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Satoru Shoji

dblp:39/9968 · DBLP profile ↗
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3ranked-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 · 3Systems, architecture and hardware · 3

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.

Human-computer interaction and pervasive computing
2 papers
Human-robot interaction · 71% Learning and educational technologies · 29%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Medical and health informatics · 50% Bioinformatics and computational biology · 50%
Artificial intelligence
1 paper
Robot manipulation · 100%

Topics — the 7 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Medical and health informatics
medical education
0.212013
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
0.212013
Development of a human-like neurologic model to simulate the influences of diseases for neurologic examination training · ICRA 2013
Human-robot interaction › healthcare robotics
medical robotics
0.112011
Development of the airway management training system WKA-4: For improved high-fidelity reproduction of real patient conditions, and improved tongue and mandible mechanisms · ICRA 2011
Learning and educational technologies › medical training
medical training systems
0.112011
Development of the airway management training system WKA-4: For improved high-fidelity reproduction of real patient conditions, and improved tongue and mandible mechanisms · ICRA 2011
Human-robot interaction › healthcare robotics
patient robot
0.112011
Development of the airway management training system WKA-4: For improved high-fidelity reproduction of real patient conditions, and improved tongue and mandible mechanisms · ICRA 2011
Human-robot interaction › assistive robotics
robot-assisted training
0.012013
Development of a human-like neurologic model to simulate the influences of diseases for neurologic examination training · ICRA 2013
Robotics › Robot manipulation › robot design
mechanism design
0.012011
Development of the airway management training system WKA-4: For improved high-fidelity reproduction of real patient conditions, and improved tongue and mandible mechanisms · ICRA 2011

Methods — techniques the papers use, named apart from their topics

physiological neurological model · 0.3force control · 0.2embedded sensors and actuators · 0.2
YearPublicationVenuePosition
2013 Development of a human-like neurologic model to simulate the influences of diseases for neurologic examination training
abstract
Neurologic 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
ICRA11
2012 Development of an arm robot for neurologic examination training
abstract
Neurologic 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
IROS11
2011 Development of the airway management training system WKA-4: For improved high-fidelity reproduction of real patient conditions, and improved tongue and mandible mechanisms
abstract
In recent years advanced robotic technology has seen more use in the medical field to assist in the development of efficient training systems. Such training systems must fulfill the following criteria: they must provide quantitative information, must simulate the real-world conditions of the task, and assure training effectiveness. We developed Waseda Kyotokagaku Airway series to fulfill all of those requirements. The WKA series we had developed does not consider external appearance such as patient skin, or internal appearance such as the pharynx, larynx, and esophagus. Moreover, the tongue mechanism of the previous system can not precisely measure the force applied by medical devices and cannot simulate muscle stiffness. In addition, the mandible mechanism of the previous system could not adequately reproduce various airway difficulties or apply force control. For these reasons, we propose the WKA-4, which has high-fidelity simulated human anatomy, and we have improved the mechanism over the previous system. We have also attached a lung to the proposed system to improve simulation of the real-world conditions of the task. In this paper, we present how to design several organs with various embedded sensors and actuators, for a conventional patient model with high-fidelity simulated human anatomy. We also present the control system for the WKA-4. Finally, we present a set of experiments carried out using doctors as subjects, and they gave their valuable opinions about our system.
Yohan Noh, Kazuki Ebihara, Masanao Segawa, Kei Sato, Chunbao Wang 0001, Hiroyuki Ishii, Jorge Solis 0001, Atsuo Takanishi, Kazuyuki Hatake, Satoru Shoji
ICRA10