• Journal of Information Technology Services
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• v.19 no.3
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• pp.117-137
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• 2020

The development of information technology leads to changes in various industries. In particular, the health care industry is more influenced so that it is focused on. With the widening of the health care market, the market of smart device based personal health care also draws attention. Since a variety of fitness applications for smartphone based exercise were introduced, more interest has been in the health care industry. But although an amount of use of mobile fitness applications increase, it fails to lead to a sustained use. It is necessary to find and understand what matters for mobile fitness application users. Therefore, this study analyze the reviews of mobile fitness application users, to draw key factors, and thereby to propose detailed strategies for promoting mobile fitness applications. We utilize text mining techniques - LDA topic modeling, term frequency analysis, and keyword extraction - to draw and analyze the issues related to mobile fitness applications. In particular, the key factors drawn by text mining techniques are explained through the concept of user experience. This study is academically meaningful in the point that the key factors of mobile fitness applications are drawn by the user experience based text mining techniques, and practically this study proposes detailed strategies for promoting mobile fitness applications in the health care area.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.136-148
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• 2024

In recent years, public attention to health and wellness issues has increased. The integration of smart fitness hardware and innovative technologies have made the development of smart fitness a trend. The number of fitness applications in the market has surged, and demand for an optimal experience is increasingly high. This study selects Sweatcoin, Home Workout, Six Pack in 30 Days, and Fitness Coach & Diet as research subjects from the top ten global mobile health and fitness apps in 2022 based on download rankings. The research is based on eight gamification elements: motivation, challenge, achievement, relationships, sharing, reward, level, and competition, identified through preliminary studies. We distributed a total of 166 questionnaires to users and collected 163 valid responses for data analysis. The Kano Model was used to study the desires of fitness enthusiasts using fitness apps. To reduce the limitations of the research results, the Better-Worse Method was employed for satisfaction index analysis. Based on the final analysis, we propose suggestions for improvement for the four fitness apps to better meet user needs and create a more attractive and efficient application experience.

• Convergence Security Journal
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• v.22 no.1
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• pp.135-140
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• 2022

This study aims to analyze exercise cases and issues using smart devices and technologies, and to present the development direction of a smart exercise environment suitable for the wellness life of active seniors with high activity and economic power unlike the existing silver generation. In the fitness industry, the subscription economy that regularly receives or uses necessary exercise tools, services, and digital content is expanding, and business models based on hardware sales and content subscription continue to emerge. In order to have value competitiveness as a platform that provides active seniors with integrated exercise services for health care, not only fitness centers, but also home training exercise equipment, fitness-related applications, and smart wearable device markets should be organically connected to form an expanded total platform. In order to have value competitiveness as a platform that provides active seniors with integrated exercise services for health care, not only fitness centers, but also home training exercise equipment, fitness-related applications, and smart wearable device markets should be organically connected to form an expanded total platform. The linkage of the digital healthcare function, which provides real-time changes to exercise programs based on continuous monitoring and feed back through wearable devices before, after, and during exercise by receiving and selecting exercise programs suitable for individual health status, is the differentiating factor in the smart fitness model.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.2
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• pp.60-67
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• 2011

Since the non-metric Multidimensional scaling (nMDS), a data visualization technique, provides with insights about engineering, economic, and scientific applications, it is widely used for analyzing large non-metric multidimensional data sets. The nMDS requires a fitness function to measure fit of the proximity data by the distances among n objects. Most commonly used fitness functions are nonlinear and have a difficulty to find a good configuration. In this paper, we propose a new fitness function, an absolute value type, and show its advantages.

• Convergence Security Journal
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• v.16 no.4
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• pp.63-68
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• 2016

This study examined the current state of fitness IT which are commercially available, and proposed the prospect and promoting plans for fitness IT. Latest wearable smart market has been reorganized into smart watch market and fitness tracker market. Fitness trackers which are typical devices of fitness IT technology has developed various types of such as watch, band, clothes, glasses, and lens. Until now, the most popular type of fitness tracker are watch and band including clip, necklace, hair band etc.. Also Apple and Google referred to as the two major axes of mobile platform has provided a health-related platform such as "Healthkit" and "Google Fit" for preoccupying the fitness business. The view of the fitness IT has seen a continuous growth trend considering smaller and lighter of fitness-related wearable device. To continuous growth and promote of fitness IT, it is expected to require mash-up a variety of fitness applications and services, ensuring the convenience of user experience, design and resonable price.

• Journal of Digital Convergence
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• v.18 no.12
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• pp.97-103
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• 2020

The proposed system is composed of two parts, an AI physical fitness measurement part and an AI physical fitness management part. In the AI fitness measurement part, a guide to physical fitness measurement and accurate calculation of the measured value are performed through deep learning-based pose recognition. Based on these measurements, the AI fitness management part designs personalized exercise programs and provides them to dedicated smart applications. To guide the measurement posture, the posture of the subject to be measured is photographed through a webcam and the skeleton line is extracted. Next, the skeletal line of the learned preparation posture is compared with the extracted skeletal line to determine whether or not it is normal, and voice guidance is provided to maintain the normal posture.

• Journal of the Korea Convergence Society
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• v.10 no.6
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• pp.235-242
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• 2019

Recently, the use of artificial intelligence technology including deep learning has become active in various fields. In particular, several algorithms showing superior performance in object recognition and detection based on deep learning technology have been presented. In this paper, we propose the proper direction for the implementation of mobile healthcare application that user's convenience is effectively reflected. By effectively analyzing the current state of use satisfaction research for the existing fitness applications and the current status of mobile healthcare applications, we attempt to secure survival and superiority in the fitness application market, and, at the same time, to maintain and expand the existing user base.

• Information Systems Review
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• v.26 no.2
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• pp.185-203
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• 2024

This study empirically explores the influence of gamification elements and privacy concerns on users' intention to use fitness apps, based on the technology acceptance model (TAM). This research classifies gamification in fitness apps into three categories: achievement-related elements, social-related elements, and immersion-related elements. Although previous research investigated the gamification of fitness apps, few studies combined the impact of gamification with privacy concerns. Considering the significant amount of sensitive personal data collected by fitness apps, we recognize the importance of data privacy and aim to address this gap in research. To achieve this goal, we collected and analyzed data from 187 Korean fitness app users through an online questionnaire. The results confirm the highly significant influence of perceived ease of use, perceived usefulness, and achievement-related gamification elements. Social-related gamification elements, immersion-related gamification elements, and privacy concerns however show insignificant results for the intention to use fitness apps in the Korean market. Location and time limit the generalizability of this study; however, the findings of this study nonetheless offer valuable insights for practitioners and developers to enhance the design and development of their applications.

• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.4
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• pp.181-186
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• 2012

Obesity is one of the biggest problem in modern society. Smartphone could be a good tool to handle this problem. In this paper, we propose a new smartphone app to recommend diet, to offer a physical practice by motion games. Our Android smartphone application encourages friends to join group fitness programs. It interfaces with social network services and smart-TV.

• Journal of Astronomy and Space Sciences
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• v.29 no.1
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• pp.11-21
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• 2012

In this paper, the authors introduced a new approach to find the optimal collision avoidance maneuver considering multi threatening objects within short period, while satisfying constraints on the fuel limit and the acceptable collision probability. A preliminary effort in applying a genetic algorithm (GA) to those kinds of problems has also been demonstrated through a simulation study with a simple case problem and various fitness functions. And then, GA is applied to the complex case problem including multi-threatening objects. Two distinct collision avoidance maneuvers are dealt with: the first is in-track direction of collision avoidance maneuver. The second considers radial, in-track, cross-track direction maneuver. The results show that the first case violates the collision probability threshold, while the second case does not violate the threshold with satisfaction of all conditions. Various factors for analyzing and planning the optimal collision avoidance maneuver are also presented.