Development of an arm robot for neurologic examination training

Noh, Yohan; Ebihara, Kazuki; Terunaga, Chihara; Tokumoto, Mitsuhiro; Okuyama, Isamu; Matsuoka, Yoh; Ishii, Hiroyuki; Takanishi, Atsuo; Hatake, Kazuyuki; Shoji, Satoru

doi:10.1109/iros.2012.6385801

Cited by 19 publications

(7 citation statements)

References 26 publications

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“…For the purpose to improve the flexibility, two non-linear actuator mechanisms are designed. The details can be found in [18]. relationship between the force F and the moving distance x.…”

Section: A Hardware Configurationmentioning

confidence: 99%

Development of a human-like neurologic model to simulate the influences of diseases for neurologic examination training

Noh

Tokumoto

Terunaga

et al. 2013

2013 IEEE International Conference on Robotics and Automation

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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.

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“…For the purpose to improve the flexibility, two non-linear actuator mechanisms are designed. The details can be found in [18]. relationship between the force F and the moving distance x.…”

Section: A Hardware Configurationmentioning

confidence: 99%

Development of a human-like neurologic model to simulate the influences of diseases for neurologic examination training

Noh

Tokumoto

Terunaga

et al. 2013

2013 IEEE International Conference on Robotics and Automation

Self Cite

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“…Therefore, it is necessary to develop an effective care training robot that can mimic the behavior or symptom of the elderly and to enable caregivers to practice elderly care skills. Such a simulator robot can be used for care training on how to take care of elderly persons and for helping therapists to learn how to rehabilitate patients ( Wang et al, 2012 ). In universities or institutes, simulator robots play an important role in teaching students how to evaluate clinical symptoms and diseases related to the muscle and joint ( Diener and Hobbs, 2012 ; Mahoney et al, 2013 ).…”

Section: Introductionmentioning

confidence: 99%

3D Facial Pain Expression for a Care Training Assistant Robot in an Elderly Care Education Environment

2021

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As the elderly population increases, the importance of the caregiver’s role in the quality of life of the elderly has increased. To achieve effective feedback in terms of care and nursing education, it is important to design a robot that can express emotions or feel pain like an actual human through visual-based feedback. This study proposes a care training assistant robot (CaTARo) system with 3D facial pain expression that simulates an elderly person for improving the skills of workers in elderly care. First, in order to develop an accurate and efficient system for elderly care training, this study introduces a fuzzy logic–based care training evaluation method that can calculate the pain level of a robot for giving the feedback. Elderly caregivers and trainees performed the range of motion exercise using the proposed CaTARo. We obtained quantitative data from CaTARo, and the pain level was calculated by combining four key parameters using the fuzzy logic method. Second, we developed a 3D facial avatar for use in CaTARo that is capable of expressing pain based on the UNBC-McMaster Pain Shoulder Archive, and we then generated four pain groups with respect to the pain level. To mimic the conditions for care training with actual humans, we designed the system to provide pain feedback based on the opinions of experts. The pain feedback was expressed in real time by using a projector and a 3D facial mask during care training. The results of the study confirmed the feasibility of utilizing a care training robot with pain expression for elderly care training, and it is concluded that the proposed approach may be used to improve caregiving and nursing skills upon further research.

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“…Takashina et al [13] and Gordon [14] developed a patient simulator for cardiac diseases. Wang et al [15] introduced an arm robot for neurologic examination training and assessed the survey responses from doctors, while Takanobu et al [16] proposed a dental patient robot with questionnaire assessment. Gerling et al [17] designed a physical simulator for clinical prostate examination training and evaluated the training effectiveness in pre-and post-test.…”

Section: Introductionmentioning

confidence: 99%

Necessity and feasibility of care training assistant robot (CaTARo) as shoulder complex joint with multi-DOF in elderly care education

et al. 2020

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As the geriatric population expands, caregivers require more accurate training to handle and care for the elderly. However, students lack methods for acquiring the necessary skill and experience, as well as sufficient opportunities to practice on real human beings. To investigate the necessity and feasibility of care training assistant robots in care education, we developed a simulated robot as a shoulder complex joint with multi-DOF. In this study, five experts with years of experience in elderly care participated in the data-acquisition process, to acquire information on aspects such as the glenohumeral angle, as well as the sterno-clavicular joint and its torque. The experts performed three types of range-of-motion exercises: (i) elevation-depression of sterno-clavicular joint; (ii) extension and flexion of glenohumeral joint; (iii) lateral and medial rotation of glenohumeral joint. The experimental results showed that the quantitative results for all the exercises were significantly different between the experts. Moreover, we observed that even experienced professionals need consistent care education based on quantitative data and feedback. Thus, we confirmed the necessity and feasibility of the care training assistant robot for improving the skills required for elderly care.

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Development of an arm robot for neurologic examination training

Cited by 19 publications

References 26 publications

Development of a human-like neurologic model to simulate the influences of diseases for neurologic examination training

Development of a human-like neurologic model to simulate the influences of diseases for neurologic examination training

3D Facial Pain Expression for a Care Training Assistant Robot in an Elderly Care Education Environment

Necessity and feasibility of care training assistant robot (CaTARo) as shoulder complex joint with multi-DOF in elderly care education

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