Analyzing the diffusion of competitive smart wearable devices: An agent-based multi-dimensional relative agreement model

2022 ◽  
Vol 139 ◽  
pp. 90-105
Author(s):  
Tianyu Zhang ◽  
Peiwu Dong ◽  
Yongchao Zeng ◽  
Yanbing Ju
2021 ◽  
Vol 10 (4) ◽  
pp. 1-25
Author(s):  
Nimi W. S. ◽  
P. Subha Hency Jose ◽  
Jegan R.

This paper presents a brief review on present developments in wearable devices and their importance in healthcare networks. The state-of-the-art system architecture on wearable healthcare devices and their design techniques are reviewed and becomes an essential step towards developing a smart device for various biomedical applications which includes diseases classifications and detection, analyzing nature of the bio signals, vital parameters measurement, and e-health monitoring through noninvasive method. From the review on latest published research papers on medical wearable device and bio signal analysis, it can be concluded that it is more important and very essential to design and develop a smart wearable device in healthcare environment for quality signal acquisition and e-health monitoring which leads to effective measures of multiparameter extractions. This will help the medical practitioners to understand the nature of patient health condition easily by visualizing a quality signal by smart wearable devices.


2020 ◽  
Author(s):  
I-Lin Wang ◽  
Li-I Wang ◽  
Yang Liu ◽  
Shi-Jie Xue ◽  
Rui Hu ◽  
...  

Abstract Background: Visual feedback from the center of pressure (COP) on the benefits of standing quietly remains controversial. The study was to investigate the adaptive effect of COP real-time visual feedback training provided by smart wearable devices on standing in silence. Methods: Thirty healthy female college students were randomly divided into three groups (visual feedback balance training group (VFT), non-visual feedback balance training group (NVFT) and control group (CG)) .Two force plates were used to calculate the coordinates of COP anteroposterior (COPAP) and COP mediolateral (COPML).The motion analysis system is used to calculate the coordinates of the center of mass in two directions. Enhanced visual feedback on the screen in the form of fluctuating in different directions, VFT received real-time visual feedback from Podoon APP for training, the NVFT only performs open eye balance without receiving real-time visual feedback. The CG group did not receive any visual feedback. The training lasted 4 weeks, the training lasts 30 minutes at an interval of 1 days. Results: After four weeks of balance training, the results showed that visual feedback training can improve the stability of human posture control by one leg stance and tandem stance static balance training on VFT intelligent App. The parameters of COPML/AP max displacement, COPML/AP velocity and COP radius and COP area in the VFT were significantly increased (p<0.05).Conclusion: The conclusion shows that COP real-time visual feedback training provided by smart wearable devices can reduce postural sway better and improve body balance ability than general training when standing quietly.


2020 ◽  
Vol 33 ◽  
pp. 4578-4585
Author(s):  
Sandeep Kodam ◽  
Nadimpally Bharathgoud ◽  
Balaji Ramachandran

Author(s):  
Mirto Musci ◽  
Daniele De Martini ◽  
Nicola Blago ◽  
Tullio Facchinetti ◽  
Marco Piastra

10.28945/4746 ◽  
2021 ◽  
Vol 16 ◽  
pp. 173-211
Author(s):  
Ahmad A. Rabaa'i ◽  
Xiaodi Zhu

Aim/Purpose: The aim of this study is to determine the variables which affect the intention to use Near Field Communication (NFC)-enabled smart wearables (e.g., smartwatches, rings, wristbands) payments. Background: Despite the enormous potential of wearable payments, studies investigating the adoption of this technology are scarce. Methodology: This study extends the Technology Acceptance Model (TAM) with four additional variables (Perceived Security, Trust, Perceived Cost, and Attractiveness of Alternatives) to investigate behavioral intentions to adopt wearable payments. The moderating role of gender was also examined. Data collected from 311 Kuwaiti respondents were analyzed using Structural Equation Modeling (SEM) and multi-group analysis (MGA). Contribution: The research model provided in this study may be useful for academics and scholars conducting further research into m-payments adoption, specifically in the case of wearable payments where studies are scarce and still in the nascent stage; hence, addressing the gap in existing literature. Further, this study is the first to have specifically investigated wearable payments in the State of Kuwait; therefore, enriching Kuwaiti context literature. Findings: This study empirically demonstrated that behavioral intention to adopt wearable payments is mainly predicted by attractiveness of alternatives, perceived usefulness, perceived ease of use, perceived security and trust, while the role of perceived cost was found to be insignificant. Recommendations for Practitioners: This study draws attention to the importance of cognitive factors, such as perceived usefulness and ease of use, in inducing users’ behavioral intention to adopt wearable payments. As such, in the case of perceived usefulness, smart wearable devices manufacturers and banks enhance the functionalities and features of these devices, expand on the financial services provided through them, and maintain the availability, performance, effectiveness, and efficiency of these tools. In relation to ease of use, smart wearable devices should be designed with an easy to use, high quality and customizable user interface. The findings of this study demonstrated the influence of trust and perceived security in motivating users to adopt wearable payments, Hence, banks are advised to focus on a relationship based on trust, especially during the early stages of acceptance and adoption of wearable payments. Recommendation for Researchers: The current study validated the role of attractiveness of alternatives, which was never examined in the context of wearable payments. This, in turn, provides a new dimension about a determinant factor considered by customers in predicting their behavioral intention to adopt wearable payments. Impact on Society: This study could be used in other countries to compare and verify the results. Additionally, the research model of this study could also be used to investigate other m-payments methods, such as m-wallets and P2P payments. Future Research: Future studies should investigate the proposed model in a cross-country and cross-cultural perspective with additional economic, environmental, and technological factors. Also, future research may conduct a longitudinal study to explain how temporal changes and usage experience affect users’ behavioral intentions to adopt wearable payments. Finally, while this study included both influencing factors and inhibiting factors, other factors such as social influence, perceived compatibility, personal innovativeness, mobility, and customization could be considered in future research.


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