• Title/Summary/Keyword: Wearable Sensor

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Deterministic Multi-dimensional Task Scheduling Algorithms for Wearable Sensor Devices

  • Won, Jong-Jin;Kang, Cheol-Oh;Kim, Moon-Hyun;Cho, Moon-Haeng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.10
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    • pp.3423-3438
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    • 2014
  • In recent years, wearable sensor devices are reshaping the way people live, work, and play. A wearable sensor device is a computer that is subsumed into the personal space of the user, and is always on, and always accessible. Therefore, among the most salient aspects of a wearable sensor device should be a small form factor, long battery lifetime, and real-time characteristics. Thereby, sophisticated applications of a wearable sensor device use real-time operating systems to guarantee real-time deadlines. The deterministic multi-dimensional task scheduling algorithms are implemented on ARC (Actual Remote Control) with relatively limited hardware resources. ARC is a wearable wristwatch-type remote controller; it can also serve as a universal remote control, for various wearable sensor devices. In the proposed algorithms, there is no limit on the maximum number of task priorities, and the memory requirement can be dramatically reduced. Furthermore, regardless of the number of tasks, the complexity of the time and space of the proposed algorithms is O(1). A valuable contribution of this work is to guarantee real-time deadlines for wearable sensor devices.

Implementation of Wearable Sensor Glove using Pulse-wave Sensor, Conducting Fabric and Embedded System (맥파 측정 센서와 전도성 섬유, 임베디드 시스템 기반의 웨어러블 센서 글러브 구현)

  • Lee, Young-Bum;Lee, Byung-Woo;Lee, Myoung-Ho
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.3
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    • pp.205-209
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    • 2007
  • Today, there are research trends about the wearable sensor device that measures various bio-signals and provides healthcare services to user using e-Health technology. This study describes the wearable sensor glove using pulse-wave sensor, conducting fabric and embedded system. This wearable sensor glove is based on the pulse-wave measurement system which is able to measure the pulse wave signal in much use of oriental medicine on the basis of a research trend of e-Health system.

Wearable Human Health-monitoring Band using Inkjet-printed Flexible Temperature Sensor

  • Han, Dong Cheul;Shin, Han Jae;Yeom, Se Hyeok;Lee, Wanghoon
    • Journal of Sensor Science and Technology
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    • v.26 no.5
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    • pp.301-305
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    • 2017
  • This paper presents a wearable human health-monitoring band. The band consists of a body temperature detector (BTD) and a hear rate detector (HRD). The BTD and HRD are realized using an inkjet-printed flexible temperature sensor and a commercial heart rate sensor module, respectively. The sensitivity of the fabricated BTD was found to be $-31/^{\circ}C$ with a linearity of 99.82%. The HRD using the commercial heart rate sensor module has a good performance with a standard deviation of 0.85 between the data of a commercial smart watch and the fabricated HRD.

Human Motion Tracking With Wireless Wearable Sensor Network: Experience and Lessons

  • Chen, Jianxin;Zhou, Liang;Zhang, Yun;Ferreiro, David Fondo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.5
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    • pp.998-1013
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    • 2013
  • Wireless wearable sensor networks have emerged as a promising technique for human motion tracking due to the flexibility and scalability. In such system several wireless sensor nodes being attached to human limb construct a wearable sensor network, where each sensor node including MEMS sensors (such as 3-axis accelerometer, 3-axis magnetometer and 3-axis gyroscope) monitors the limb orientation and transmits these information to the base station for reconstruction via low-power wireless communication technique. Due to the energy constraint, the high fidelity requirement for real time rendering of human motion and tiny operating system embedded in each sensor node adds more challenges for the system implementation. In this paper, we discuss such challenges and experiences in detail during the implementation of such system with wireless wearable sensor network which includes COTS wireless sensor nodes (Imote 2) and uses TinyOS 1.x in each sensor node. Since our system uses the COTS sensor nodes and popular tiny operating system, it might be helpful for further exploration in such field.

Development of wearable devices and mobile apps for fall detection and health management

  • Tae-Seung Ko;Byeong-Joo Kim;Jeong-Woo Jwa
    • International Journal of Advanced Culture Technology
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    • v.11 no.1
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    • pp.370-375
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    • 2023
  • As we enter a super-aged society, studies are being conducted to reduce complications and deaths caused by falls in elderly adults. Research is being conducted on interventions for preventing falls in the elderly, wearable devices for detecting falls, and methods for improving the performance of fall detection algorithms. Wearable devices for detecting falls of the elderly generally use gyro sensors. In addition, to improve the performance of the fall detection algorithm, an artificial intelligence algorithm is applied to the x, y, z coordinate data collected from the gyro sensor. In this paper, we develop a wearable device that uses a gyro sensor, body temperature, and heart rate sensor for health management as well as fall detection for the elderly. In addition, we develop a fall detection and health management system that works with wearable devices and a guardian's mobile app to improve the performance of the fall detection algorithm and provide health information to guardians.

A Research for Removing ECG Noise and Transmitting 1-channel of 3-axis Accelerometer Signal in Wearable Sensor Node Based on WSN (무선센서네트워크 기반의 웨어러블 센서노드에서 3축 가속도 신호의 단채널 전송과 심전도 노이즈 제거에 대한 연구)

  • Lee, Seung-Chul;Chung, Wan-Young
    • Journal of Sensor Science and Technology
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    • v.20 no.2
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    • pp.137-144
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    • 2011
  • Wireless sensor network(WSN) has the potential to greatly effect many aspects of u-healthcare. By outfitting the potential with WSN, wearable sensor node can collects real-time data on physiological status and transmits through base station to server PC. However, there is a significant gap between WSN and healthcare. WSN has the limited resource about computing capability and data transmission according to bio-sensor sampling rates and channels to apply healthcare system. If a wearable node transmits ECG and accelerometer data of 4 channel sampled at 100 Hz, these data may occur high loss packets for transmitting human activity and ECG to server PC. Therefore current wearable sensor nodes have to solve above mentioned problems to be suited for u-healthcare system. Most WSN based activity and ECG monitoring system have been implemented some algorithms which are applied for signal vector magnitude(SVM) algorithm and ECG noise algorithm in server PC. In this paper, A wearable sensor node using integrated ECG and 3-axial accelerometer based on wireless sensor network is designed and developed. It can form multi-hop network with relay nodes to extend network range in WSN. Our wearable nodes can transmit 1-channel activity data processed activity classification data vector using SVM algorithm to 3-channel accelerometer data. ECG signals are contaminated with high frequency noise such as power line interference and muscle artifact. Our wearable sensor nodes can remove high frequency noise to clear original ECG signal for healthcare monitoring.

Advances in Non-Interference Sensing for Wearable Sensors: Selectively Detecting Multi-Signals from Pressure, Strain, and Temperature

  • Byung Ku Jung;Yoonji Yang;Soong Ju Oh
    • Journal of Sensor Science and Technology
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    • v.32 no.6
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    • pp.340-351
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    • 2023
  • Wearable sensors designed for strain, pressure, and temperature measurements are essential for monitoring human movements, health status, physiological data, and responses to external stimuli. Notably, recent research has led to the development of high-performance wearable sensors using innovative materials and device structures that exhibit ultra-high sensitivity compared with their commercial counterparts. However, the quest for accurate sensing has identified a critical challenge. Specifically, the mechanical flexibility of the substrates in wearable sensors can introduce interference signals, particularly when subjected to varying external stimuli and environmental conditions, potentially resulting in signal crosstalk and compromised data fidelity. Consequently, the pursuit of non-interference sensing technology is pivotal for enabling independent measurements of concurrent input signals related to strain, pressure, and temperature, ensuring precise signal acquisition. In this comprehensive review, we present an overview of the recent advances in noninterference sensing strategies. We explore various fabrication methods for sensing strain, pressure, and temperature, emphasizing the use of hybrid composite materials with distinct mechanical properties. This review contributes to the understanding of critical developments in wearable sensor technology that are vital for their ongoing application and evolution in numerous fields.

Nanoparticle based Wearable Sensor (나노입자 기반의 웨어러블 센서)

  • Woo, Ho Kun;Ahn, Junhyuk;Oh, Soong ju
    • Ceramist
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    • v.22 no.1
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    • pp.4-16
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    • 2019
  • Recently, wearable sensors have received considerable attention in a variety of research fields and industries as the importance of wearable healthcare systems, soft robotics and bio-integrated devices increased. However, expensive and complex processes are hindering the commercialization of wearable sensors. Nanoparticle presents some of solutions to these problems as its adjustable for processability and tunable properties. In this paper, the recent development of nanoparticle based pressure and strain sensors was reviewed, and a discussion on their strategies to overcome the conventional limitation and operating principles is presented.

Wearable System for Real-time Monitoring of Multiple Vital Signs (인체 착용형 다중 생체신호 실시간 모니터링 시스템)

  • Lee, Young-Dong;Chung, Wan-Young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2008.05a
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    • pp.249-252
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    • 2008
  • A wearable ubiquitous health care monitoring system using integrated ECG and accelerometersensors based on WSN is designed and developed. Wireless sensor network technology is applied for non intrusive healthcare in some wide area coverage with small battery support for RF transmission. We developed wearable devices which are wearable USN node, sensor board and base-station. Low power operating ECG and accelerometer sensor board was integrated to wearable USN node for user's health monitoring. The wearable ubiquitous healthcare monitoring system allows physiological data to be transmitted in wireless sensor network from on body wearable sensor devices to a base-station connected to server PC using IEEE 802.15.4. Physiological data displays and stores on server PC continuously.

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Skin-interfaced Wearable Biosensors: A Mini-Review

  • Kim, Taehwan;Park, Inkyu
    • Journal of Sensor Science and Technology
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    • v.31 no.2
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    • pp.71-78
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    • 2022
  • Wearable devices have the potential to revolutionize future medical diagnostics and personal healthcare. The integration of biosensors into scalable form factors allow continuous and noninvasive monitoring of key biomarkers and various physiological indicators. However, conventional wearable devices have critical limitations owing to their rigid and obtrusive interfaces. Recent developments in functional biocompatible materials, micro/nanofabrication methods, multimodal sensor mechanisms, and device integration technologies have provided the foundation for novel skin-interfaced bioelectronics for advanced and user-friendly wearable devices. Nonetheless, it is a great challenge to satisfy a wide range of design parameters in fabricating an authentic skin-interfaced device while maintaining its edge over conventional devices. This review highlights recent advances in skin-compatible materials, biosensor performance, and energy-harvesting methods that shed light on the future of wearable devices for digital health and personalized medicine.