Human-Machine Interaction Methods for Minimally Invasive Surgical Robotic Arms

Abstract

Minimally invasive surgery has a smaller incision area than traditional open surgery, which can greatly reduce damage to the human body and improve the utilization of medical devices. However, minimally invasive surgery also has disadvantages such as limited flexibility and operational characteristics. The interactive minimally invasive surgical robot system not only improves the stability, safety, and accuracy of minimally invasive surgery but also introduces force feedback in controlling the surgical robot, which is a new development direction in the field of minimally invasive surgery. This paper reviews the development status of interactive minimally invasive surgical robotic systems and key technologies to achieve human-robot interaction and finally provides an outlook and summary of its development. Fuzzy theory and reinforcement learning are introduced into the parameter adjustment process of the variable guide control model, and a human-robot interaction method for minimally invasive surgical robot posture adjustment is proposed.

Computational Analysis and Classification of Hernia Repairs

“…Computational modeling has been utilized to assess the safety and efficacy of hernia mesh and biomaterial-based implants [20]. Artificial intelligence (AI) enables the integration of medical imaging, robotic hernia surgery [21][22][23][24][25], computer-aided hernia repair, and surgeon training. Furthermore, deep learning-based methods have been employed for automated surgical phase recognition [26], which incorporates information about the complexity of intra-abdominal and abdominal wall anatomy.…”