Demo Data from SIGIR 2026 / reviewers in the wild / expert
Terunaga Chihara
dblp:87/11183
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2013
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2Systems, architecture and hardware · 2
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Medical and health informatics · 50% Bioinformatics and computational biology · 50% | |
| Human-computer interaction and pervasive computing
1 paper |
Human-robot interaction · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Medical and health informatics
medical education |
0.2 | 1 | 2013 | Development of a human-like neurologic model to simulate the influences of diseases for neurologic examination training · ICRA 2013 |
Bioinformatics and computational biology › systems biology
physiological modeling |
0.2 | 1 | 2013 | Development of a human-like neurologic model to simulate the influences of diseases for neurologic examination training · ICRA 2013 |
Human-robot interaction › assistive robotics
robot-assisted training |
0.0 | 1 | 2013 | Development of a human-like neurologic model to simulate the influences of diseases for neurologic examination training · ICRA 2013 |
Methods — techniques the papers use, named apart from their topics
physiological neurological model · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2013 | Development of a human-like neurologic model to simulate the influences of diseases for neurologic examination trainingabstractNeurologic examination procedures require not only abundant knowledge but also prominent skills. During medical education and training, several methods will be put to use such as watching video, reading books, making use of the simulated patient (SP), and so on. These can help medical staffs, especially novices, to master the skills and accumulate experiences. To make up for the drawbacks of the above methods, such as lack of active interactions, limitation of multi-symptom reproductions, etc, the medical training simulators have been developed to improve training effectiveness. However, most of these simulators only mimic the symptoms. They have no the abilities to show the pathology of diseases. This limits the training effectiveness. In this paper, we propose an elbow robot named WKE-1(Waseda Kyotokagaku Elbow Robot No.1) for neurologic examination training as one part of the whole body patient robot named WKP (Waseda Kyotokagaku Patient). In this robot, we simulate various symptoms occurring during the examination of elbow force, biceps tendon reflex, involuntary action, and also make a physiological neurological model to simulate the pathology of the nervous system. Taking advantage of this robot, the trainee can get a systematic training on both the skills and knowledge. Finally, we take a set of experiments to verify our proposed mechanism and system. The experimental results lead to the consideration that the approach is worth following in further research. Chunbao Wang 0001, Yohan Noh, Mitsuhiro Tokumoto, Terunaga Chihara, Yusuke Matsuoka, Hiroyuki Ishii, Salvatore Sessa 0001, Massimiliano Zecca, Atsuo Takanishi, Kazuyuki Hatake, Satoru Shoji |
ICRA | 4 |
| 2012 | Development of an arm robot for neurologic examination trainingabstractNeurologic examination takes an important role in diagnosis of the nerve system diseases. Neurologic medical staffs, especially the novices, need to be trained on this skill. There are many methodologies which can help to accumulate experiences, such as watching video, reading books, making use of the simulated patient (SP), and so on. However, the best way is to practice on the real patient. All the above methods have their own drawbacks such as lack of active interactions, limitation of multi-symptoms' reproducing, etc. To improve the training effectiveness, an arm robot is proposed in this paper for neurologic examination training as one part of the whole body patient robot named Waseda Kyotokagaku Patient (WKP). In this robot, various symptoms of the elbow force, biceps tendon reflex, involuntary action, and so on, are simulated and shown to the trainee. Finally, a set of experiments was carried out to verify our proposed mechanism and control system. Three neurologists with over 30 years' experience were invited to show their opinions on the reproductions of patients' symptoms, and to discuss the results. The effectiveness of this system was confirmed. The experimental results lead to the consideration that the approach is worth following in further research. Chunbao Wang 0001, Yohan Noh, Kazuki Ebihara, Terunaga Chihara, Mitsuhiro Tokumoto, Isamu Okuyama, Yusuke Matsuoka, Hiroyuki Ishii, Atsuo Takanishi, Kazuyuki Hatake, Satoru Shoji |
IROS | 4 |