• 융합경영연구
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• 제10권4호
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• pp.13-24
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• 2022

Purpose: Although numerous research has covered content on trends in the adoption and use of wearable devices, their uses across several sectors such as healthcare, gaming, and fashion, there seems to be a considerable paucity with regard to empirical research focusing on the solutions for factors that undermine the effectiveness of wearable devices in healthcare. The present research aims to highlight what has been covered on wearable devices in healthcare while highlighting the limitations for future research. Research design, data, and methodology -The present authors conducted one of the most famous qualitative literature approach which has been called as PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) statement. The selecting criteria for eligible prior studies was estimated by whether studies are suitable for the current research, identifying they are peer-reviewed and issued by notable publishers between 2017 and 2022. Result - Our results indicated that (1) Increasing the Affordability and User Education on Wearable Devices in Healthcare (2) Tackling the Technological Issues in Wearable Devices to Promote Healthcare Delivery (3) Solving Security and Privacy Issues Associated with Wearable Devices (4) Promoting Standards and Appropriate Regulations for Wearable Devices. Conclusion - To add, resolving the technological issues associated with wearable devices in healthcare will ensure that the new devices in the market will have longer battery life, multiple functions, and enhanced accuracy, thus ensuring that patients receive better care. Necessary interventions are taken on time to avoid any deleterious consequences such as proliferating mortality rates among the different patient groups.

• 센서학회지
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• 제32권6호
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• pp.378-385
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• 2023

Human biosignals provide essential information for diagnosing diseases such as dementia and Parkinson's disease. Owing to the shortcomings of current clinical assessments, noninvasive solutions are required. Machine learning (ML) on wearable sensor data is a promising method for the real-time monitoring and early detection of abnormalities. ML facilitates disease identification, severity measurement, and remote rehabilitation by providing continuous feedback. In the context of wearable sensor technology, ML involves training on observed data for tasks such as classification and regression with applications in clinical metrics. Although supervised ML presents challenges in clinical settings, unsupervised learning, which focuses on tasks such as cluster identification and anomaly detection, has emerged as a useful alternative. This review examines and discusses a variety of ML algorithms such as Support Vector Machines (SVM), Random Forests (RF), Decision Trees (DT), Neural Networks (NN), and Deep Learning for the analysis of complex clinical data.

• 한국정보시스템학회지:정보시스템연구
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• 제25권4호
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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.

• 디지털산업정보학회논문지
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• 제11권1호
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• pp.145-155
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• 2015

The game industry has changed along with the advancement of device technology. The wearable, a recently appeared device will create new demand in this saturated age of the smart devices. The game industry's content targeted towards the wearable devices will play an important role as main driving source. For this reason, this research studies the development aspect and the current technical capabilities of games' platforms and contents by analyzing the contrast between the results of features and current situations of the wearable market. Consequently, we define the prospects of game content for wearable device. We also expect that the new style of the game content, combined with cloud game, augmented reality game and virtual reality game will appear in the next generation platforms gearing towards the wearable devices.

• International Journal of Advanced Culture Technology
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• 제11권1호
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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.

• 디지털융복합연구
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• 제15권4호
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• pp.205-212
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• 2017

본 연구는 웨어러블 디바이스 소비자의 사용의도에 영향을 미치는 요인에 관한 주제를 가지고 웨어러블 디바이스를 사용한 경험이 있거나, 아직 사용경험이 없는 소비자의 사용의도에 긍정적 영향을 끼치는 요인들을 파악하였다. 일반 성인남녀를 대상으로 기술수용모델(TAM)의 지각된 사용용이성, 지각된 유용성 그리고 소비자 개인특성(개인 혁신성, 자기효능감, 주관적 규범)과 웨어러블 디바이스의 특성(심미성, 호환성)이 사용의도에 미치는 영향에 대해 분석하였다. 본 연구는 소비자 개인의 사용의도에 미치는 영향에 초점을 맞췄다. 본 연구에 사용된 설문지는 총 296부이며 표본추출은 임의표본추출을 사용하였으며 SPSS 23.0으로 분석하였다. 회귀분석 결과, 사용의도에 대해서 지각된 사용, 자기효능감이 유의미하게 나타났으며, 나머지 변수는 유의미한 결과를 발견하기 어려웠다. TAM, 개인특성, 제품특성으로 웨어러블 디바이스에 대한 사용의도를 살펴본 본 연구는 제품의 종류의 특징에 따라 한계가 있음을 다시 확인하였다.

• 한국융합학회논문지
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• 제10권4호
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• pp.7-16
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• 2019

웨어러블 디바이스를 둘러싼 기업 간 경쟁이 치열해 짐에 따라, 소비자들의 수용성을 제고할 수 있는 기술기획이 필요한 상황이다. 이에 본 연구는 웨어러블 디바이스의 소비자 선호 속성을 파악함으로써 이 분야 기술기획을 위한 시사점을 제공하고자 하였다. 이를 위한 분석 방법으로는 컨조인트 분석을 활용하였다. 이 과정에서 초점집단면점을 주로 사용한 기존 연구들과는 달리 표준화 기구의 예지적 표준화 활동을 반영함으로써 분석의 객관성을 보완하고자 하였다. 예지적 표준화 활동으로는 국제전기기술위원회의 리에종 및 프로젝트 현황을 조사하였으며, 이를 바탕으로 컨조인트 분석을 설계하였다. 컨조인트 설문은 온라인으로 진행하여, 총 229명이 응답하였다. 분석 결과, 웨어러블 디바이스의 주용도와 강화된 기능이 중요한 속성으로 파악된 가운데, 속성 수준별 세부 선호도는 소비자 성별, 연령대별 다르게 나타났다. 따라서 웨어러블 디바이스의 기술기획 시에는 소비자 세그멘트별 차별화된 접근이 필요할 것으로 예상된다.

• 한국항행학회논문지
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• 제19권5호
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• pp.452-457
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• 2015

최근 사용자들의 취향을 고려하는 다양한 디자인을 내세워 기존의 안경, 시계 등의 친숙한 형태의 웨어러블 디바이스가 등장하면서 많은 인기를 얻고 있다. 하지만 착용이 가능한 초소형 디바이스라는 특성을 고려하지 않고 기존의 스마트폰 UI/UX를 적용하였기 때문에 작은 디스플레이 상에서 문자 입력이라는 문제점을 안고 있다. 이에 본 논문에서는 스마트워치와 같은 웨어러블 디바이스의 기존 입력 방법과 관련 연구들을 분석하여 UI/UX에 대한 문제점을 도출하고 스마트 워치를 위한 새로운 입력 방식을 제안한다. 이를 위해, 트랙볼 센서를 활용하여 웨어러블 디바이스에서 효율적인 문자 입력이 가능하도록 설계하고 구현한 결과를 통해 제안된 인터페이스의 유용성 및 성능을 검증한다.

• International Journal of Advanced Culture Technology
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• 제9권3호
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• pp.277-282
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• 2021

The generalization of social distancing due to the COVID-19 pandemic has rapidly spread non-face-to-face services, accelerating the speed of non-face-to-face digital conversion technology. The importance of telemedicine, a remote service, has been rekindled in the wearable technology including the medical industry. In a situation where it is not easy for any company to overcome the COVID-19 pandemic, it is a time when collaboration within the industry or between competitors is necessary. In addition to the digital-based online exhibition hall using AR-VR-MR technology, which is a major core technology of the future industry, virtual stores that can receive services such as actual shopping should be actively used. Paradoxically COVID-19 will provide new opportunities to reshape and reconnect the future of the textile and fashion industry. Therefore, the purpose of this study is to investigate the current status of wearable technology products being developed as fashion items for the prevention of COVID-19 and analyze their characteristics. This study results can be used as basic data for future research on the fashion industry and education.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.72-75
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• 2004

In this paper, a finger-click recognition method is proposed to improve the recognition performance for finger-clicking of a wearable input device, called $SCURRY^{TM}$. The proposed method is composed of three parts including feature extraction part, valid click discrimination part, and cross-talk avoidance part. Two types of MEMS inertial sensors are embedded into the wearable input device to measure the angular velocity of a hand (hand movement) and the acceleration rates at the ends of fingers (finger-click motion). The experiment applied to the $SCURRY^{TM}$ device shows the improved stability and performance.