A Predictive Approach for Enhancing Accuracy in Remote Robotic Surgery Using Informer Model

Sensors, Год журнала: 2025, Номер 25(10), С. 3067 - 3067

Опубликована: Май 13, 2025

Precise and real-time estimation of the robotic arm's position on patient's side is essential for success remote surgery in Tactile Internet (TI) environments. This paper presents a prediction model based Transformer-based Informer framework accurate efficient estimation, combined with Four-State Hidden Markov Model (4-State HMM) to simulate realistic packet loss scenarios. The proposed approach addresses challenges such as network delays, jitter, ensure reliable precise operation surgical applications. method integrates optimization problem into by embedding constraints energy efficiency, smoothness, robustness its training process using differentiable layer. uses features ProbSparse attention, attention distilling, generative-style decoder focus position-critical while maintaining low computational complexity O(LlogL). evaluated JIGSAWS dataset, achieving accuracy over 90% under various A comparison models TCN, RNN, LSTM demonstrates framework's superior performance handling meeting requirements, making it suitable Internet-enabled surgery.

Язык: Английский

Current perspectives of telesurgery applications among different specialties: first multicentric and multispecialty retrospective study

Journal of Robotic Surgery, Год журнала: 2025, Номер 19(1)

Опубликована: Май 28, 2025

Язык: Английский