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1st International conference on Health Informatics, HEALTHINF 2008

作者： Subramanian, Mahesh Conley, Edward C. Rana, Omer F. Hardisty, Alex Ali, Shaikh Luzio, Stephen Owens, David R. Wright, Steve Donovan, Tim Bedi, Bharat Conway-Jones, Dave Vyvyan, David Arnold, Gillian Creasey, Chris Horgan, Adrian Cox, Tristram Waite, Rhys The Welsh E-science Centre Cardiff University School of Computer Science 5 The Parade Roath Cardiff CF24 3AA United Kingdom Diabetes Research Unit Cardiff University Llandough Hospital Penlan Road Penarth Cardiff CF64 2XX United Kingdom IBM United Kingdom Ltd. Hursley House Hursley Park Winchester SO21 2JN United Kingdom Smart Holograms 291 Cambridge Science Park Milton Road Milton Cambridge CB4 OWF United Kingdom Zarlink Semiconductor Ltd. Phase 2 Mitel Business Park Caldicot Monmouthshire CF26 5YW United Kingdom

ISBN: (纸本)9789898111166

Novel sensor-based continuous biomedical monitoring technologies have a major role in chronic disease management for early detection and prevention of known adverse trends. In the future, a diversity of physiological, biochemical and mechanical sensing principles will be available through sensor device 'ecosystems'. In anticipation of these sensor-based ecosystems, we have developed Healthcare@Home (HH) - a research-phase generic intervention-outcome monitoring framework. HH incorporates a closed- loop intervention effect analysis engine to evaluate the relevance of measured (sensor) input variables to system-defined outcomes. HH offers real-world sensor type validation by evaluating the degree to which sensor-derived variables are relevant to the predicted outcome. This 'index of relevance' is essential where clinical decision support applications depend on sensor inputs. HH can help determine system-integrated cost-utility ratios of bespoke sensor families within defined applications - taking into account critical factors like device robustness / reliability / reproducibility, mobility / interoperability, authentication / security and scalability / usability. Through examples of hardware / software technologies incorporated inthe HH end-to-end monitoring system, this paper discusses aspects of novel sensor technology integration for outcome-based risk analysis in diabetes.

关键词： Decision support systems

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Wearable respiratory strain monitoring system based on textile-based capacitive strain sensor 3

Wearable respiratory strain monitoring system based on texti...

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2020 3rd International conference on Advanced Algorithms and Control Engineering, ICAACE 2020

作者： Jun, Zhong Chun-Na, L.I. Wen-Liang, Z.H.U. Hong, Zhou Yong-Feng, L.I.U. Xue-Feng, H.A.N. Suzhou Institute of Biomedical Engineering and Technology Chinese Academy of Sciences Suzhou215163 China 964 Hospital of the Joint Service Support Force of the Chinese People's Liberation Army Changchun130062 China Changchun Guoke Medical Technology Development Co. Ltd Changchun130000 China

Respiratory state analysis based on respiratory strain monitoring plays an increasingly important role in the assessment of the continuous dynamic physiological state of the human body. The proposed respiratory strain monitoring system uses the STM32F411 single-chip microcomputer as the main control chip, combined with the FDC2214 capacitor-to-digital converter, collects the capacitance value of the flexible cloth-based capacitive strain sensor through the IIC method, and sends the collected result to the upper computer for processing and analysis through Bluetooth. The device collects the respiratory strain signal of the chest in three motion states: Stationary, walking, and running. Through data acquisition and algorithm processing, it can clearly display the waveform of respiratory strain, and the extraction accuracy of the respiratory rate is ±1rpm. The experimental results show that the system has good stability and accuracy, strong anti-interference ability, and can meet the requirements of continuous dynamic high-precision respiratory rate monitoring. © Published under licence by IOP Publishing Ltd.

关键词： Data acquisition

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Research of Personalized Medical Testing technology for Healthy smart Home

Research of Personalized Medical Testing Technology for Heal...

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The 4th International conference on Bioinformatics and biomedical Engineering(第四届IEEE生物信息与生物医学工程国际会议 iCBBE 2010)

作者： Lijuan Lai Yun Peng Jing Zhou xiaoming Wu Department of Biomedical Engineering South China University of Technology Guangzhou China

This paper proposes design ideas for personalized medical testing technology of healthy smart home. The system architecture and design of physiological parameter detection sensors with wireless, low-costing and low power consumption are expounded. And the study of ECG monitoring in this system is presented to solve the key problem of ambulatory physiological parameter monitoring. Moreover, a design of communication network for healthy smart home is put forward as well, and some research and test on local communication network which is consisted of ZigBee nodes are discussed, the occupants’ physiological parameters that have converged can be transmitted over long distance via TCP/IP network. So the smart home and the community health service center will be built up a medical monitoring system.

关键词： Medical tests smart homes biomedical monitoring Condition monitoring Communication networks Intelligent sensors sensor systems Wireless sensor networks Energy consumption Electrocardiography

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Improved Anonymous Hybrid Authentication Scheme for Body Area Network Utilizing Channel Characteristics

Improved Anonymous Hybrid Authentication Scheme for Body Are...

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2021 International conference on Networking and Network Applications, NaNA 2021

作者： Umar, Mubarak Liao, Xuening Chen, Jiawang Shaanxi Normal University School of Computer Science Xi'an710062 China Department of Information Technology Bayero University Kano700241 Nigeria

ISBN: (纸本)9781665441582

Although wireless body network (WBAN) plays a vital role in revolutionizing healthcare delivery, it has also brought security concerns due to the sensitive nature of the patients' biomedical data being measured by the sensors in the network. Thus, authentication is essential for the safety of the patients in WBAN. Recently, Koya and Deepthi proposed an anonymous hybrid authentication scheme using a physiological signal to fix the security limitations of the existing anonymous authentication approaches in WBAN. However, their scheme lacks forward secrecy and requires that additional sensing hardware be attached to each sensor in WBAN, which is not only cost-prohibitive, but can lead to compatibility issues with legacy systems. To overcome these limitations, we propose an improved anonymous hybrid authentication scheme using physical layer (PHY) channel characteristics. The key idea in the proposed scheme is to replace the physiological signal used in the Koya and Deepthi scheme with a received signal strength (RSS) information already available in the wearable devices in WBAN as an identity identifier. We conduct security analysis to show the security strength of our approach and performance analysis to prove its computational efficiency. Moreover, we conduct experiments on human volunteers in indoor and outdoor locations to show the robustness of the proposed approach. The results demonstrate that our scheme can provide anonymous authentication and identify 90% of attack attempts in WBAN with less computation cost and without any additional sensing hardware. © 2021 IEEE.

关键词： Authentication

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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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EMG-Based Gestures Classification Using a Mixed-Signal Neuromorphic Processing System

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IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS 2020年第4期10卷 578-587页

作者： Ma, Yongqiang Chen, Badong Ren, Pengju Zheng, Nanning Indiveri, Giacomo Donati, Elisa Xi An Jiao Tong Univ Inst Artificial Intelligence & Robot Xian 710049 Peoples R China Univ Zurich Inst Neuroinformat CH-8006 Zurich Switzerland Swiss Fed Inst Technol CH-8092 Zurich Switzerland

The rapid increase of wearable sensor devices poses new challenges for implementing continuous real-time processing of physiological data. Neuromorphic sensory-processing devices can enable both the measurement of bio-signals and their processing locally in compact embedded wearable systems. In particular, mixed-signal spiking neural networks implemented on neuromorphic processors can be integrated directly with the sensors to extract temporal data-streams in real-time with very low power consumption. In this work, we present a neuromorphic approach for classifying spatio-temporal data from electromyography (EMG) signals, which paves the way toward the realization of compact wearable solutions for neuroprosthetic control. Here we extend previously proposed delta-encoding methods to transform bio-signals into spike trains and use a spiking Recurrent Neural Network (SRNN) architecture to extract features from them. The SRNN was first simulated in software to find the optimal set of hyperparameters, and then validated on the neuromorphic hardware, with a difference in the performance of less than 2%. We describe how biologically plausible mechanisms such as Spike-Timing Dependent Plasticity (STDP) and soft Winner-Take-All (WTA) networks can be exploited to classify the EMG signals and show how their combined use in EMG data classification achieves competitive results with different datasets. Specifically, the classification performance for the Roshambo EMG dataset, which has three different classes, is above 85%, and for the basic finger movements dataset from the Ninapro database, which has eight different classes, reaches 55% accuracy.

关键词： Neuromorphic engineering biomedical signal processing Recurrent neural networks Wearable sensors Neuromorphic engineering biomedical signal processing spike encoding spiking recurrent neural network spike-based learning Winner-Take-All

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Wearable Ear sensor for physiological States Monitoring

Wearable Ear Sensor for Physiological States Monitoring

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IEEE International conference on smart Internet of Things (smartIoT)

作者： Yimeng Zhang Qinghao Xu Wenbo Ding xi Tian Tsinghua-Berkeley Shenzhen Institute Tsinghua University Shenzhen China

ISBN: (数字)9798350366440

ISBN: (纸本)9798350366457

Wearable devices have rapidly evolved as essential tools for continuous health monitoring. However challenges persist in achieving high-accuracy physiological data acquisition due to issues such as suboptimal sensor placement and environmental interference. To overcome these limitations, we introduce a wearable ear sensor designed to offer comprehensive and reliable physiological monitoring. The sensor integrates different sensing modalities, including electroencephalography (EEG) and electromyography (EMG), within a compact, user-friendly form optimized for long-term wear. Utilizing biocompatible polydimethylsiloxane (PDMS) for in-ear electrodes and a lightweight reference electrode, the device ensures stable contact and signal fidelity. The designed signal acquisition system is able to realize low-noise amplification and adaptive signal processing, enabling accurate detection of low-amplitude bioelectrical signals. Experimental validation demonstrates the sensor's capability to capture and analyze physiological signals associated with various activities, such as eye movements and respiratory rhythms. The findings highlight the potential of ear-worn sensors in advancing wearable health monitoring technologies, with applications in both clinical and consumer health contexts.

关键词： Electrodes sensor placement Ear Reliability engineering Electromyography Electroencephalography biomedical monitoring Wearable devices Monitoring Wearable sensors

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A Framework of Blockchain-Based Security for WBANs

A Framework of Blockchain-Based Security for WBANs

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smart BlockChain (smartBlock), International conference on

作者： Han Deng xiangwei Meng Jun Guo Erhui xi Hui Zhao Big Data Development and Research Center Guangzhou College of Technology and Business Guangzhou China School of Computer science and Engineering Hunan University of Science and Technology Xiangtan China School of Software Engineering Quanzhou University of Information Engineering Quanzhou China Guangzhou College of Technology and Business Guangzhou China Educational Information Technology Laboratory Henan University Kaifeng China

Purposed to collect and store human physiological data, WBANs as a telemedicine system play a significant role in sensor networks. The complex network environment presents a formidable challenge to the stability of the system and the security of the database. The traditional centralized architecture is to store the registration data of the sensor node and the patient's physiological data in the hub node. When the hub node is subjected to Denial of Service attacks (DoS) and Distributed Denial of Service attacks (DDoS), there will be a single point of failure, so that the sensor node cannot establish a communication connection with the hub node. In this paper, a cloud server layer architecture based on blockchain technology is proposed for WBNAs to ensure system stability and patient data security. Meanwhile, Ciphertext-Policy Attribute-Based Encryption (CP-ABE) scheme is used to ensure patient physiological data safety.

关键词： Wireless communication Cloud computing Architecture Distributed databases Blockchain Medical services Permission

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A information system based on wireless networks for individual care management

A information system based on wireless networks for individu...

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International conference on Wavelet Active Media technology and Information Processing (ICWAMTIP)

作者： Ke-xin Liao Si-Yu Zhan Guo-Ming Lu Jian-Ming Liao Schocl of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China

An information system for the individual care management was proposed in this paper, which is an embedded physiological data acquisition system based on ATMEL9260 utilizing the combination of wearable physiological detecting technology, sensor technology, electronic technology and network technology. It realized continues and long-term detection of physiological data, contributing to real-time monitoring of patients and remote consultation.

关键词： biomedical monitoring Monitoring Servers Bluetooth smart phones Temperature sensors Temperature measurement

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The human-environment interface design with a vision assistance module or a smart wheelchair

The human-environment interface design with a vision assista...

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International conference on Advanced Robotics and Intelligent Systems (ARIS)

作者： Han-Yen Yu Jiann-Jone Chen Chung-Hsien Kuo National Taiwan University of Science and Technology Taipei Taiwan

Automatic and intelligent health care service becomes important with the growth of aged population. To achieve intelligent mobility for a smart wheelchair, we proposed to construct a friend user-environment interface that users can interact with the living environment like a normal healthy person. An integrated interactive platform, including touch control panel, together with several cameras, and wireless sensors, is embedded on a wheelchair to achieve human interaction. Interaction functions, such as appliance control, semi-automatic vision assistant function, and physiological information monitoring function etc. have been developed to achieve the target. The goal of light mobility can be reached and the overall smart wheelchair system comprises: a mobile vehicle, information sensor modules, analysis control modules and an image capture unit which is set towards the headrest direction of the mobile vehicle to capture human facial image data. The physiological sensor module is used for sensing user physiological data. The analysis control module seamlessly transmits monitoring signals to a caregiver side in response to the image data or physiological data. These user-environment interaction functions are developed under the design target of human technology that the wheelchair user can interact with the environment like a normal person.

关键词： sensors biomedical monitoring Face Cameras Monitoring Image color analysis Visualization

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