Skill of Eye-Hand Coordination in Calligraphy - Difference of Skill of Hand-Eye Coordination between Expert and Novice -

A system that can simultaneously measure the movement of a brush tip and the eye-gaze position during a calligraphy task has been developed. The system consisted of a device to measure the location of a brush tip and an eye tracker. Using this system, the skill of hand-eye coordination was measured for an expert and novices. It has been clarified that an expert of calligraphy distributes the eye-gaze over a wider area and gazes in advance a part that should be written next. In other words, an expert does not gaze at the brush tip but at the part that should be written at the next stage

Study of Sharing Patient Information by Nurses Between Inpatient and Outpatient Wards in Japan

Studies in Health Technology and Informatics Volume 284Shortening hospital stays increases communication needs between nurses in inpatient and outpatient wards. Smooth information sharing is required to reduce the workload of nurses and improve the quality of patient care. However, electronic medical records (EMR) system does not have sufficient functions to support information sharing between wards, because EMR has been developed mainly for recording. This study led to three improvements; unified communication tool, common patient list linked to EMR, and outpatient nursing diagnosis

Visualizing the Cascade Effect of Redesigning Features in an EMR System

Electronic Medical Record (EMR) systems are complex systems with interdependent features. Redesigning one feature of the system can create a cascade effect affecting the other features. By calculating the cascade effect, the designers can understand how each individual feature could be affected. This understanding allows them to maximize the positive effects and avoid negative consequences of their redesign activities. To understand the cascade effect, the designers can look at their computations’ results; a task that becomes more difficult when the number of features grows. To reduce their task load, we propose a tool for visualizing the cascade effect of redesigning features in an EMR system. Our preliminary evaluation with six graduate students shows that visualizing the cascade effect reduces the task load and slightly improves their performance when analyzing the cascade effect. Ways for improving the tool include (i) showing the computation results within the visualization, and (ii) allowing the designers to compare the cascade effect generated by redesigning different features

Recognition of Instrument Passing and Group Attention for Understanding Intraoperative State of Surgical Team

Appropriate evaluation of the intraoperative state of a surgical team is essential for the improvement of teamwork and hence a safe surgical environment. Traditional methods to evaluate intraoperative team states such as interview and self-check questionnaire on each surgical team member often require human efforts, which are time-consuming and can be biased by individual recall. One effective solution is to analyze the surgical video and track the important team activities, such as whether the members are complying with the surgical procedure or are being distracted by unexpected events. However, due to the complexity of the situations in an operating room, identifying the team activities without any human effort remains challenging. In this work, we propose a novel approach that automatically recognizes and quantifies intraoperative activities from surgery videos. As a first step, we focus on recognizing two activities that especially involve multiple individuals: (a) passing of clean-packaged surgery instruments which is a representative interaction between the surgical technologists such as the circulating nurse and scrub nurse, and (b) group attention that may be attracted by unexpected events. We record surgical videos as input, and apply pose estimation and particle filters to extract individual's face orientation, body orientation, and arm raise. These results coupled with individual IDs are then sent to an estimation model that provides the probability of each target activity. Simultaneously, a person model is generated and bound to each individual, which describes all the involved activities along the timeline. We tested our method using videos of simulated activities. The results showed that the system was able to recognize instrument passing and group attention with F1 = 0.95 and F1 = 0.66, respectively. We also implemented a system with an interface that automatically annotated intraoperative activities along the video timeline, and invited feedback from surgical technologists. The results suggest that the quantified and visualized activities can help improve understanding of the intraoperative state of the surgical team

Design Elements of Pervasive Games for Elderly Players: A Social Interaction Study Case

We present the design process and evaluation of a pervasive, location-based mobile game created to act as an experiment system and allow evaluation of how different design elements can influence player behaviour, using social interaction as a study case. A feasibility study with a group of community dwelling elderly volunteers from the city of Kyoto, Japan, was performed to evaluate the system. Results showed that the choice of theme and overall design of game was adequate, and that elderly people could understand the game rules and their goals while playing. Points of improvement included reducing the complexity of game controls and changing social interaction mechanics to account for situations when there are only a few players active or players are too far apart

Handheld Guides in Inspection Tasks : Augmented Reality versus Picture

Inspection tasks focus on observation of the environment and are required in many industrial domains. Inspectors usually execute these tasks by using a guide such as a paper manual, and directly observing the environment. The effort required to match the information in a guide with the information in an environment and the constant gaze shifts required between the two can severely lower the work efficiency of inspector in performing his/her tasks. Augmented reality (AR) allows the information in a guide to be overlaid directly on an environment. This can decrease the amount of effort required for information matching, thus increasing work efficiency. AR guides on head-mounted displays (HMDs) have been shown to increase efficiency. Handheld AR (HAR) is not as efficient as HMD-AR in terms of manipulability, but is more practical and features better information input and sharing capabilities. In this study, we compared two handheld guides: an AR interface that shows 3D registered annotations, that is, annotations having a fixed 3D position in the AR environment, and a non-AR picture interface that displays non-registered annotations on static images. We focused on inspection tasks that involve high information density and require the user to move, as well as to perform several viewpoint alignments. The results of our comparative evaluation showed that use of the AR interface resulted in lower task completion times, fewer errors, fewer gaze shifts, and a lower subjective workload. We are the first to present findings of a comparative study of an HAR and a picture interface when used in tasks that require the user to move and execute viewpoint alignments, focusing only on direct observation. Our findings can be useful for AR practitioners and psychology researchers

Promoting Physical Activity in Japanese Older Adults Using a Social Pervasive Game: Randomized Controlled Trial

Background: Pervasive games aim to create more fun and engaging experiences by mixing elements from the real world into the game world. Because they intermingle with players’ lives and naturally promote more casual gameplay, they could be a powerful strategy to stimulate physical activity among older adults. However, to use these games more effectively, it is necessary to understand how design elements of the game affect player behavior. Objective: The aim of this study was to evaluate how the presence of a specific design element, namely social interaction, would affect levels of physical activity. Methods: Participants were recruited offline and randomly assigned to control and intervention groups in a single-blind design. Over 4 weeks, two variations of the same pervasive game were compared: with social interaction (intervention group) and with no social interaction (control group). In both versions, players had to walk to physical locations and collect virtual cards, but the social interaction version allowed people to collaborate to obtain more cards. Changes in the weekly step counts were used to evaluate the effect on each group, and the number of places visited was used as an indicator of play activity. Results: A total of 20 participants were recruited (no social interaction group, n=10; social interaction group, n=10); 18 participants remained active until the end of the study (no social interaction group, n=9; social interaction group, n=9). Step counts during the first week were used as the baseline level of physical activity (no social interaction group: mean 46, 697.2, SE 7905.4; social interaction group: mean 45, 967.3, SE 8260.7). For the subsequent weeks, changes to individual baseline values (absolute/proportional) for the no social interaction group were as follows: 1583.3 (SE 3108.3)/4.6% (SE 7.2%) (week 2), 591.5 (SE 2414.5)/2.4% (SE 4.7%) (week 3), and −1041.8 (SE 1992.7)/0.6% (SE 4.4%) (week 4). For the social interaction group, changes to individual baseline values were as follows: 11520.0 (SE 3941.5)/28.0% (SE 8.7%) (week 2), 9567.3 (SE 2631.5)/23.0% (SE 5.1%) (week 3), and 7648.7 (SE 3900.9)/13.9% (SE 8.0%) (week 4). The result of the analysis of the group effect was significant (absolute change: η2=0.31, P=.04; proportional change: η2=0.30, P=.03). Correlations between both absolute and proportional change and the play activity were significant (absolute change: r=0.59, 95% CI 0.32 to 0.77; proportional change: r=0.39, 95% CI 0.08 to 0.64). Conclusions: The presence of social interaction design elements in pervasive games appears to have a positive effect on levels of physical activity. Trial Registration: Japan Medical Association Clinical Trial Registration Number JMA-IIA00314; https://tinyurl.com/y5nh6ylr (Archived by WebCite at http://www.webcitation.org/761a6MVAy

Integrating Preprocessing Operations into Deep Learning Model: Case Study of Posttreatment Visual Acuity Prediction

Designing a deep neural network model that integrates clinical images with other electronic medical records entails various preprocessing operations. Preprocessing of clinical images often requires trimming of parts of the lesions shown in the images, whereas preprocessing of other electronic medical records requires vectorization of these records; for example, patient age is often converted into a categorical vector of 10-year intervals. Although these preprocessing operations are critical to the performance of the classification model, there is no guarantee that the preprocessing step chosen is appropriate for model training. The ability to integrate these preprocessing operations into a deep neural network model and to train the model, including the preprocessing operations, can help design a multi-modal medical classification model. This study proposes integration layers of preprocessing, both for clinical images and electronic medical records, in deep neural network models. Preprocessing of clinical images is realized by a vision transformer layer that selectively adopts the parts of the images requiring attention. The preprocessing of other medical electrical records is performed by adopting full-connection layers and normalizing these layers. These proposed preprocessing-integrated layers were verified using a posttreatment visual acuity prediction task in ophthalmology as a case study. This prediction task requires clinical images as well as patient profile data corresponding to each patient's posttreatment logMAR visual acuity. The performance of a heuristically designed prediction model was compared with the performance of the prediction model that includes the proposed preprocessing integration layers. The mean square errors between predicted and correct results were 0.051 for the heuristic model and 0.054 for the proposed model. Experimental results showed that the proposed model utilizing preprocessing integration layers achieved nearly the same performance as the heuristically designed model

Smart lighting can change our life style

期間: 2014年8月4日講義場所: 情報科学研究科大講義室(L1)講演者所属: 本学情報科学研究科インタラクティブメディア設計学研究室助教Symposium: Making Augmented Reality Real Presentation-