• The Journal of Economics, Marketing and Management
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• v.10 no.4
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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.

• Journal of Sensor Science and Technology
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• v.32 no.6
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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.

• 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.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.1
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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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• 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.

• Journal of Digital Convergence
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• v.15 no.4
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• pp.205-212
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• 2017

This study examined the factors affecting the intention to use the wearable device consumers and the factors that have positive effects on the intention to use the wearable device or the consumers who have not yet used the wearable device. The purpose of this study was to examine the perceived usefulness, perceived usefulness, consumer individuality (individual innovation, self-efficacy, subjective norm) and wearable device characteristics (aesthetics, compatibility) of technology acceptance model (TAM). The results of the analysis are as follows. This study focused on the effect of consumers on the intention to use. (TPB) and Davis (1989) proposed technology acceptance model which is applied to various fields to predict the intention to use as it is proved validity and usefulness as a theory explaining various social behaviors. TAM) in order to examine the intention to use. In addition, we added consumer characteristics and variables related to product characteristics of wearable devices, which have not been studied much in previous studies.

• Journal of the Korea Convergence Society
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• v.10 no.4
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• pp.7-16
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• 2019

As fierce competition is expected in the wearable devices marekt, it is needed to develop a technology planning that can increase consumer acceptance. This study aims to provide implications for technology planning of wearable devices by examining consumer preferences for the devices. For this purpose we employed a conjoint analysis. In the process of the analysis, we considered the trend of anticipatory standardization for wearable devices in an attempt to improve objectivity of analysis whilst many previous studies relied on focus group interview. For the anticipatory standardization information, we utilized liaisons and projects of wearable devices at International Electrotechnical Commission, and we designed a conjoint survey on the basis of the information. We conducted an online survey, and a total of 229 individuals responded to our survey. The result of conjoint analysis shows that main use and enhanced features were more important attributes than the others were. However, consumer preferences for detailed levels of each attribute were different by gender and age groups. This result implies that technology planning of wearable devices require distinct approaches by consumer segments.

• Journal of Advanced Navigation Technology
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• v.19 no.5
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• pp.452-457
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• 2015

Recently, wearable devices have gained popularity with familiar form factors and designs of eye-wear and watch to satisfy wearers' various preferences. Since UI/UX of smartphones can not be applied directly on smaller wearable devices, text entry on wearable devices is still problematic. In this paper, we first identify UI/UX problems of existing input methods and propose a new input method for wearable devices specifically targeting smartwatch platforms. We design and implement an efficient text entry method for wearable devices using trackball sensor and evaluate its performance and usability.

• International Journal of Advanced Culture Technology
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• v.9 no.3
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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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• 2004.08a
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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.