• Title/Summary/Keyword: wearable sensors

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Design of a Smart Safety Enforcement System for Patients with Dementia (치매 환자를 위한 지능형 안전강화 시스템 설계)

  • Pi, Kyungjoon;Lee, Kyungmi;Min, Hong
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.20 no.6
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    • pp.59-64
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    • 2020
  • As the number of elderly people rapidly increases, needs of patient safety monitoring system also increases in indoor and outdoor medical facilities. With developing technologies related to sensors and information and communication technology, various dementia patient monitoring systems have been proposed. However, previous studies that depend on wearable devices provides limited functionalities. In this paper, we designed an integrated system that includes smart devices to monitor patient's status, user friendly UI/UX, and interaction with hospital information system. Medical teams and carers can receive satus of each patient in real-time and trace the location of dementia patients outdoor as well as indoor by using the proposed system.

Security Threats and Attacks in Internet of Things (IOTs)

  • Almtrafi, Sara Mutlaq;Alkhudadi, Bdour Abduallatif;Sami, Gofran;Alhakami, Wajdi
    • International Journal of Computer Science & Network Security
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    • v.21 no.1
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    • pp.107-118
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    • 2021
  • The term Internet of Things (IoTs) refers to the future where things are known daily through the Internet, whether in one way or another, as it is done by the method of collecting various information from various sensors to form a huge network through which people, things and machines are helped to make a link between them at all time and anywhere. The IoTs is everywhere around us such as connected appliances, smart homes security systems and wearable health monitors. However, the question is what if there is a malfunction or outside interference that affects the work of these IoTs based devises? This is the reason of the spread of security causes great concern with the widespread availability of the Internet and Internet devices that are subject to many attacks. Since there aren't many studies that combines requirements, mechanisms, and the attacks of the IoTs, this paper which explores recent published studies between 2017 and 2020 considering different security approaches of protection related to the authentication, integrity, availability and confidentiality Additionally, the paper addresses the different types of attacks in IoTs. We have also addressed the different approaches aim to prevention mechanisms according to several researchers' conclusions and recommendations.

A Novel Spiking Neural Network for ECG signal Classification

  • Rana, Amrita;Kim, Kyung Ki
    • Journal of Sensor Science and Technology
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    • v.30 no.1
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    • pp.20-24
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    • 2021
  • The electrocardiogram (ECG) is one of the most extensively employed signals used to diagnose and predict cardiovascular diseases (CVDs). In recent years, several deep learning (DL) models have been proposed to improve detection accuracy. Among these, deep neural networks (DNNs) are the most popular, wherein the features are extracted automatically. Despite the increment in classification accuracy, DL models require exorbitant computational resources and power. This causes the mapping of DNNs to be slow; in addition, the mapping is challenging for a wearable device. Embedded systems have constrained power and memory resources. Therefore full-precision DNNs are not easily deployable on devices. To make the neural network faster and more power-efficient, spiking neural networks (SNNs) have been introduced for fewer operations and less complex hardware resources. However, the conventional SNN has low accuracy and high computational cost. Therefore, this paper proposes a new binarized SNN which modifies the synaptic weights of SNN constraining it to be binary (+1 and -1). In the simulation results, this paper compares the DL models and SNNs and evaluates which model is optimal for ECG classification. Although there is a slight compromise in accuracy, the latter proves to be energy-efficient.

An Observational Study of Office Workers' Postural Behaviors During Computer Work (사무직 근로자의 컴퓨터 작업 자세의 관찰 연구)

  • Jun, Deok-Hoon;Goo, Mi-Ran
    • PNF and Movement
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    • v.19 no.2
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    • pp.243-250
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    • 2021
  • Purpose: The purpose of this study was to observe office workers' postural behaviors during computer work to identify the risk factors for head and thorax postural behaviors. Methods: The participants included 57 office workers who worked longer than 20 hours on a computer. Postural behaviors during computer work were measured using 3-D wearable motion sensors on the forehead and sternum. A multivariate linear regression model evaluated the association between various risk factors (neck pain, demographics, and environmental factors) and non-head and thorax postural behaviors. Results: The participants maintained their head and thorax in neutral postures (defined as 10° extension~10° flexion and 5° extension~10° flexion, respectively) for 24.7% and 39.3% of the total recorded time. Those who reported neck pain at the measurement of postural behaviors showed less time spent in thorax postures. Current neck pain, high desk height, and the distance between the keyboard and the edge of the desk (cm) were found to be related to less time spent in a neutral thorax posture. Conclusion: Office environment factors and current neck pain might affect workers' thorax postures, which might also determine the orientation of head postures during computer work.

Solution-Processed Two-Dimensional Materials for Scalable Production of Photodetector Arrays

  • Rhee, Dongjoon;Kim, Jihyun;Kang, Joohoon
    • Journal of Sensor Science and Technology
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    • v.31 no.4
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    • pp.228-237
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    • 2022
  • Two-dimensional (2D) nanomaterials have demonstrated the potential to replace silicon and compound semiconductors that are conventionally used in photodetectors. These materials are ultrathin and have superior electrical and optoelectronic properties as well as mechanical flexibility. Consequently, they are particularly advantageous for fabricating high-performance photodetectors that can be used for wearable device applications and Internet of Things technology. Although prototype photodetectors based on single microflakes of 2D materials have demonstrated excellent photoresponsivity across the entire optical spectrum, their practical applications are limited due to the difficulties in scaling up the synthesis process while maintaining the optoelectronic performance. In this review, we discuss facile methods to mass-produce 2D material-based photodetectors based on the exfoliation of van der Waals crystals into nanosheet dispersions. We first introduce the liquid-phase exfoliation process, which has been widely investigated for the scalable fabrication of photodetectors. Solution processing techniques to assemble 2D nanosheets into thin films and the optoelectronic performance of the fabricated devices are also presented. We conclude by discussing the limitations associated with liquid-phase exfoliation and the recent advances made due to the development of the electrochemical exfoliation process with molecular intercalants.

Classification of Fall Direction Before Impact Using Machine Learning Based on IMU Raw Signals (IMU 원신호 기반의 기계학습을 통한 충격전 낙상방향 분류)

  • Lee, Hyeon Bin;Lee, Chang June;Lee, Jung Keun
    • Journal of Sensor Science and Technology
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    • v.31 no.2
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    • pp.96-101
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    • 2022
  • As the elderly population gradually increases, the risk of fatal fall accidents among the elderly is increasing. One way to cope with a fall accident is to determine the fall direction before impact using a wearable inertial measurement unit (IMU). In this context, a previous study proposed a method of classifying fall directions using a support vector machine with sensor velocity, acceleration, and tilt angle as input parameters. However, in this method, the IMU signals are processed through several processes, including a Kalman filter and the integration of acceleration, which involves a large amount of computation and error factors. Therefore, this paper proposes a machine learning-based method that classifies the fall direction before impact using IMU raw signals rather than processed data. In this study, we investigated the effects of the following two factors on the classification performance: (1) the usage of processed/raw signals and (2) the selection of machine learning techniques. First, as a result of comparing the processed/raw signals, the difference in sensitivities between the two methods was within 5%, indicating an equivalent level of classification performance. Second, as a result of comparing six machine learning techniques, K-nearest neighbor and naive Bayes exhibited excellent performance with a sensitivity of 86.0% and 84.1%, respectively.

Assessing the Human Perceptions of Physical Environmental Stressors Through Behavior Response Examination

  • Kim, Siyeon;Kim, Yeon Joo;Kim, Hyunsoo;Hwang, Sungjoo
    • International conference on construction engineering and project management
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    • 2022.06a
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    • pp.855-862
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    • 2022
  • Environmental stressors considerably influence the health and safety of humans and must thus be continuously monitored to enhance the urban environments and associated safety. Environmental stressors typically act as stimuli and lead to behavioral changes that can be easily identified. These behavioral responses can thus be used as indicators to clarify people's perceptions of environmental stressors. Therefore, in this study, a framework for assessing environmental stressors based on human behavioral responses was developed. A preliminary experiment was conducted to investigate the feasibility of the framework. Human behavioral and physiological data were collected using wearable sensors, and a survey was performed to determine the psychological responses. Humans were noted to consistently exhibit changes in the movement and speed in the presence of physical environmental stressors, as physiological and psychological responses. The results demonstrated the potential of using behavioral responses as indicators of the human perceptions toward environmental stressors. The proposed framework can be used for urban environment monitoring to enhance the quality and safety.

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Analysis of instrument exercise using IMU about symmetry

  • Yohan Song;Hyun-Bin Zi;Jihyeon Kim;Hyangshin Ryu;Jaehyo Kim
    • International Journal of Advanced Culture Technology
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    • v.11 no.1
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    • pp.296-305
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    • 2023
  • The purpose of this study is to measure and compare the balance of motion between the left and right using a wearable sensor during upper limb exercise using an exercise equipment. Eight participants were asked to perform upper limb exercise using exercise equipment, and exercise data were measured through IMU sensors attached to both wrists. As a result of the PCA test, Euler Yaw(Left: 0.65, Right: 0.75), Roll(Left: 0.72, Right: 0.58), and Gyro X(Left: 0.64, Right: 0.63) were identified as the main components in the Butterfly exercise, and Euler Pitch(Left: 0.70, Right 0.70) and Gyro Z(Left: 0.70, Right: 0.71) were identified as the main components in the Lat pull down exercise. As a result of the Paired-T test of the Euler value, Yaw's Peak to Peak at Butterfly exercise and Roll's Mean, Yaw's Mean and Period at Lat pull down exercise were smaller than the significance level of 0.05, proving meaningful difference was found. In the Symmetry Index and Symmetry Ratio analysis, 89% of the subjects showed a tendency of dominant limb maintaining relatively higher angular movement performance then non-dominant limb as the Butterfly exercise proceeds. 62.5% of the subjects showed the same tendency during the Lat pull down exercise. These experimental results indicate that meaningful difference at balance of motion was found according to an increase in number of exercise trials.

Industry 4.0 & Construction H&S: Comparative Perceptions

  • Beale, James;Smallwood, John
    • International conference on construction engineering and project management
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    • 2020.12a
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    • pp.249-256
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    • 2020
  • Historical construction health and safety (H&S) challenges, in terms of a range of resources and issues, continue to be experienced, namely design process-related hazards are encountered on site, workers are unaware of the hazards and risks related to the construction process and its activities, activities are commenced on site without adequate hazard identification and risk assessments (HIRAs), difficulty is experienced in terms of real time monitoring of construction-related activities, workers handle heavy materials, plant, and equipment, and ultimately the experience of injuries. Given the abovementioned, and the advent of Industry 4.0, a quantitative study, which entailed the completion of a self-administered questionnaire online, was conducted among registered professional (Pr) and candidate Construction H&S Agents, to determine the potential of Industry 4.0 to contribute to resolving the challenges cited. The findings indicate that Industry 4.0 technologies such as augmented reality (AR), drone technology, virtual reality (VR), VR based H&S training, and wearable technology /sensors have the potential to resolve the cited H&S challenges as experienced in construction. Conclusions include that Industry 4.0 technologies can finally address the persistent H&S challenges experienced in construction. Recommendations include: employer associations, professional associations, and statutory councils should raise the level of awareness relative to the potential implementation of Industry 4.0 relative to H&S in construction; case studies should be documented and shared; tertiary construction management education programmes should integrate Industry 4.0 into all possible modules, especially H&S-related modules, and continuing professional development (CPD) H&S should address Industry 4.0.

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Engineered Stretchability of Conformal Parylene Thin-film On-skin Electronics

  • Jungho Lee;Gaeun Yun;Juhyeong Jeon;Phuong Thao Le;Seung Whan Kim;Geunbae Lim
    • Journal of Sensor Science and Technology
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    • v.32 no.6
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    • pp.335-339
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    • 2023
  • Skin-compatible electronics have evolved to achieve both conformality and stretchability for stable contact with deformable biological skin. While existing research has largely concentrated on alternative materials, the potential of Parylene-based thin-film electrodes for stretchable on-skin applications remains relatively untapped. This study proposes an engineering strategy to achieve stretchability using the Parylene thin-film electrode. Unlike the conventional Parylene thin-film electrode, we introduce morphological adaptability via controlled microscale slits in the Parylene electrode structure. The slits-containing device enables unprecedented stretchability while maintaining critical electrical insulation properties during mechanical deformation. Finally, the demonstration on human skin shows the mechanical adaptability of these Parylene-based bioelectrodes while their electrical characteristics remain stable during various stretching conditions. Owing to the ultra-thinness of the Parylene coating, the wearable bioelectrode not only achieves stretchability but also conforms to the skin. Our findings broaden the practical use of Parylene thin-film bioelectrodes.