• Title/Summary/Keyword: Wearable device

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A Study on Finger-click Recognition of a Wearable Input Device using Inertial Sensors (관성 센서를 이용한 착용형 공간 입력장치의 클릭 인식에 관한 연구)

  • Soh, Byung-Seok;Kim, Yoon-Sang;Lee, Sang-Goog
    • Proceedings of the KIEE Conference
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    • 2004.05a
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    • pp.120-122
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    • 2004
  • Wearable input device that can make free-space typewriting possible is introduced. We named this device as $SCURRY^{TM}$. To measure the angular velocity of hand and the acceleration rates at the ends of fingers, we buried MEMS inertial sensors in this keyboard. We processed sensor signals to get the information on hand movement and finger-click motion. With this signal processing, apparent finger movements were depicted over the virtual keyboard shown on output device of a target computing system. In this paper, a finger-click recognition method is proposed to improve the recognition performance for finger clicking of $SCURRY^{TM}$. The proposed method is composed of three parts including feature extraction part, valid click part, and cross-talk avoidance part. The experiments were conducted to verify the effectiveness and efficiency of the proposed algorithms.

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Evaluating Performance of Pointing Interface of Dynamic Gain Control in Wearable Computing Environment (웨어러블 컴퓨터 환경에서 포인팅 인터페이스의 동적 이득 방법의 효율성 평가)

  • Hong, Ji-Young;Chae, Haeng-Suk;Han, Kwang-Hee
    • Journal of the Ergonomics Society of Korea
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    • v.26 no.4
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    • pp.9-16
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    • 2007
  • Input devices of wearable computer are difficult to use, so a lot of alternative pointing devices have been considered in recent years. In order to resolve this problem, this paper proposed a dynamic gain control method which is able to improve the performance of wearable pointing device and showed an experimental result comparing this method with conventional method. Also the effects of methods were compared in terms of device (wearable and desktop). The result of calculating throughputs(index of performance) by Fitts' law showed that the pointing performance in dynamic gain condition was improved 1.4 times more than normal gain.

The Structural Relationships among Innovation Characteristics, Consumer Characteristics, Innovation Resistance, and Intention to Acceptance of Wearable Device Customers: Based on Innovation Resistance Model and Theory of Perceived Risk (웨어러블 디바이스 소비자의 혁신특성, 소비자특성, 혁신저항, 그리고 수용의도와의 구조적 관계: 혁신저항모형과 인지된 위험이론을 기반으로)

  • Bae, Jae Kwon
    • The Journal of Information Systems
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    • v.25 no.4
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    • pp.87-104
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    • 2016
  • Purpose As the smartphone market arrived at its saturation, from world leading information and communications technologies (ICT) businesses to startups, companies are competing to develop innovative wearable device products and suitable contents. Utility, technology, design, price, and various killer contents development targeting every customer's need should be considered for a success in the wearable device market. Design/methodology/approach Prior studies on innovation technology of ICT field have mainly focused on the innovation diffusion theory, expectation confirmation theory, and technology acceptance model, this study suggested the innovation resistance factors of adopting the smart wearable devices based on the innovation resistance model and theory of perceived risk. The model comprises the following two characteristics factors: 1) innovation characteristics which include perceived relative advantages, perceived compatability, perceived complexity, and perceived risk, 2) consumer characteristics which include attitudes towards innovation and existing products (i.e., mobile devices and analog watches). This study developed an extended innovation resistance model to explain the intention to acceptance of wearable devices consumers and collected 284 online survey responses from the non-consumers of the wearable devices. Findings The findings of this study suggest that perceived relative advantage, perceived compatibility, perceived complexity, perceived risk, attitudes towards innovation and attitudes towards existing analog watches affected the innovation resistance which has negative influence on the intention to adoption of wearable devices.

Implementation of 3D Information Acquisition Device for Wearable U-Health (착용형 U-헬스용 3D 정보 입력장치 구현)

  • Kim, Yoon-Ho;Park, Ki-Hong
    • Journal of Advanced Navigation Technology
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    • v.12 no.6
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    • pp.640-645
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    • 2008
  • In progress to ubiquitous intelligent society, there are emerging technologies such smart wear related researches as wearable computer, smart fiber and smart fashion. In this paper, wearable 3D information acquisition device which improved both advanced in convenience and portable is implemented. 3D information input system is basically grouped of some modules; Gyro sensor for acquisition of 3D space coordinate, RF transmitter/receiver, and signal processing module etc. To testify the validity of designed system, some experiments are performed using lest board with respect to the communication distance, easiness of wearable and operation sensibility.

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Correlation Between Physical Activity Measured by a Wearable Device and Quality of Life in Older Adults

  • Kim, Si-hyun
    • Physical Therapy Korea
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    • v.28 no.4
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    • pp.251-255
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    • 2021
  • Background: Physical activity and quality of life (QOL) influence the health status of older adults. Recently, the use of wearable devices to monitor physical activity has increased. Objects: This study examined the relationship between the amount of physical activity, measured using a wearable device, and QOL among older adults. Methods: In total, 71 older adults (aged ≥ 65 years) were enrolled. The amount of physical activity was measured using a wearable device with a wrist strap, and daily physical activity was classified according to intensity (sedentary, light, moderate, or very active). Self-reported QOL was evaluated using the Short Form 36 (SF-36) questionnaire. Pearson and Spearman correlation analyses were conducted to analyze parametric and non-parametric variables, respectively. The relationship between amount of daily physical activity and SF-36 scores was assessed. Results: The correlation analyses revealed positive correlations between the amount of moderate-intensity and very active physical activity (minutes/day) and SF-36 scores (p < 0.05). Conclusion: Physical activity of at least moderate intensity is associated with better QOL in older adults. Further studies are required to verify the effects of increased physical activity on QOL in older adults.

Group Decision Algorithm for Convergence Oriented Group Display of Several Wearable Devices (복수 개의 웨어러블 디바이스들의 융합지향 그룹 디스플레이를 위한 그룹결정 알고리즘)

  • Kim, Yong-Gil;Kim, Yong-Ki;Kim, Mi-Hye
    • Journal of the Korea Convergence Society
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    • v.8 no.8
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    • pp.27-32
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    • 2017
  • The several wearable devices are not able to communicate through cable due to its portability. The wireless communication method is used because of its good communication quality and group action features when the several wearable devices communicate with each other. In this paper, we proposed the group decision algorithm for grouping display of the several wearable devices. It means that recognize as a group member after measuring distance in the wireless communication environment. The result of experience showed that the group-type display of several wearable devices method overcome the limit of the display of single wearable device.

The Plug-in Module for Simultaneous Monitoring of Multi Bio-signal in Wearable Devices (착용형 단말에서 다수 생체신호의 동시 측정을 가능하게 하는 플러그인 모듈)

  • Choi, Moon Sik;Choi, Dong Jin;Kang, Soon Ju
    • KIISE Transactions on Computing Practices
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    • v.22 no.4
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    • pp.195-200
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    • 2016
  • With development of wearable devices, there is an increased interest in bio-signal monitoring techniques that can measure the user's health condition. However, embedding several bio-signal sensors in one wearable device has some inherent problems in terms of limited resources such as its size. Furthermore, such problem also arise when new bio-signal sensors are added. In this paper, we introduced the Bio-Cradle, which is a Plug-in module that can transfer the biological signals in real time from the accelerometer, ECG, or PPG sensor to other wearable devices at the request from the user of wearable devices. When the Bio-Cradle plugged in to the other device, it can transfer several synchronized bio-signals regardless of the type of device.

A Study on the game app production utilizing wearable smart device health care information (웨어러블 스마트 디바이스의 헬스 케어 정보를 활용한 게임 앱 제작에 관한 연구)

  • Choi, Yong-Seok;Ju, Woo-Suk
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.05a
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    • pp.168-169
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    • 2015
  • Recent wearable smart device products, but with a variety of features and form that go out after a series of releases in has been outside for a lack of consumer content. The device advances, the type of equipment attached to the user's body was released, which was the background to be subjected to a health-care products of interest to the user and the machine-to-machine interaction. This study is to identify health care elements wearable smart device content around the market with features to interact with the game content and game content derived elements fit smart wearable devices. Survey research method was developed or released wearable devices and game content and take advantage of this any existing research literature related to game development. Based on this we derive the interactive elements for a wearable smart devices based.

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A Hand Gesture Recognition Method using Inertial Sensor for Rapid Operation on Embedded Device

  • Lee, Sangyub;Lee, Jaekyu;Cho, Hyeonjoong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.2
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    • pp.757-770
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    • 2020
  • We propose a hand gesture recognition method that is compatible with a head-up display (HUD) including small processing resource. For fast link adaptation with HUD, it is necessary to rapidly process gesture recognition and send the minimum amount of driver hand gesture data from the wearable device. Therefore, we use a method that recognizes each hand gesture with an inertial measurement unit (IMU) sensor based on revised correlation matching. The method of gesture recognition is executed by calculating the correlation between every axis of the acquired data set. By classifying pre-defined gesture values and actions, the proposed method enables rapid recognition. Furthermore, we evaluate the performance of the algorithm, which can be implanted within wearable bands, requiring a minimal process load. The experimental results evaluated the feasibility and effectiveness of our decomposed correlation matching method. Furthermore, we tested the proposed algorithm to confirm the effectiveness of the system using pre-defined gestures of specific motions with a wearable platform device. The experimental results validated the feasibility and effectiveness of the proposed hand gesture recognition system. Despite being based on a very simple concept, the proposed algorithm showed good performance in recognition accuracy.