检索结果-内蒙古大学图书馆

2024 IEEE International conference on Consumer Electronics, ICCE 2024

作者： Zou, Jiadao Jackman, Christopher Zhang, Qingxue Purdue Univeristy School of Engineering and Technology Electrical and Computer Engineering IN United States Indiana University School of Medicine Clinical Neurology Riley Hospital IN United States Purdue Univeristy School of Engineering and Technology Electrical and Computer Engineering Biomedical Engineering IN United States

ISBN: (纸本)9798350324136

Wearable massive-sensor computers show great promise for comprehensive bio-dynamics capturing towards smart health big data. Nevertheless, mining the critical and complementary patterns from a large amount of data, especially with a high dimensionality, is challenging. In this study, we propose a novel deep learning framework, with both deep graph convolutional learning and multi-view representation, to boost the spatial dynamics complementarity mining. More specifically, we have proposed a multi-stage deep learning architecture, with a graph convolutional network for spatial pattern propagation and fusion, and a convolutional network for further pattern abstraction. Further, we have proposed a multi-view data representation approach with both temporal and spectral feature formation. Evaluated on the wearable massive-sensor data mining application, the proposed framework has greatly boosted the complementarity learning capability and yielded a significantly improved detection performance. This study is expected to greatly advance spatial dynamics complementarity learning with graph convolutional learning. © 2024 IEEE.

关键词： Big Data Wearable Massive-sensor Computers Deep Learning Graph Convolutional Network

来源：评论

学校读者我要写书评

暂无评论

Biomechanics of the Lower Extremity in Youth Football League: FIFA 11+ One Leg Squat Analysis 12

Biomechanics of the Lower Extremity in Youth Football League...

引用

Proceedings of the 12th International conference on Sport Sciences Research and technology Support, icSPORTS 2024

作者： Davidovica, Anna Davidovics, Sergejs Semjonova, Guna Katashev, Alexei Oks, Alexander Lancere, Linda Tomsone, Signe Zolovs, Maksims Department of Rehabilitation Riga Stradins University 16 Dzirciema Street RigaLV-1007 Latvia Institute of Mechanical and Biomedical Engineering Riga Technical University RigaLV-1048 Latvia Institute of Architecture and Design Riga Technical University RigaLV-1048 Latvia Department of Sociotechnical Systems Modelling Vidzeme University of Applied Sciences ValmieraLV-4201 Latvia Statistical Unit Faculty of Medicine Riga Stradins University 16 Dzirciema Street RigaLV-1007 Latvia

ISBN: (纸本)9789897587191

Background: Football carries substantial injury risks, especially for youth players. Providing biofeedback of lower limb motion during functional tasks is a crucial part of injury prevention programs such as FIFA 11+. While the FIFA 11+ warm-up program providing individualised feedback remains challenging, wireless sensor systems such as the DAid® Pressure Sock system, NOTCH® Inertial sensor System, and PLUx Wireless Biosignals (muscleBAN kit) System offer potential solutions. Aim: This study aims to explore the correlation of lower limb biomechanical variables during the FIFA 11+ Part 2 exercise "One Leg Squat"in youth football players using wireless sensor systems and video recordings. Methods: Using wireless sensor systems and video recordings, we analysed lower limb biomechanics during the "One Leg Squat"exercise in youth football players. Results: Strong positive correlations were identified between hip joint adduction and the changes in the centre of pressure of the plantar surface of the foot (COP1y), as well as between hip joint internal rotation and COP1y. COP2x correlated strongly with gluteus medius activity. Conversely, COP2y showed a negative correlation with gluteus maximus activity. Conclusions: The results support the potential of wireless sensor systems in monitoring the biomechanical changes of the lower extremity movements and lay the groundwork for future biofeedback methods based on the DAid® smart socks system technology for evaluating lower limb motion, especially the changes in the centre of pressure of the plantar surface of the foot, during functional tasks in Football Youth League players. Copyright © 2024 by SCITEPRESS - Science and technology Publications, Lda.

关键词： Biofeedback

来源：评论

学校读者我要写书评

暂无评论

PhysioChair: A Dual-Frequency Radar System for Noninvasive and Continuous Detection of physiological Signatures

引用

IEEE sensorS JOURNAL 2022年第8期22卷 8224-8233页

作者： Wen, Li Gao, Yue Gu, Changzhan Mao, Junfa Shanghai Jiao Tong Univ MoE Key Lab High Speed Elect Syst Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ MoE Key Lab Artificial Intelligence Shanghai 200240 Peoples R China

This paper presents PhysioChair which is a novel sensing technique integrated in smart chairs for noninvasive and continuous detection of multiple physiological signatures. A dual-frequency radar system is designed and integrated in the PhysioChair, including a 5.8 GHz single-antenna radar for chest movement detection and a 120 GHz miniaturized radar for pulse detection. The dual-frequency multi-radar sensing system is calibrated to ensure systematic synchronization. Besides the conventional vital signs such as respiration, heartbeat and pulse, this paper proposes techniques and approaches to make it possible for the PhysioChair to estimate additional physiological signatures including heart rate variability (HRV), pulse transit time (PTT), pulse wave velocity (PWV), and blood pressure (BP). Experiments have been launched in an office environment with Photoplethysmography (PPG) and digital sphygmomanometer as reference. The experimental results show a great performance of the proposed PhysioChair in detection of weak physiological signatures. Compared to the ground truth, the estimated physiological signatures such as HRV and BP have mean relative errors below 3%, and 6 out of 7 subjects have an over 90% probability of absolute errors less than 5mmHg. The results reveal the possibility for the PhysioChair to be employed outside the clinic, such as applications in the vast internet-of-things (IoT) and in-home health monitoring.

关键词： Radar sensors biomedical monitoring Radar detection sensor systems Demodulation Radar antennas Radar linear demodulation respiration heart rate pulse HRV PTT PWV blood pressure

来源：评论

学校读者我要写书评

暂无评论

smart Drowsiness Detection System with Microcontroller Integration 14th

Smart Drowsiness Detection System with Microcontroller Integ...

引用

14th EAI International conference on Broadband Communications, Networks, and Systems, BROADNETS 2024

作者： Motupalli, Satyarth Ravindra, J.V.R. Satish Kumar, G.A.E. Vidhyadhar, R. Phani Kanneboina, Ramavathar Yadav Reddy, Varun Kumar Tammineni, Siddarth Department of ECE Chaitanya Bharathi Institute of Technology Telangana Hyderabad India Department of ECE Vardhaman College of Engineering Telangana Hyderabad India

ISBN: (纸本)9783031811678

An embedded system is designed to address the issue of drowsy driving by using a microcontroller and a pulse sensor. This system combines multiple sensors, including the pulse sensor, with a microcontroller to monitor a driver’s vital signs and behaviour. The microcontroller acts as the central processing unit, collecting data from the sensors, analyzing it, and making informed decisions. Specifically, the pulse sensor measures heart rate and heart rate variability, which can provide insights into a driver’s physiological state, especially when drowsiness leads to changes in these parameters. The compact size and low power consumption of this embedded system make it suitable for integration into various vehicles, from personal cars to commercial fleets. In conclusion, this abstract emphasizes the potential of integrating such a system into vehicles to enhance road safety by detecting drowsy drivers and reducing accidents associated with drowsy driving. In essence, this technology embodies the spirit of looking out for one another. It transforms every journey into a secure experience where drivers and passengers can travel with confidence, knowing they are shielded by a caring, understanding companion. It’s not just about avoiding accidents;it’s about fostering a culture of safety, where we all contribute to making our roads a better place for everyone. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2025.

关键词： Microcontrollers

来源：评论

学校读者我要写书评

暂无评论

Electrospinning Polyvinyl Alcohol/Polyaniline Nanofiber-Based Humidity sensor

Electrospinning Polyvinyl Alcohol/Polyaniline Nanofiber-Base...

引用

sensors and Information technology (ICSI), International conference on

作者： Rong Du Han Song Yi Liu Boyi Wang Wuhan University of Technology Wuhan China Wuhan University of Technology Shaoxing Institute for Advanced Research Wuhan China

ISBN: (数字)9798331542887

ISBN: (纸本)9798331542894

With the rapid advancement of smart wearable devices, the monitoring of human physiological signals has emerged as a prominent research focus. In this study, a polyvinyl alcohol/polyaniline (PVA/PANI) resistive humidity sensor with superior humidity sensing performance was fabricated using electrospinning technology. Within the relative humidity ranges of 25% to 65% and 65% to 95%, the sensor exhibits sensitivities of-120.77MΩ/%RH and -4.44MΩ/%RH, respectively. Furthermore, the sensor exhibits a response/recovery time of approximately 45/14 seconds, hysteresis of 2.23%. The PVA/PANI humidity sensor has the ability of respiration monitoring, which provides a new method for the application of polymer humidity sensor in human physiological signal monitoring.

关键词： Sensitivity Humidity Polymers Time factors biomedical monitoring Wearable devices Monitoring Hysteresis Standards Testing

来源：评论

学校读者我要写书评

暂无评论

Wearables, sensors and the future of technology to detect and infer loneliness in older adults

引用

Gerontechnology 2023年第2期22卷 1-4页

作者： Rees, Jessica Matcham, Faith Probst, Freya Ourselin, Sebastien Shi, Yu Antonelli, Michela Tinker, Anthea Liu, Wei Department of Global Health and Social Medicine King’s College London London United Kingdom School of Psychology University of Sussex Falmer United Kingdom Department of Engineering King’s College London London United Kingdom School of Biomedical Engineering & Imaging Sciences King’s College London London United Kingdom School of Design University of Leeds Leeds United Kingdom

Loneliness is a growing concern affecting the health and quality of life of older adults living in the community. Addressing loneliness in ageing populations is an important policy priority. Central to this is the detection of type and severity of loneliness. Advancement in technology provides an opportunity for loneliness to be inferred through physiological and behavioural changes. In this article, we provide an overview of the current evidence on wearable and sensor technologies to detect loneliness in older adults including reviewing physiological measures of loneliness. Two recent reviews have highlighted how loneliness in older adults can be inferred using in-home sensors and smartphones. However, ethical and privacy issues remain an unaddressed issue in the development of technologies to measure loneliness in this population. Ongoing research is working to address this through the development a new multi-functional sensor which can be used in fabrics and textiles in the home to measure loneliness in people age 65 and over. We present an overview of the DEsign for healthy ageing: A smart system to decrease LONELINESS for older people (DELONELINESS) study. © (2023). All Rights Reserved.

关键词： ageing loneliness measurement older adults technology

来源：评论

学校读者我要写书评

暂无评论

Developing a 3D Laparoscopy Training Application to Assess the Efficacy in Virtual Reality Environments 9th

Developing a 3D Laparoscopy Training Application to Assess t...

引用

9th EAI International conference on smart Objects and Technologies for Social Goods, GOODTECHS 2023

作者： Yosunkaya, Ege Şahin, Sebahat Selin Surer, Elif Keleş, Hasan Onur Department of Modeling and Simulation Graduate School of Informatics Middle East Technical University Ankara06800 Turkey Department of Biomedical Engineering Ankara University Ankara06830 Turkey

ISBN: (纸本)9783031525230

This study aims to develop a multimodal understanding of transferring an established method of laparoscopy training to the virtual reality domain. The virtual reality version of the laparoscopic box trainer is developed and tested with 15 participants. Post-experiment questionnaires showed the version of the simulation with tutorial and haptic feedback is acceptable in terms of usability and received better feedback in the technology acceptance model questionnaire. Furthermore, the kinematic behavior of participants’ hands showed a significant distinction between above-average and below-average completion time groups similar to the physical and computer-based non-immersive simulation counterparts. The physiological response of the participants is investigated between rest state and during the task with an Electrocardiogram (ECG) and indicators of increased mental workload are observed with increased heart rate and decreased heart rate variability. The interest in assessing the physiological and kinematic features of trainees in a virtual reality (VR) environment is on the rise and the proposed study is very promising in terms of enhancing the development of improved training and assessment methodologies. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Virtual reality

来源：评论

学校读者我要写书评

暂无评论

A Novel Symmetric Key Compact to Reliable Connection between sensor Nodes Using Exploitable Features of ECG

A Novel Symmetric Key Compact to Reliable Connection between...

引用

2022 International conference on Innovative Computing, Intelligent Communication and smart Electrical Systems, ICSES 2022

作者： Riya, K.S. Sudhakar, J. Ravichandran, M. Tamilselvi, M. Sajiv, G. Vel Tech Multi Tech Dr Rangerajan Dr Sakunthala Engineering College Department of Computer Science and Engineering Chennai India Chennai Institute of Technology Kundrathur Department of Biomedical Engineering Chennai600069 India K. Ramakrishnan College of Engineering Department of Mechanical Engineering Trichy621 112 India T.S.Srinivasan Centre for Polytechnic College and Advanced Training Department of Mechatronics Engineering Vanagaram Chennai600 095 India SIMATS Saveetha School of Engineering Department of ECE Chennai602105 India

ISBN: (数字)9781665474139

ISBN: (纸本)9781665474139

Wireless sensor networks (WSNs) have evolved to serve a diverse multitude of uses, including field of health and social systems, as a result of advancements in the technology. In sensing devices, a wireless body area network (WBAN) is a particularly unique network technology that is meant to operate continuously to connect smart equipment and equipment implanted both in and out of person that are used for lengthy healthcare monitoring within even outside a medical environment. A WBAN is a network of sensor nodes that are implanted in and/or fastened on the individual body for the purpose of tracking the individual's physiological features. Although the growth of WBAN technology has the potential to considerably assist medical healthcare systems, the collection and transmission of private physiological data in such an open setting poses severe security and privacy issues. Throughout this research, we offer a unique key-agreement mechanism for securing communications between sensor nodes of wireless body area networks (WBANs). In order to communicate, the suggested technique relies on the measurement and verification of shared physiological properties at both the transmitter and receiver sensors. In contrast to current protocols, the suggested protocol allows communicating sensors to leverage their prior session pre-knowledge for encrypted communication during a certain length of time, as opposed to existing protocols. Thus, the time necessary for creating the shared key will be reduced. In addition, extracted characteristics will not be repeated in the medium, preventing listening attacks while keeping the unpredictability of the key. The experimental outcomes show the efficacy of the suggested key agreement existing protocols of both the image retrieval and the key establishment phases, with an efficiency of 99.50 percent and an error rate of 0.005 percent in both the image retrieval and based consensus phases. When compared to current key agreement methods, the sug

关键词： sensor nodes

来源：评论

学校读者我要写书评

暂无评论

Internet of Things and Machine Learning Enabled smart e-Textile with Exceptional Breathability for Point-of-Care Diagnostics

引用

ADVANCED MATERIALS TECHNOLOGIES 2024年第20期9卷

作者： Mondal, Bidya Saini, Dalip Mishra, Hari Krishna Mandal, Dipankar Inst Nano Sci & Technol Quantum Mat & Devices Unit Sect 81 Mohali 140306 India

In recent years, the convergence of smart electronic textile (e-textile) and digital technology has emerged as a transformative shift in healthcare, offering innovative solutions for point-of-care diagnostics. However, the development of textile electronics with exceptional functionality and comfort still remains challenging. Here, all-electrospun piezoelectric smart e-textile empowered is reported by Internet of Things (IoT) and machine learning for advanced point-of-care diagnostics. The resulting e-textile exhibits exceptional breathability (b approximate to 4.13 kg m-2 d-1), flexibility, water-resistive properties (water contact angle approximate to 137 degrees), and mechano-sensitivity of 1.5 V N-1 due to its mechanical-to-electrical energy conversion abilities. It can efficiently monitor different critical biomedical healthcare signals, such as, arterial pulse and respiration rate. Importantly, the e-textile sensor demonstrates remarkable attributes, generating an open circuit voltage of 10.5 V, a short circuit current of 7.7 mu A, and power density of 4.2 mu W cm-2. Moreover, the e-textile provides real-time, non-invasive monitoring of human physiological movements through IoT. It is worth highlighting that the machine learning showcases an impressive 96% of accuracy in detecting respiratory signals, representing a significant accomplishment. Thus, this e-textile has enormous potential in remote patient monitoring and early disease detection, aiming to reduce healthcare costs, enhance patient outcomes, and improve the overall quality of medical care. All-electrospun piezoelectric smart e-textile integrates IoT and machine learning for advanced point-of-care diagnostics. Exhibiting breathability, flexibility, and waterproofness, it monitors arterial pulse and respiration rate. The e-textile sensor generates significant electrical outputs, and machine learning achieves 96% accuracy in detecting respiratory signals, promising enhanced remote patient monitoring a

关键词： biomedical signals IoT machine learning piezoelectric sensor point-of-care diagnostics smart e-textile

来源：评论

学校读者我要写书评

暂无评论

Design of Wireless Based Telemonitoring System with biomedical sensor

Design of Wireless Based Telemonitoring System with Biomedic...

引用

IEEE International conference on Emerging & Sustainable Technologies for Power & ICT in a Developing Society (NIGERCON)

作者： A. O. Ogunsanya D. O. Daramola O. O. Ogunbiyi J. W. Sojobi Y. T. Oladijo S. T. Ajayi Department of Biomedical Engineering Bells University of Technology Ota Nigeria Department of Mechanical Engineering Bells University of Technology Ota Nigeria

ISBN: (数字)9798331542559

ISBN: (纸本)9798331542566

Patient surveillance is critical in-order to decrease and/or avoid the spread of the chronic conditions. Although effective, the traditional healthcare systems of patient monitoring are limited, making it difficult for ambulatory patient seek medical care and have their physiological parameters evaluated. Advent of wireless technology and advancements in on-body sensor design have enabled a shift in the traditional health-care system. Thereby, allowing smart healthcare systems to take its place. This paper aims to describe the design and development of wireless based telemonitoring system with biomedical sensors for vulnerable individuals. Non-invasive biomedical sensors, signal condition system, Internet of Things (IoT), radio frequency module (RF) was used to implement the design. The sensors were used to collect physiological parameters before transferring over the hybrid transmission medium. Thing-Speak and graphic user interface (GUI) were used to display the results. The system design was successfully deployed, with efficient transmission of patient data with an average accuracy of 99.06%. The hybrid wireless monitoring system can give continuous physiological data as well as more detailed information about an individual's overall health. Hybrid wireless physiological parameter monitoring system has the potential of enhancing the quality of life of disease management individuals and lower healthcare expenditures.

关键词： Wireless communication Wireless sensor networks Surveillance Medical services Internet of Things Biosensors Reliability biomedical monitoring System analysis and design Graphical user interfaces

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：