, and also provides a data foundation for cloud-based healthcare big data analyzing. © 2023 IEEE.

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Evaluation of Radiopacity and Biocompatibility of sensor Package for smart Catheter Application 24

Evaluation of Radiopacity and Biocompatibility of Sensor Pac...

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24th Electronics Packaging technology conference, EPTC 2022

作者： Lim, Ruiqi Damalerio, Ramona B. Vw, James Yap Cheng, Ming-Yuan Innovis 2 Fusionopolis Way #08-02 Innovis Tower Singapore138634 Singapore

ISBN: (纸本)9798350398854

smart catheters integrated with multiple sensors measure and provide surgeons with physiological data such as temperature, heart rate, pH value, blood flow or pressure. This feedback information enabled surgeons to better monitor and evaluate a patient's condition during the procedure. Thus, surgeons will be able to make accurate medical intervention and lead to a better health outcome for the patient. However, there is a growing trend to employ smaller catheters for certain procedures. Challenges faced by smart catheters include limited space for sensors integration which promotes the initiative to minimize sensor packaging. This led to secondary challenge of radiopaque visibility and biocompatibility for such sensor package. In this work, radiopaque visibility studies have been conducted and a minimum tungsten thickness of 100um is required for a sample size of 1.8mm (L) x 0.7mm (W). Additional radiopaque ink can be used as an alternative for die attach adhesive. The sensor package includes a polyimide-nitinol based flexible circuitry substrate with silicon-based sensor chip, radiopaque material (tungsten) and epoxy encapsulant has been verified to be biocompatible and suitable for catheter-based application. © 2022 IEEE.

关键词： Catheters

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Design of a smart physiological Monitoring System for the Elderly to Enable Predictive, Preventive, and Personalized Medicine

Design of a Smart Physiological Monitoring System for the El...

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Electronic Information Engineering and Computer Communication (EIECC), International conference on

作者： Ziqing Cai Weitao Wang Han Zhang School of Law and Humanities China University of Mining and Technology (Beijing) Beijing China School of Artificial Intelligence China University of Mining and Technology (Beijing) Beijing China

ISBN: (数字)9798331534622

ISBN: (纸本)9798331534639

The global increase in the elderly population presents significant challenges to healthcare systems, requiring the development of innovative solutions for health monitoring. This study presents the design of a smart physiological monitoring system aimed at delivering predictive, preventive, and personalized medicine for elderly individuals. The overall system integrates a microcontroller-based hardware platform with Wi-Fi communication to enable real-time monitoring of key physiological metrics such as heart rate and body temperature. The system’s hardware design utilizes the STC89C52 microcontroller, interfaced with a heart rate detection circuit that employs the ADC0832 analog-to-digital converter to connect a heart rate sensor to the microcontroller, as well as a DS18B20 temperature sensor. The circuit is optimized for low power consumption and incorporates a Wi-Fi module. The software design of the system is based on an embedded platform, utilizing a lightweight real-time operating system to manage sensor data acquisition, processing, and communication. Algorithms for data filtering, anomaly detection, and real-time analysis are implemented to ensure accurate monitoring of physiological conditions. This study eventually concludes by emphasizing the system’s potential to improve elderly healthcare and support for predictive, preventive, and personalized medicine.

关键词： Temperature sensors Microcontrollers Precision medicine Medical services Real-time systems Hardware Older adults biomedical monitoring Monitoring Wireless fidelity

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Experimental Study on Designing Advanced Driver Assistance System for Two-Wheelers Using Mobility and physiological sensors

Experimental Study on Designing Advanced Driver Assistance S...

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IEEE International conference on Vehicular Electronics and Safety (ICVES)

作者： Daiwat Amit Vyas Manish Chaturvedi Naveen Kumar Karan Kamath Piyusha Gupta Aryan Dwivedi Department of Computer Science and Engineering Institute of Infrastructure Technology Research and Management (IITRAM) Institute of Technology Nirma University Department of Computer Science and Engineering IITRAM Indian Institute of Information Technology (IIIT) Vadodara SRM Institute of Science and Technology

ISBN: (数字)9798350387278

ISBN: (纸本)9798350387285

Advanced Driver Assistance Systems (ADAS) enhance driver safety through various technologies. In high-end cars, ADAS typically uses computer vision-based solutions, such as eye-tracking, to monitor driver attention, mood, and drowsiness. However, these ADAS solutions are challenging to implement for two-wheeler (2W) drivers, who constitute about 80% of drivers population in India, mainly due to helmet usage and the unique dynamics of 2W vehicles. This paper investigates improving 2W driver safety through integrating mobility and physiological sensors for ADAS. Experimental studies evaluated a novel ADAS framework combining mobility sensor data (e.g., speed, acceleration, position) with physiological parameters (e.g., heart rate, etc.). This fusion of sensors data approach enables monitoring vehicle dynamics and driver conditions for providing adaptive safety interventions by identifying aggressive/non-aggressive and stress/non-stress patterns. To facilitate the collection of mobility and physiological sensors data a mobile application was developed using Flutter. The physiological parameters were captured from the smart-watch paired with the smart-phone and the mobility parameters were captured from the mobility sensors that were in-built in the smart-phone. The data was collected in Navi-Mumbai area of India. Preliminary experiments conducted using these integrated sensors data show promising results. To incorporate supervised approach for Driver Behaviour Analysis (DBA) requires a tedious task of manual tagging and each driver reacts differently to the different situations that arise while driving. So, an un-supervised learning approach has been incorporated and clustering techniques like k-Means, Gaussian Mixture Model (GMM), Hierarchical Clustering, and k-Means with Dynamic Time Wrapping (DTW) analysed the sensor data to identify patterns indicating potential hazards or driver impairment. The findings based on the preliminary experimental studies done indicate t

关键词： Tagging sensor systems biomedical monitoring Vehicle dynamics Advanced driver assistance systems Driver behavior Wrapping Intelligent sensors Monitoring Vehicles

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smart Device Fall Detection System for Real-Time Monitoring and Emergency Response for Specially Abled Individuals

Smart Device Fall Detection System for Real-Time Monitoring ...

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Software, Systems and Information technology (SSITCON), International conference on

作者： N Rajesh A C Ramachandra V Viswanatha V Chathurima V N Pallavi Swati Pujari Department of ECE Nitte Meenakshi Institute of Technology Bengaluru India

ISBN: (数字)9798350352931

ISBN: (纸本)9798350352948

Fall detection systems are essential for protecting specially-abled individuals and the elderly, who face an increased risk of injury due to falls. This paper presents the design and implementation of a smart Device Fall Detection System aimed at real-time monitoring and emergency response, supported by a dedicated Data Analysis Module for post-fall analysis. The system integrates multiple sensors, including an accelerometer, gyroscope, pressure sensor, cardiotachometer, and GPS module, all connected through an ESP32 microcontroller. It continuously monitors users’ movements and physiological data, which are transmitted to the Blynk cloud service for analysis. The algorithm processes the sensor data to detect fall events and trigger emergency alerts. The Data Analysis Module further analyzes fall data to extract patterns and trends, enhancing the understanding of fall incidents and informing preventive measures. The proposed system was evaluated through various fall and non-fall scenarios, achieving an impressive accuracy of $97.9 \%$ and a response time of just 1.45 seconds. Compared to existing solutions, this system demonstrates enhanced performance in fall detection accuracy, sensitivity, and emergency response efficiency. Ultimately, the smart Device Fall Detection System, combined with the Data Analysis Module, offers a practical and scalable solution to improve the safety and well-being of individuals at risk of falls, paving the way for further advancements in fall prevention technology.

关键词： Data analysis Accuracy Emergency services sensor systems Real-time systems Time factors Fall detection smart devices biomedical monitoring Monitoring

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smart Warfare: Designing Intelligent Vests for Enhanced Military Operations

Smart Warfare: Designing Intelligent Vests for Enhanced Mili...

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International conference on Inventive Computation Technologies (ICICT)

作者： Shital Raut Gaurav Jaisinghani Nisarg Doshi Ganesh Gaikwad Department of Electronics and Telecommunication Vishwakarma Institute of Technology Pune Maharashtra India

ISBN: (数字)9798350359299

ISBN: (纸本)9798350359305

In the rapidly evolving field of technology in the field of defense, wearable smart devices have emerged as a crucial area of research. From real-time health monitoring to augmented reality displays and enhanced communication platforms, the advancements in wearable technology are rapidly transforming the future of warfare and opening up exciting new avenues for military research. The study explores the creation and development of an innovative military vest, designed to augment the safety, efficiency, and effectiveness of military personnel during operations. The proposed design integrates a health monitoring system that combines sensor technologies, cloud computing, and web-based monitoring. The smart vest can track vital signs like heart rate and body temperature via two integrated sensors, IR temperature sensor and a heart-rate sensor. Beyond vital signs, the vest also safeguards the soldier against environmental threats through an integrated gas sensor and an accelerometer sensor for the purpose of tracking the movement of the soldier. The accelerometer sensor is integrated into the smart military vest by offering motion detection for fall detection. This strengthens military personnel's safety and effectiveness during operations. By encompassing these both technologies, physiological and environmental monitoring, the smart vest also unlocks a new frontier in silent, covert communication through a gesture-based communication system. This novel technology enables soldiers to exchange crucial information via hand gestures, revolutionizing battlefield communication in noise-filled or radio-restricted environments and helping soldiers to exchange information with each other in critical situations.

关键词： Temperature sensors Military communication Accelerometers Technological innovation Military computing Tracking Safety

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