• Title/Summary/Keyword: wearable biosensing

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Nanoplasmonics: An Enabling Platform for Integrated Photonics and Biosensing

  • Lee, Jihye;Yeo, Jong-Souk
    • Applied Science and Convergence Technology
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    • v.25 no.1
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    • pp.7-14
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    • 2016
  • Nanoplasmonics is a developing field that offers attractive optical, electrical, and thermal properties for a wide range of potential applications. Based on the compelling characteristics of this field, researchers have shed light on the possibilities of integrated photonics and biosensing platforms using nanoplasmonic principles. Single and unique nanostructures with plasmons can act as individual transducers that convert desired information into measurable and readable signals. In this review, we will discuss nanoplasmonic sensors, especially those in relation to photodetectors for future optical interconnects, and bioinformation sensing platforms based on nanoplasmonics, thus providing a viable approach by which to create sensors corresponding to target applications. In addition, we also discuss scalable fabrication processes for the creation of unconventional nanoplasmonic devices, which will enable next-generation plasmonic devices for wearable, flexible, and biocompatible systems.

Online Multi-Task Learning and Wearable Biosensor-based Detection of Multiple Seniors' Stress in Daily Interaction with the Urban Environment

  • Lee, Gaang;Jebelli, Houtan;Lee, SangHyun
    • International conference on construction engineering and project management
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    • 2020.12a
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    • pp.387-396
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    • 2020
  • Wearable biosensors have the potential to non-invasively and continuously monitor seniors' stress in their daily interaction with the urban environment, thereby enabling to address the stress and ultimately advance their outdoor mobility. However, current wearable biosensor-based stress detection methods have several drawbacks in field application due to their dependence on batch-learning algorithms. First, these methods train a single classifier, which might not account for multiple subjects' different physiological reactivity to stress. Second, they require a great deal of computational power to store and reuse all previous data for updating the signle classifier. To address this issue, we tested the feasibility of online multi-task learning (OMTL) algorithms to identify multiple seniors' stress from electrodermal activity (EDA) collected by a wristband-type biosensor in a daily trip setting. As a result, OMTL algorithms showed the higher test accuracy (75.7%, 76.2%, and 71.2%) than a batch-learning algorithm (64.8%). This finding demonstrates that the OMTL algorithms can strengthen the field applicability of the wearable biosensor-based stress detection, thereby contributing to better understanding the seniors' stress in the urban environment and ultimately advancing their mobility.

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High Performance Flexible Inorganic Electronic Systems

  • Park, Gwi-Il;Lee, Geon-Jae
    • Proceedings of the Korean Vacuum Society Conference
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    • 2012.08a
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    • pp.115-116
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    • 2012
  • The demand for flexible electronic systems such as wearable computers, E-paper, and flexible displays has increased due to their advantages of excellent portability, conformal contact with curved surfaces, light weight, and human friendly interfaces over present rigid electronic systems. This seminar introduces three recent progresses that can extend the application of high performance flexible inorganic electronics. The first part of this seminar will introduce a RRAM with a one transistor-one memristor (1T-1M) arrays on flexible substrates. Flexible memory is an essential part of electronics for data processing, storage, and radio frequency (RF) communication and thus a key element to realize such flexible electronic systems. Although several emerging memory technologies, including resistive switching memory, have been proposed, the cell-to-cell interference issue has to be overcome for flexible and high performance nonvolatile memory applications. The cell-to-cell interference between neighbouring memory cells occurs due to leakage current paths through adjacent low resistance state cells and induces not only unnecessary power consumption but also a misreading problem, a fatal obstacle in memory operation. To fabricate a fully functional flexible memory and prevent these unwanted effects, we integrated high performance flexible single crystal silicon transistors with an amorphous titanium oxide (a-TiO2) based memristor to control the logic state of memory. The $8{\times}8$ NOR type 1T-1M RRAM demonstrated the first random access memory operation on flexible substrates by controlling each memory unit cell independently. The second part of the seminar will discuss the flexible GaN LED on LCP substrates for implantable biosensor. Inorganic III-V light emitting diodes (LEDs) have superior characteristics, such as long-term stability, high efficiency, and strong brightness compared to conventional incandescent lamps and OLED. However, due to the brittle property of bulk inorganic semiconductor materials, III-V LED limits its applications in the field of high performance flexible electronics. This seminar introduces the first flexible and implantable GaN LED on plastic substrates that is transferred from bulk GaN on Si substrates. The superb properties of the flexible GaN thin film in terms of its wide band gap and high efficiency enable the dramatic extension of not only consumer electronic applications but also the biosensing scale. The flexible white LEDs are demonstrated for the feasibility of using a white light source for future flexible BLU devices. Finally a water-resist and a biocompatible PTFE-coated flexible LED biosensor can detect PSA at a detection limit of 1 ng/mL. These results show that the nitride-based flexible LED can be used as the future flexible display technology and a type of implantable LED biosensor for a therapy tool. The final part of this seminar will introduce a highly efficient and printable BaTiO3 thin film nanogenerator on plastic substrates. Energy harvesting technologies converting external biomechanical energy sources (such as heart beat, blood flow, muscle stretching and animal movements) into electrical energy is recently a highly demanding issue in the materials science community. Herein, we describe procedure suitable for generating and printing a lead-free microstructured BaTiO3 thin film nanogenerator on plastic substrates to overcome limitations appeared in conventional flexible ferroelectric devices. Flexible BaTiO3 thin film nanogenerator was fabricated and the piezoelectric properties and mechanically stability of ferroelectric devices were characterized. From the results, we demonstrate the highly efficient and stable performance of BaTiO3 thin film nanogenerator.

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Bio-Sensing Convergence Big Data Computing Architecture (바이오센싱 융합 빅데이터 컴퓨팅 아키텍처)

  • Ko, Myung-Sook;Lee, Tae-Gyu
    • KIPS Transactions on Software and Data Engineering
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    • v.7 no.2
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    • pp.43-50
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    • 2018
  • Biometric information computing is greatly influencing both a computing system and Big-data system based on the bio-information system that combines bio-signal sensors and bio-information processing. Unlike conventional data formats such as text, images, and videos, biometric information is represented by text-based values that give meaning to a bio-signal, important event moments are stored in an image format, a complex data format such as a video format is constructed for data prediction and analysis through time series analysis. Such a complex data structure may be separately requested by text, image, video format depending on characteristics of data required by individual biometric information application services, or may request complex data formats simultaneously depending on the situation. Since previous bio-information processing computing systems depend on conventional computing component, computing structure, and data processing method, they have many inefficiencies in terms of data processing performance, transmission capability, storage efficiency, and system safety. In this study, we propose an improved biosensing converged big data computing architecture to build a platform that supports biometric information processing computing effectively. The proposed architecture effectively supports data storage and transmission efficiency, computing performance, and system stability. And, it can lay the foundation for system implementation and biometric information service optimization optimized for future biometric information computing.