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http://elartu.tntu.edu.ua/handle/lib/46628
Título: | Smart Prosthetics in Surgery: AI-Driven Tactile Feedback Using Piezoelectric Sensors |
Authors: | Tymkiv, Pavlo Kłos-Witkowska, Aleksandra Bahrii-Zaiats, Oksana Kovalyk, Serhii |
Bibliographic description (Ukraine): | Pavlo Tymkiv, Aleksandra Kłos-Witkowska, Oksana Bahrii-Zaiats, Serhii Kovalyk. Smart Prosthetics in Surgery: AI-Driven Tactile Feedback Using Piezoelectric Sensors. Proceedings of the 1st International Workshop on Bioinformatics and Applied Information Technologies (BAIT 2024) Zboriv, Ukraine, October 02-04, 2024. Vol.3842. P.208-217. ISSN 1613-0073. |
Data de edición: | 2-Oct-2024 |
Date of entry: | 16-Dec-2024 |
Country (code): | UA |
Place of the edition/event: | Zboriv,Ukraine |
Palabras chave: | Robotic surgery robotic manipulator arm tactile feedback precision control AI |
Page range: | 208-217 |
Resumo: | This paper explores the innovative application of piezoelectric sensors in robotic prosthetics for surgical systems, emphasizing their potential to enhance tactile feedback during delicate procedures. Piezoelectric sensors can efficiently convert mechanical pressure and vibrations into electrical signals, offering a crucial means for surgeons to feel and interpret force, texture, and other surface characteristics in real time. The ability to generate and transmit tactile feedback through cloud-based systems allows for the creation of a database of tactile patterns, enabling automated recognition of specific tactile interactions during surgery. The integration of artificial intelligence (AI) further enhances the system by learning from collected data, predicting future interactions, and optimizing pattern recognition. Additionally, combining piezoelectric sensors with other types of sensory inputs, such as temperature and strain gauges, allows for a multi-dimensional feedback system. This results in an immersive experience, granting surgeons precise control over their robotic tools. The continuous improvement of these systems through AI and data collection holds vast potential for future developments in robotic surgery, leading to more accurate, safer procedures and better patient outcomes. This research underscores the transformative impact of AI-driven, multi-sensory feedback systems in enhancing the capabilities of robotic-assisted surgeries. |
URI: | http://elartu.tntu.edu.ua/handle/lib/46628 |
ISSN: | 1613-0073 |
References (International): | [1] Kim, K., Cho, K., Lee, S., Park, S., & Lee, J. (2021). "Tactile Feedback in Robotic Surgery: Emerging Technologies and Applications." Annual Review of Biomedical Engineering, 23, 145-169. [2] Wang, J., He, Y., Li, T., Zhao, X., & Liu, J. (2023). "Integration of Haptic Feedback and AI for Advanced Prosthetic Hand Control." Frontiers in Neuroscience, 17, 928202. [3] Pfeiffer, F., & Bruns, T. M. (2022). "Multi-modal Sensor Systems for Robotic Surgery: A Comprehensive Review." Journal of Medical Robotics Research, 7(1), 2150008. [4] Clemente, F., Dosen, S., Markovic, M., Farina, D., & Cipriani, C. (2020). "Exploiting Sensory-Motor Interactions in Myoelectric Prostheses with Neuromorphic Feedback: A Review." IEEE Transactions on Medical Robotics and Bionics, 2(3), 121-130. [5] Gonzalez et al. (2020). Advanced Prosthetics with Tactile Feedback: A Review. Frontiers in Robotics and AI, 7, 33-45. [6] Cutkosky et al. (2019). Tactile Sensors for Robotic Surgery: A Review. Journal of Medical Robotics, 36(4), 1023-1042. [7] Khvostivskyy M., Osukhivska H., Khvostivska L., Lobur T., Velychko D., Lupenko S., Hovorushchenko T. Mathematical modelling of daily computer network traffic. The 1st International Workshop on Information Technologies: Theoretical and Applied Problems, ITTAP 2021. CEUR Workshop Proceedings. Ternopil, Ukraine, November 16-18, 2021. Vol. 3039. P.107-111. ISSN 1613-0073. [8] Khvostivska L., Khvostivskyi M., Dediv I. Mathematical, algorithmic and software support for signals wavelet detection in electronic communications. Proceedings of the 2nd International Workshop on Computer Information Technologies in Industry [9] Tymkiv, P., Kłos-Witkowska, A., Babiak, Z., Koshelyuk, V., & Holovko, A. (2024). Robotic Arm Concept for Surgery: Integrating of 3D Printing and IoT Technologies. Proceedings of the 2nd International Workshop on Computer Information Technologies in Industry 4.0 (CITI 2024). CEUR Workshop Proceedings, 3742, 249-260. [10] Martsenyuk, V., Klos-Witkowska, A., Sverstiuk, A., Bahrii-Zaiats O., Bernas, M., Witos, K. Intelligent big data system based on scientific machine learning of cyber-physical systems of medical and biological processes. CEUR Workshop Proceedings, 2021, 2864, pp. 34–48. [11] Zhukovskyy, V., Shatnyi, S., Zhukovska, N., & Sverstiuk, A. (2021). Neural Network Clustering Technology for Cartographic Images Recognition. In IEEE EUROCON 2021 - 19th International Conference on Smart Technologies. IEEE EUROCON 2021 - 19th International Conference on Smart Technologies. IEEE. https://doi.org/10.1109/eurocon52738.2021.9535544 [12] Oksana Dozorska, Evhenia Yavorska, Vasil Dozorskyi, Vyacheslav Nykytyuk, Leonid Dediv (2020). The Method of Selection and Pre-processing of Electromyographic Signals for Bio-controlled Prosthetic of Hand. Proc. of the 2020 IEEE 15th International Conference on Computer Sciences and Information Technologies (CSIT), 23-26 September 2020, (pp.188–192). Lviv-Zbarazh, Ukraine. |
Content type: | Conference Abstract |
Aparece nas Coleccións | Наукові публікації працівників кафедри біотехнічних систем |
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