Inziarte-Hidalgo Ibai, Nieto Estela, Roldan Diego, Sorrosal Gorka, Perez-Llano Jesus, Zulueta Ekaitz
Research & Development Department, Aldakin, 31800 Altsasu, Spain.
Ikerlan Technology Research Centre, Basque Research and Technology Alliance (BRTA), 20500 Arrasate-Mondragon, Spain.
Sensors (Basel). 2024 Dec 20;24(24):8150. doi: 10.3390/s24248150.
In recent years, the application of AI has expanded rapidly across various fields. However, it has faced challenges in establishing a foothold in medicine, particularly in invasive medical procedures. Medical algorithms and devices must meet strict regulatory standards before they can be approved for use on humans. Additionally, medical robots are often custom-built, leading to high costs. This paper introduces a cost-effective brain retraction robot designed to perform brain retraction procedures. The robot is trained, specifically the Deep Deterministic Policy Gradient (DDPG) algorithm, using reinforcement learning techniques with a brain contact model, offering a more affordable solution for such delicate tasks.
近年来，人工智能的应用在各个领域迅速扩展。然而，它在医学领域站稳脚跟面临挑战，尤其是在侵入性医疗程序方面。医学算法和设备在被批准用于人体之前必须符合严格的监管标准。此外，医疗机器人通常是定制的，导致成本高昂。本文介绍了一种旨在执行脑回缩程序的高性价比脑回缩机器人。该机器人经过训练，特别是采用深度确定性策略梯度（DDPG）算法，使用带有脑接触模型的强化学习技术，为这类精细任务提供了更经济实惠的解决方案。
