Analysis of a soft bio-Inspired active actuation model for the design of artificial vocal folds

Phonation results from the passively induced oscillation of the vocal folds in the larynx, creating sound waves that are then articulated by the mouth and nose. Patients undergoing laryngectomy have their vocal folds removed and thus must rely on alternative sources of achieving the desired vibration of artificial vocal folds. Existing solutions, such as voice prostheses and the Electrolarynx, are limited by producing sufficient voice quality, for instance. In this paper, we present a mathematical analysis of a physical model of an active vocal fold prosthesis. The inverse dynamical equation of the system will help to understand whether specific types of soft actuators can produce the required force to generate natural phonations. Hence, this is referred to as the active actuation model. We present the analysis to replicate the vowels /a/, /e/, /i/, and /u/ and voice qualities of vocal fry, modal, falsetto, breathy, pressed, and whispery. These characteristics would be required as a first step to design an artificial vocal folds system. Inverse dynamics is used to identify the required forces to change the glottis area and frequencies to achieve sufficient oscillation of artificial vocal folds. Two types of ionic polymer-metal composite (IPMC) actuators are used to assess their ability to produce these forces and the corresponding activation voltages required. The results of our proposed analysis will enable research into the effects of natural phonation and, further, provide the foundational work for the creation of advanced larynx prostheses

Meshless Simulation of Multi-site Radio Frequency Catheter Ablation through the Fragile Points Method

Computational models for radio frequency catheter ablation (RFCA) of cardiac arrhythmia have been developed and tested in conditions where a single ablation site is considered. However, in reality arrhythmic events are generated at multiple sites which are ablated during treatment. Under such conditions, heat accumulation from several ablations is expected and models should take this effect into account. Moreover, such models are solved using the Finite Element Method which requires a good quality mesh to ensure numerical accuracy. Therefore, clinical application is limited since heat accumulation effects are neglected and numerical accuracy depends on mesh quality. In this work, we propose a novel meshless computational model where tissue heat accumulation from previously ablated sites is taken into account. In this way, we aim to overcome the mesh quality restriction of the Finite Element Method and enable realistic multi-site ablation simulation. We consider a two ablation sites protocol where tissue temperature at the end of the first ablation is used as initial condition for the second ablation. The effect of the time interval between the ablation of the two sites is evaluated. The proposed method demonstrates that previous models that do not account for heat accumulation between ablations may underestimate the tissue heat distribution

Computational Analysis of Balloon Catheter Behaviour at Variable Inflation Levels

Aortic valvuloplasty is a minimally invasive procedure for the dilatation of stenotic aortic valves. Rapid ventricular pacing is an established technique for balloon stabilization during this procedure. However, low cardiac output due to the pacing is one of the inherent risks, which is also associated with several potential complications. This paper proposes a numerical modelling approach to understand the effect of different inflation levels of a valvuloplasty balloon catheter on the positional instability caused by a pulsating blood flow. An unstretched balloon catheter model was crimped into a tri-folded configuration and inflated to several levels. Ten different inflation levels were then tested, and a Fluid-Structure Interaction model was built to solve interactions between the balloon and the blood flow modelled in an idealised aortic arch. Our computational results show that the maximum displacement of the balloon catheter increases with the inflation level, with a small step at around 50% inflation and a sharp increase after reaching 85% inflation. This work represents a substantial progress towards the use of simulations to solve the interactions between a balloon catheter and pulsating blood flow

Soft, stiffness-controllable sensing tip for on-demand force range adjustment with angled force direction identification

Force sensors are essential for measuring and controlling robot-object interactions. However, current force sensors have limited usability in applications such as grasping and palpation, where the range of angled forces changes between tasks. To address this limitation this paper proposes a novel optical-based soft-tipped force sensor capable of adjusting its range and sensitivity through pneumatic modulation. This research describes the sensor’s design and examines the relationship between the internal pressure of the sensor and its sensing range, sensitivity, single-axis force-sensing accuracy, and capability of measuring the angle and magnitude of non-normal forces. Results indicate that by increasing the pressure in the sensor, the sensing range can be increased and the sensitivity decreased. These results demonstrate that the sensor can measure normal forces reliably at each pressure using 4th order fits with root-mean-square error (RMSE) ∈[0.032N0.110N] . Finally, it is also demonstrated that by using a neural network, the sensor can measure the angle and magnitude of non-normal forces with RMSEs on trained variables of 0.0120 Rad for Y-angle ( θY ) measurements, 0.0109 Rad for X-angle ( θX ) measurements, and 0.102 N for force measurements

Editorial: Translational research in medical robotics—challenges and opportunities

In the last few decades, emerging medical technologies and the growing number of commercial robotic platforms have supported diagnosis and treatment of both acute and chronic diseases of the human body, improving the clinical outcome, reducing trauma, shortening the patient recovery time, and increasing postoperative survival rates (Troccaz et al., 2019). Medical robots–including surgical robots, rehabilitation and assistive robots, and hospital automation robots–with improved safety, efficacy and reduced costs, robotic platforms will soon approach a tipping point, moving beyond early adopters to become part of the mainstream clinical practice, defining the future of smart hospitals and home-based patient care. Surgical robots promise to enhance minimally invasive surgery with precise instrument control, intuitive hand-eye coordination, and superior dexterity within tight spaces (Dupont et al., 2021). Rehabilitation robotics facilitates robot-assisted therapy and automated recovery training (Xue et al., 2021). Assistive robots aid individuals with physical limitations, either enhancing or compensating for functions, promoting independence, and lessening the burden on caregivers (Trainum et al., 2023). Additionally, robotic systems can automate hospital operations, spanning service robots aiding clinicians to robots in labs for high-throughput testing (Kwon et al., 2022). These technologies aim to revolutionize healthcare, offering improved patient care and operational efficiency

Soft Robot-Assisted Minimally Invasive Surgery and Interventions: Advances and Outlook

Since the emergence of soft robotics around two decades ago, research interest in the field has escalated at a pace. It is fuelled by the industry's appreciation of the wide range of soft materials available that can be used to create highly dexterous robots with adaptability characteristics far beyond that which can be achieved with rigid component devices. The ability, inherent in soft robots, to compliantly adapt to the environment, has significantly sparked interest from the surgical robotics community. This article provides an in-depth overview of recent progress and outlines the remaining challenges in the development of soft robotics for minimally invasive surgery

Modular integration of a 3 DoF F/T sensor for robotic manipulators

Robot assisted surgery and minimally invasive robotic surgery inherently entail that the hands of the surgeon indirectly interact with the patient tissues and organs even if the operator is out of the affected body. Hence, transferring sensor information from the inside of the patient to the outside of the surgeon may certainly improve the perception of the robotic enduser. To this aim – within the EU framework of the STIFF-FLOP project (STIFFness controllable Flexible and Learnable Manipulator for Surgical Operations), we developed a novel design of miniaturized and magnetic resonance compatible sensors for force and torque real-time measurements in robotic surgery. The sensor design has a hollow shape, whose geometry allows its integration and embedding within snake-like surgical robots and modular devices. According to typical requirements and specifications of a surgical procedure, the sensor operates in a range of force and torque of 0-5 N and 0-5 N⋅cm, respectively. Due to a customized tool and calibration procedure, an error of less than 15% of sensor range can be obtained. This novel transducer may advance force and haptic feedback in robot assisted and minimally invasive surgeries