Smart glasses and telehealth services by professionals in isolated areas in Korea: Acceptability and concerns.

BACKGROUND: Smart glass technology offers remote interaction between health professionals for telehealth, alleviating healthcare disparities in isolated areas. OBJECTIVE: To evaluate the professionals' perceptions of smart glass technology as a tool for telehealth and distance learning. METHOD: This mixed-method study on health professionals in 10 different island areas in Korea involved participants experiencing a smart glass-based telehealth system using the scenario of clinical consultation with remote specialists. A group pre- and post-test design was used to examine the change in attitude and perceived importance among health professionals about using smart glasses in telehealth. RESULTS: Forty-seven participants completed both pre-and post-evaluation of smart glasses. A positive, statistically significant change in participants' perceptions of smart glasses regarding their implications for telehealth and distance learning (p< 0.05) was found. Fifty-one health workers provided feedback on smart glasses, and a majority expressed their expectations of quality care with telehealth using advanced technology. The main concerns were patients' privacy issues and inadequate technology for seamless application. CONCLUSION: The incorporation of smart glass technology offers great potential to enrich telehealth as well as distance learning for unskilled health professionals in isolated areas. Future studies are needed to increase efforts to secure a high level of acceptance for clinical consultation with remote specialists on this newly developed device.

An All-in-One Vehicle Type and License Plate Recognition System Using YOLOv4.

In smart surveillance and urban mobility applications, camera-equipped embedded platforms with deep learning technology have demonstrated applicability and effectiveness in identifying various targets. These use cases can be found in a variety of contexts and locations. It is critical to collect relevant data from the location where the application will be deployed. In this paper, we propose an integrated vehicle type and license plate recognition system using YOLOv4, which consists of vehicle type detection, license plate detection, and license plate character detection to better support the context of Korean vehicles in multilane highway and urban environments. Using our dataset of one to four multilane images, our system detected six vehicle classes and license plates with mAP of 98.0%, 94.0%, 97.1%, and 84.6%, respectively. On our dataset and a publicly available open dataset, our system demonstrated mAP of 99.3% and 99.4% for the detected license plates, respectively. From 4K high-resolution images, our system was able to detect minuscule license plates as small as 100 pixels wide. We believe that our system can be used in densely populated regions to address the high demands for enhanced visual sensitivity in smart cities and Internet-of-Things.

All-in-one encoder/decoder approach for non-destructive identification of 3D-printed objects.

This paper presents an all-in-one encoder/decoder approach for the nondestructive identification of three-dimensional (3D)-printed objects. The proposed method consists of three parts: 3D code insertion, terahertz (THz)-based detection, and code extraction. During code insertion, a relevant one-dimensional (1D) identification code is generated to identify the 3D-printed object. A 3D barcode corresponding to the identification barcode is then generated and inserted into a blank bottom area inside the object's stereolithography (STL) file. For this objective, it is necessary to find an appropriate area of the STL file and to merge the 3D barcode and the model within the STL file. Next the information generated inside the object is extracted by using THz waves that are transmitted and reflected by the output 3D object. Finally, the resulting THz signal from the target object is detected and analyzed to extract the identification information. We implemented and tested the proposed method using a 3D graphic environment and a THz time-domain spectroscopy system. The experimental results indicate that one-dimensional barcodes are useful for identifying 3D-printed objects because they are simple and practical to process. Furthermore, information efficiency can be increased by using an integral fast Fourier transform to identify any code located in areas deeper within the object. As 3D printing is used in various fields, the proposed method is expected to contribute to the acceleration of the distribution of 3D printing empowered by the integration of the internal code insertion and recognition process.

Google Glass-Supported Cooperative Training for Health Professionals: A Case Study Based on Using Remote Desktop Virtual Support.

PURPOSE: Observation of medical trainees' care performance by experts can be extremely helpful for ensuring safety and providing quality care. The advanced technology of smart glasses enables health professionals to video stream their operations to remote supporters for collaboration and cooperation. This study monitored the clinical situation by using smart glasses for remote cooperative training via video streaming and clinical decision-making through simulation based on a scenario of emergency nursing care for patients with arrhythmia. PARTICIPANTS AND METHODS: The clinical operations of bedside trainees, who is Google Glass Enterprise Edition 2(Glass EE2) wearers, were live streamed via their Google Glasses, which were viewed at a remote site by remote supporters via a desktop computer. Data were obtained from 31 nursing students using eight essay questions regarding their experience as desktop-side remote supporters. RESULTS: Most of the participants reported feeling uneasy about identifying clinical situations (84%), patients' condition (72%), and trainees' performance (69%). The current system demonstrated sufficient performance with a satisfactory level of image quality and auditory communication, while network and connectivity are areas that require further improvement. The reported barriers to identifying situations on the remote desktop were predominantly a narrow field of view and motion blur in videos captured by Glass EE2s, and using the customized mirror mode. CONCLUSION: The current commercial Glass EE2 can facilitate enriched communication between remotely located supporters and trainees by sharing live videos and audio during clinical operations. Further improvement of hardware and software user interfaces will ensure better applicability of smart glasses and video streaming functions to clinical practice settings.

Adaptation of Extended Reality Smart Glasses for Core Nursing Skill Training Among Undergraduate Nursing Students: Usability and Feasibility Study.

BACKGROUND: Skill training in nursing education has been highly dependent on self-training because of Korea's high student-faculty ratio. Students tend to have a passive attitude in self-practice, and it is hard to expect effective learning outcomes with traditional checklist-dependent self-practice. Smart glasses have a high potential to assist nursing students with timely information, and a hands-free device does not interrupt performance. OBJECTIVE: This study aimed to develop a smart glass-based nursing skill training program and evaluate its usability and feasibility for the implementation of self-practice. METHODS: We conducted a usability and feasibility study with 30 undergraduate nursing students during a 2-hour open lab for self-practice of core nursing skills, wearing smart glasses for visualized guidance. The usability test was conducted using a 16-item self-reporting questionnaire and 7 open-ended questions. Learning satisfaction was assessed using a 7-item questionnaire. The number of practice sessions was recorded, and perceived competency in core nursing skills was measured before and after the intervention. At the final evaluation, performance accuracy and time consumed for completion were recorded. RESULTS: Smart glass-assisted self-practice of nursing skills was perceived as helpful, convenient, and interesting. Participants reported improved recollection of sequences of skills, and perceived competency was significantly improved. Several issues were raised by participants regarding smart glasses, including small screen size, touch sensors, fogged lenses with masks, heaviness, and heat after a period of time. CONCLUSIONS: Smart glasses have the potential to assist self-practice, providing timely information at students' own paces. Having both hands free from holding a device, participants reported the convenience of learning as they could practice and view the information simultaneously. Further revision correcting reported issues would improve the applicability of smart glasses in other areas of nursing education.

A Non-Touchscreen Tactile Wearable Interface as an Alternative to Touchscreen-Based Wearable Devices.

Current consumer wearable devices such as smartwatches mostly rely on touchscreen-based user interfaces. Even though touch-based user interfaces help smartphone users quickly adapt to wearable devices with touchscreens, there exist several limitations. In this paper, we propose a non-touchscreen tactile wearable interface as an alternative to touchscreens on wearable devices. We designed and implemented a joystick-integrated smartwatch prototype to demonstrate our non-touchscreen tactile wearable interface. We iteratively improved and updated our prototype to improve and polish interaction ideas and prototype integration. To show feasibility of our approach, we compared and contrasted form factors of our prototype against the latest nine commercial smartwatches in terms of their dimensions. We also show response time and accuracy of our wearable interface to discuss our rationale for an alternative and usable wearable UI. With the proposed tactile wearable user interface, we believe our approach may serve as a cohesive single interaction device to enable various cross-device interaction scenarios and applications.

Cross-Device Computation Coordination for Mobile Collocated Interactions with Wearables.

Mobile devices, wearables and Internet-of-Things are crammed into smaller form factors and batteries, yet they encounter demanding applications such as big data analysis, data mining, machine learning, augmented reality and virtual reality. To meet such high demands in the multi-device ecology, multiple devices should communicate collectively to share computation burdens and stay energy-efficient. In this paper, we present a cross-device computation coordination method for scenarios of mobile collocated interactions with wearables. We formally define a cross-device computation coordination problem and propose a method for solving this problem. Lastly, we demonstrate the feasibility of our approach through experiments and exemplar cases using 12 commercial Android devices with varying computation capabilities.