| 研究課題/領域番号 |
19J23169
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| 研究機関 | 名古屋工業大学 |
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研究代表者 |
LY HOANG HIEP 名古屋工業大学, 工学研究科, 特別研究員(DC1)
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| 研究期間 (年度) |
2019-04-25 – 2022-03-31
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| キーワード | tactile display / pneumatic power / shear force / tumor detection / substitutional display / laparoscopic surgery |
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| 研究実績の概要 |
In order to support operation and diagnosis in laparoscopic surgery, apart from tactile sensor, I have developed a ring-type pneumatic tactile display that employed normal indentation substituted for lateral skin stretch to provide normal and shear feedback. Psychophysical experiments were conducted to evaluate how users perceive the provided feedbacks as well as the effectiveness of the tactile display in tumor localization. The experimental results show that the participant could perceive well the provided normal and shear feedbacks. The shear feedback enables the users to enhance their performance in localizing the tumor, and the normal feedback could contribute to ensuring the safety requirements in laparoscopic surgery.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
2: おおむね順調に進展している
理由
I introduced the tactile sensor having normal and shear force measurement function using the acoustic reflection principle for laparoscopic surgery. The sensor performance was accepted in an international journal. I have also developed a pneumatic tactile display that is capable of providing normal and shear feedback for intra-operative tumor detection. The experiment results with the tactile display have been summarized to submit to an international journal.
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| 今後の研究の推進方策 |
The characterization of contact tissue (tumor) such as its shape and its depth might allow surgeons to dissect tumors with a minimum margin in intra-operative surgery. I aim to use the tactile information (both normal and shear force) obtained from the developed tactile sensor to estimate the mentioned characteristics of tissue (tumor). Some artificial phantom tissue with different embedded tumor shapes (or depth) will be prepared for experiments. The tactile data will be collected through simulated tissue palpitation experiments which are conducted by numerous participants. I intend to employ a deep neural network to establish classification model of the tissue characterization based on the collected tactile data. The effectiveness of the model is planned to evaluate by surgeons in practical laparoscopic tissue palpation. The study’s results will be analyzed and summarized to submit to an international journal.
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