A Multimodal Feedback Sensing System for an Endovascular Surgery Robot
Robot-assisted endovascular surgery (RES) acts as a promising alternative to aid medical cures. To overcome the current limitations of single feedback sensing for surgeons in RES, in this work, a multimodal feedback sensing system integrated with four kinds of feedback (temperature, vibration, haptic, and vision) are developed, fabricated, and tested to provide immersive feedback sensing to surgeons, improve the transparency and safety for operations. A small-sized wearable sensing bracelet (WSB), assembled by Peltier module, vibration motor, and film thermistor, is designed to generate continuous real-time feedback sensing (thermal feedback and vibrating feedback) and measure the temperature of thermal feedback. The haptic interface can offer force feedback. The monitor window is able to provide visual feedback. Besides, a multilevel control strategy for the feedback sensing system is proposed to indicate different surgical conditions. The performance evaluation for three feedback and insertions (in vitro experiments) are carried out to verify the feasibility and repeatability. Insertion results by five subjects demonstrate that proposed multimodal feedback sensing system achieves fast response, immersive feedback, and large repetition capacity. Moreover, benefiting from the inspiration of multimodal feedback sensing, it is suitable to combine more feedback stimulus, even possible to explore newly immersive/spatial feedback sensing for leader-follower robotics.
Authors
- Masahiko Kawanishi (ORCID: https://orcid.org/0000-0001-5961-9252)
- Shuxiang Guo (ORCID: https://orcid.org/0000-0002-0607-9798)
- Xinming Li (ORCID: https://orcid.org/0000-0003-1861-5751)
- Keisuke Suzuki (ORCID: https://orcid.org/0000-0001-7942-7610)
Institutions
- Kagawa University (JP)
- Southern University of Science and Technology (CN)
- Takamatsu University (JP)
- Guangzhou Maritime College (CN)
- Guangdong Institute of Intelligent Manufacturing (CN)
- Shenzhen Technology University (CN)
- South China University of Technology (CN)
Publication Details
- Journal
- IEEE Sensors Journal
- Published
- 2025-07-14
- DOI
- https://doi.org/10.1109/jsen.2025.3587324
- Primary Topic
- Soft Robotics and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00