Editorial: latest trends in bio-inspired medical robotics: structural design, manufacturing, detection, actuate and control

In recent decades, robotic technologies have been largely introduced into different medical applications, such as surgical operation and rehabilitation engineering, to improve the efficiency and quality of medical treatment. However, these robots must generally interact with humans and manipulate their complex structure and internal organs via small openings, which presents a large challenge for current detection, actuation and control strategies (Muscolo and Fiorini, 2023; Sun and Lueth, 2023b). To solve these problems, many researchers have introduced biological inspiration techniques into medical robots. For example, soft snake-shaped robots are used to obtain flexible flexible movements in mini-invasive surgery (Burger-Kahrs et al., 2015; Lin et al., 2024; Cianchetti et al., 2018; Athuri et al., 2020; Sun et al., 2020; Sun and Lueth, 2023a), while exoskeleton robots inspired by insects can provide walking assistance to disabled patients (Shi et al., 2019; Yang et al., 2023; Liao et al., 2023).

In this research subject, we aim to present the latest developments and achievements of bio-inspired technologies to support future research orientations in the field of medical robotics, in particular structural design, modeling, manufacturing, detection, actuation and control. Following the call for participation, seven articles were finally accepted and collected in this research subject.

The first two articles focus on the structural design of robotic systems for medical robots. In the newspaper “A compact motorized final effector for ankle rehabilitation training” by Wu et al. The authors presented the design and development of an ankle rehabilitation robot with a final effector called CEARR to support the amplitude of the rehabilitation of the movement ankle. The CEARR used a bilateral symmetrical structure with three degrees of freedom per side, driven by independent actuators, and has integrated a real -time voluntary control strategy (VTC) using surface electromyography (SEMG) and torque signals to improve rehabilitation outputs. The proposed VTC strategy could be more profitable than algorithms based on the neural network, as it can be executed on a single microcontroller with fewer IT resources. In the newspaper “Optimization and manufacture of programmable fields for mild magnetic robots: a review” by Bacchetti et al. The authors reviewed the current state of the art of programmable magnetic robots, focusing on bio-inspired structural optimization and manufacturing. The article indicated that significant additional developments in programmable magnotic robots could be obtained by increasing the computation power of new optimization methods, combined with progress in calculation resolution, material options and automation of manufacturing methods.

The contribution in “New bio-inspired flexible actuators for exoskeletons with upper joked: design, manufacturing and feasibility study” by Zhang et al. Analysis the design of the actuator for medical robots. In this article, two types of soft actuators have been developed for exoskeletons of the upper limbs: the silicone pneumatic robot inspired by lobster (lily) for the elbow and the pneumatic robot in the shape of a scasted (scasper) for the shoulder. The experimental results have shown that by using the position and severity compensation control mode, an exoskeleton with upper limb equipped with the proposed actuators can stable the desired trajectory and maintain the desired position.

The other two contributions approach the research subject of the design of touch sensors for medical robots. Paper “Validations of various handling strategies of hand objects using a new touch sensor developed for a under-accusary hand” by Singh et al. presented a touch-based tactile sensor, which has been integrated into an under-accompaned prosthetic hand (Prisma Hand II) to carry out a complex handling of objects in hand. Based on the tension value of the tactile sensor, deep learning methods have been developed to calculate the input forces and couples for the manipulation of objects. Paper “Dynamic beach strength sensor with abrassed optical fiber for tissue palpation” by Dawood et al. On the other hand, introduced a variable-stiffness dynamic beach strength sensor based on an abrasive optical fiber, which can be used to provide remote haptic feedback. By adjusting the rigidity of the sensor, the measurement range of the force of touch can be modified.

The last two articles focus on controlling the movement of medical robots. In the newspaper “Integration of computer vision into the control of prosthetic hands with SEMG: preliminary results in the classification of entry” by Wang et al. The authors studied the feasibility of the integration of SEMG signals into visual information to improve the accuracy of the prosthetic hand control. The results have shown that, during the early damage phase, higher precision in the classification of entry models could be obtained with integrated vision data. Based on this knowledge, more vision -based methods could be developed in the future to improve the accuracy of control of myoelectric prosthetic movements. In the newspaper “Adaptive approach for monitoring organic target movements: application to intervention based on robots for prostate cancer” by Smahi et al. The authors presented a robotic system for curiousherapy in the treatment of prostate cancer. Using an in -depth learning framework based on short -term short -term memory networks (LSTM) and convolutional neurons (CNNS) networks to predict the position of the prostate, the proposed system can precisely deliver the radioactive drug to cancer tissue and, therefore, improve the patient’s experience in prostate cancer in prostate cancer.