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RFID Positioning and physiological signals for Remote Medical Care

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Computer Systems Science & Engineering 2022年第4期41卷 289-304页

作者： Wen-Tsai Sung Sung-Jung Hsiao Department of Electrical Engineering National Chin-Yi University of TechnologyTaichung411030Taiwan Department of Information Technology Takming University of Science and TechnologyTaipei City11451Taiwan

The safety of patients and the quality of medical care provided to them are vital for their *** study establishes a set of RFID(Radio Fre-quency Identiﬁcation)-based systems of patient care based on physiological sig-nals in the pursuit of a remote medical care *** RFID-based positioning system allows medical staff to continuously observe the patient's health and *** staff can thus respond to medical emergencies in time and appropriately care for the *** the COVID-19 pandemic broke out,the proposed system was used to provide timely information on the location and body temperature of patients who had been screened for the *** results of experiments and comparative analyses show that the proposed system is superior to competing systems in *** use of remote monitoring technology makes user interface easier to provide high-quality medical services to remote areas with sparse populations,and enables better care of the elderly and patients with mobility *** can be found from the experiments of this research that the accuracy of the position sensor and the ability of package delivery are the best among the other related *** presentation of the graphical interface is also the most cordial among human-computer interaction and the operation is simple and clear.

关键词： Remote medical care active RFID positioning physiological signal

Preparation and application of graphene-based wearable sensors

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Nano Research 2022年第11期15卷 9850-9865页

作者： Shan Xia Ming Wang Guanghui Gao Polymeric and Soft Materials Laboratory School of Chemical Engineering and Advanced Institute of Materials ScienceChangchun University of TechnologyChangchun 130012China Beijing Graphene Institute(BGI) Beijing 100871China

With the development of digital healthcare technology,the demand for non-invasive monitoring of human health is rapidly *** recent years,the research and application of timely,economical,and easy-to-operate wearable sensing devices have attracted much *** recent studies,graphene has been widely used to improve the sensing performance of wearable sensors due to its advantages in mechanical,electrical,and thermal *** review mainly focuses on summarizing graphene and its derivative-based wearable sensors and their latest developments in personal health *** will first introduce the novel structure and sensing mechanism of different types of graphene ***,we summarize the latest applications of the graphene wearable sensors in human health monitoring,including human activity,heart rate,pulse,electrophysiological signal,and electronic ***,the future challenges and prospects of graphene wearable devices will be discussed.

关键词： graphene sensor health monitoring physiological signal electronic skin

Highly sensitive and stretchable piezoelectric strain sensor enabled wearable devices for real-time monitoring of respiratory and heartbeat simultaneously

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Nanotechnology and Precision Engineering 2022年第1期5卷 12-23页

作者： Zhenjie Ji Menglun Zhang State Key Laboratory of Precision Measuring Technology and Instruments Tianjin UniversityTianjin 300072China

The World Health Organization has declared COVID-19 a *** demand for devices or systems to diagnose and track COVID-19 infections noninvasively not only in hospitals but also in home settings has led to increased interest in consumer-grade wearables.A common symptom of COVID-19 is dyspnea,which may manifest as an increase in respiratory and heart *** this paper,a novel piezoelectric strain sensor is presented for real-time monitoring of respiratory and heartbeat signals.A highly sensitive and stretchable piezoelectric strain sensor is fabricated using a piezoelectric film with a serpentine *** thickness of the patterned PVDF flexible piezoelectric strain sensor is only 168μm,and the voltage sensitivity reaches 0.97 mV/με.The effective modulus is 13.5 MPa,which allows the device to fit to the skin and detect the small strain exhibited by the human *** vibrations are captured by the piezoelectric sensor,which produces an electrical output voltage signal conformally mapped with respiratory–cardiac *** separate heart activity and respiratory signals are extracted from the mixed respiratory–cardiac signal by an empirical mode decomposition data processing *** detecting vital signals such as respiratory and heart rates,the proposed device can aid early diagnosis and monitoring of respiratory diseases such as COVID-19.

关键词： physiological signal Strain sensor High sensitivity Flexibility Early diagnosis COVID-19

Home Monitoring of Pets Based on AIoT

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Computer Systems Science & Engineering 2022年第10期43卷 59-75页

作者： Wen-Tsai Sung Sung-Jung Hsiao Department of Electrical Engineering National Chin-Yi University of TechnologyTaichung City411030Taiwan Department of Information Technology Takming University of Science and TechnologyTaipei City11451Taiwan

With technological and social development in recent decades,people have begun pursuing more comfortable lives that frequently feature household pets that are treated like members of the *** average,one out of every three households has a *** has also led to the creation and growth of many businesses in the pet industry.A few companies have developed a system that allows busy office workers to remotely care for pets at home based on the Internet of Things and an intelligent adjustment *** owners of two dogs,the authors of this study observed their pets’living habits and recorded environmental conditions that appear suitable for *** data were then used to develop an automatic control system to care for *** observational data on the pets’habits and environment were written in a program in Arduino by using the ESP8266 Wi-Fi *** module and booster module control is the switch and setting of various household *** to the loop setting of the program,the system does not need to manually switch or adjust the electrical settings of the ***,the pet's living environment is assessed by using various *** use of Arduino programs helps develop a system that can automatically adjust the environment to one that is most suitable for the pet's comfort.

关键词： Remote medical care active RFID positioning physiological signal

Wearable Alignment‑Free Microfber‑Based Sensor Chip for Precise Vital Signs Monitoring and Cardiovascular Assessment

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Advanced Fiber Materials 2022年第3期4卷 475-486页

作者： Liangye Li Yunfei Liu Changying Song Shunfeng Sheng Liuyang Yang Zhijun Yan Dora Juan Juan Hu Qizhen Sun School of Optical and Electronic Information and National Engineering Laboratory for Next Generation Internet Access System(NGIA)and Wuhan National Laboratory for Optoelectronics(WNLO) Huazhong University of Science and TechnologyWuhan 430074HubeiChina Institute for Infocomm Research Singapore 138632Singapore

Continuous pulse wave signals monitoring is the essential basis for clinical cardiovascular diagnosis and *** researches show the majority of current electronic pulse sensors usually face challenges in electrical safety concern,poor durability and demanding precision in position ***,a highly sensitive,inherently electrical safe,robust and alignment-free device is highly ***,we present a wearable alignment-free microfber-based sensor chip(AFMSC)for precise vital signs monitoring and cardiovascular health *** AFMSC comprises an optical micro/nano fber sensor(MNF)and a fexible soft liquid sac while the MNF sensor is used to perceive the physiological signals and the liquid sac is used to eliminate the *** real-time and accurate monitoring of the pulse signals was realized by tracking the optical power variation of transmitted light from ***,the cardiovascular vital signs extracted from radial artery pulse signals were used to evaluate cardiovascular health condition and the results were in accordance with human physiological ***,the pulse signals from diferent arterial area,the respiration signals from chest and the radial pulse signals before and after exercise were detected and *** non-invasive,continuous and accurate monitoring of cardiovascular health based on the reported wearable and alignment-free device is promising in both ftness monitoring and medical diagnostics for cardiovascular disease prevention and diagnosis.

关键词： Optical microfber sensor Wearable,alignment-free physiological signal Cardiovascular health

Measuring System Regularity Using Fuzzy Similarity-based Approximate Entropy

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Journal of Shanghai Jiaotong university(Science) 2007年第5期12卷 623-627页

作者：陈伟婷王志中王刚 Dept.of Biomedical Eng. Shanghai Jiaotong Univ.

Approximate entropy (ApEn), a measure quantifying regularity and complexity, is believed to be an effective analyzing method of diverse settings that include both deterministic chaotic and stochastic processes, particularly operative in the analysis of physiological signals that involve relatively small amount of data. However, the similarity definition of vectors based on Heaviside function, of which the boundary is discontinuous and hard, may cause some problems in the validity and accuracy of ApEn. To overcome these problems, a modified ApEn based on fuzzy similarity (mApEn) was proposed. The performance on the MIX stochastic model, as well as those on the Logistic map and the Hennon map with noise, shows that the fuzzy similarity-based ApEn gets more satisfying results than the standard ApEn when characterizing systems with different regularities.

关键词： regularity approximate entropy (ApEn) fuzzy similarity physiological signal

A Method of Multimodal Emotion Recognition in Video Learning Based on Knowledge Enhancement

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Computer Systems Science & Engineering 2023年第11期47卷 1709-1732页

作者： Hanmin Ye Yinghui Zhou Xiaomei Tao School of Information Science and Engineering Guilin University of TechnologyGuilin541004China Guangxi Key Laboratory of Embedded Technology and Intelligent System Guilin University of TechnologyGuilin541004China Guangxi Key Lab of Multi-Source Information Mining and Security Guangxi Normal UniversityGuilin541004China

With the popularity of online learning and due to the significant influence of emotion on the learning effect,more and more researches focus on emotion recognition in online *** of the current research uses the comments of the learning platform or the learner’s expression for emotion *** research data on other modalities are *** of the studies also ignore the impact of instructional videos on learners and the guidance of knowledge on *** of the need for other modal research data,we construct a synchronous multimodal data set for analyzing learners’emotional states in online learning *** data set recorded the eye movement data and photoplethysmography(PPG)signals of 68 subjects and the instructional video they *** the problem of ignoring the instructional videos on learners and ignoring the knowledge,a multimodal emotion recognition method in video learning based on knowledge enhancement is *** method uses the knowledge-based features extracted from instructional videos,such as brightness,hue,saturation,the videos’clickthrough rate,and emotion generation time,to guide the emotion recognition process of physiological *** method uses Convolutional Neural Networks(CNN)and Long Short-Term Memory(LSTM)networks to extract deeper emotional representation and spatiotemporal information from shallow *** model uses multi-head attention(MHA)mechanism to obtain critical information in the extracted deep ***,Temporal Convolutional Network(TCN)is used to learn the information in the deep features and knowledge-based ***-based features are used to supplement and enhance the deep features of physiological ***,the fully connected layer is used for emotion recognition,and the recognition accuracy reaches 97.51%.Compared with two recent researches,the accuracy improved by 8.57%and 2.11%,*** the four public data sets,our proposed method also achieves bett

关键词： Emotion recognition video learning physiological signal knowledge enhancement deep learning CNN LSTM TCN

Exploring the Application of Vibration Analysis Technology in the Medical Field

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Journal of Biosciences and Medicines 2023年第6期11卷 210-217页

作者： Hong Qin Mai Xin Yuhan Cai Changhua Chen Department of Gynecology People’s Hospital of Xiangxi Tujia and Miao Autonomous Prefecture (The First Affiliated Hospital of Jishou University) Xiangxi Tujia and Miao Autonomous Prefecture China School of Energy and Power Nanjing University of Aeronautics and Astronautics Nanjing China Sichuan Qiyue Logistics Technology Co. Ltd. Meishan China Nanjing University of Aeronautics and Astronautics Nanjing China

In the field of engine maintenance and assurance, the technology of unit condition detection through vibration analysis is relatively mature. More and more patents and technical products have been released, proving the practical value of the technology in mechanical vibration from the application level. In medical science, signals such as heart sounds and pulses are also vibration signals in nature, in order to expand the application of the technology and explore the value of the technology in medical applications. In order to extend the application of the technology and to explore the value of the technology in medical applications, the wavelet analysis technology was used to program the Labview2022 software to implement the corresponding analysis program for the analysis of the collected physiological signals. Finally, the wavelet transform-based analysis of the physiological signals was successfully implemented. It is demonstrated that the design concept can be achieved by applying this technique, which makes it valuable in the field of physiological signal detection and analysis.

关键词： Vibration physiological signal Analysis Wavelet Technique Detection

EEG Feature Selection for Emotion Recognition Based on Cross-subject Recursive Feature Elimination

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EEG Feature Selection for Emotion Recognition Based on Cross...