Transseptal puncture (TSP) is a prerequisite for left atrial catheter ablation for atrial fibrillation, requiring access from the right side of the heart. It is a demanding procedural step associated with complications, including inadvertent puncturing and application of large forces on the tissue wall. Robotic systems have shown great potential to overcome such challenges by introducing force-sensing capabilities and increased precision and localization accuracy. Therefore, this work introduces the design and development of a novel robotic system developed to perform TSP. We integrated optoelectronic sensors into the tools' fixtures, measuring tissue contact and puncture forces along one axis. The novelty of this design is in the system's ability to manipulate a Brockenbrough (BRK) needle and dilator-sheath simultaneously and measure tissue contact and puncture forces. In performing puncture experiments on anthropomorphic tissue models, an average puncture force of 3.97 ± 0.45 N (1SD) was established - similar to the force reported in literature on the manual procedure. This research highlights the potential for improving patient safety by enforcing force constraints, paving the way to more automated and safer TSP.

This paper demonstrates a working prototype for shape sensing using miniature optoelectronic sensors integrated into a chain of rotational links. Wearable sensors for rehabilitation, prosthetics and robotics must be lightweight, miniature, and compact to allow comfortable range of motion without obstruction, and therefore, the integrated network of sensors and hardware must be adapted to this. The sensing principle is based on light intensity modulation using a curvature varying reflector. The modular sensing configuration design offers a low-cost, miniaturized approach to shape sensing, compatible in clinical applications. A prototype is constructed, and calibration is carried out. Shape sensing estimation is evaluated to assess accuracy. A four-link rotational chain prototype shows average estimation errors of 2.4° for shape sensing compared to an inertial measurement unit.

Measuring forces and torques applied to tools of unconventional shapes can be challenging due to difficulties in connecting commercially available force/torque sensors. We propose an innovative, customizable six-axis force/torque sensor which can be clamped around a tool or end-effector to minimize the proximity between tool tip and sensor structure. The sensor is fabricated using 3d printing technology and consists of two pieces which together form an 8-legged Stewart platform. Each leg is designed as a cantilever beam to allow for a measurable displacement under an external load. The displacements of the legs are measured with 8 light intensity-based optoelectronic sensors, which exhibit high sensitivities and low noise levels without the need for external amplification circuitry. A customized printed circuit board and peripheral hardware are proposed to allow for efficient analog-to-digital conversion of the force/torque measurement. A calibration process is proposed which makes use ofa commercial ATI Mini40 sensor and custom hardware to allow for fast calibration routines. Finally, the calibrated sensor design is compared to the ATI Mini40 sensor by measuring sequences of forces and torques, and the maximum errors of force/torque components (Fx, Fy, Fz, Mx, My, Mz) are 16.3%, 20.0%, 27.5%, 20.5%, 21.6%, 14.9% respectively.

Many modern roboticists take inspiration from biology to create novel robotic structures, including those that are modeled after the octopus. This paper advances this trend by creating soft robots modeling the complex motion patterns of octopus tentacles employing a bio-mimetic approach. The proposed octopus robot is entirely made from soft material and uses a novel fluidic actuation mechanism that allows the robot to advance forward, change directions and rotate around its primary axis. The paper presents the robot's design and fabrication process. An experimental study is conducted showing the feasibility of the proposed robot and actuation mechanism.

The constantly increasing amount of machines operating in the vicinity of humans makes it necessary to rethink the design approach for such machines to ensure that they are safe when interacting with humans. Traditional mechanisms are rigid and heavy and as such considered unsuitable, even dangerous when a controlled physical contact with humans is desired. A huge improvement in terms of safe human-robot interaction has been achieved by a radically new approach to robotics - soft material robotics. These new robots are made of compliant materials that render them safe when compared to the conventional rigid-link robots. This undeniable advantage of compliance and softness is paired with a number of drawbacks. One of them is that a complex and sophisticated controller is required to move a soft robot into the desired positions or along a desired trajectory, especially with external forces being present. In this paper we propose an improved soft fluidic rotary actuator composed of silicone rubber and fiber-based reinforcement. The actuator is cheap and easily manufactured providing near linear actuation properties when compared to pneumatic actuators presented elsewhere. The paper presents the actuator design, manufacturing process and a mathematical model of the actuator behavior as well as an experimental validation of the model. Four different actuator types are compared including a square-shaped and three differently reinforced cylindrical actuators.

A novel three axis force sensor, based on magnetic flux measurements, was used in the fingers of a gripper. The force sensor uses three Hall Effect sensors orthogonally placed at the base of a hemisphere made of silicon rubber. A neodymium permanent magnet was inside the hemisphere. When a force was applied to the perimeter of hemisphere, it compressed the hemisphere displacing the magnet. This displacement caused change in the magnetic field around the Hall-effect sensors. By analysing these changes, we calculated the force in three directions using a lookup table. This sensor can be used in robot grippers to manipulate objects dexterously with tactile feedback. The cheap construction, robustness and reliability are few advantages of this sensor for it to be used in industrial applications. The sensor design, simulation and its characterization are presented in this work. Furthermore, as an application, a peg in a hole experiment was carried out to present the ability of the sensors to be used in robot grippers for manipulation tasks.

This work investigates the applicability of stiffness-based modelling in soft robotics manipulation. The methodology is introduced and applied to model a soft robotics manipulator as single 3d Timoshenko beam element. The model is then utilized to solve the forward kinematics problem for the manipulator. The algorithm is validated comparing the simulated deflection with the deflection of the physical manipulator for two defined pressure sequences. It is shown that the model behaves in a highly similar fashion in comparison to the manipulator. For both trajectories the maximum position error is close to 6 mm while the error in orientation not more than 18°. The methodology as described in this work reveals great applicability to the field of soft robots being limited only by the stiffness matrix assembly for the given system. Implementations of inverse kinematics and the effects of external force applications are effectively integrable in the described theory.

This paper presents a methodology for the development of a multi-axis force/torque sensor based on optoelectronic technology. The advantages of using this sensing principle are the low manufacturing costs, the simple fabrication, and the immunity to electrical noise. The force/ torque sensor makes use of six optical sensors: each sensor measures the displacement of a reflective surface that moves integrally with a simply-supported beam. The proposed mechanical structure allows for a variety of shapes on the mechanical structure to be easily adaptable to many robot applications. In this paper, we present a five-axis force/torque sensor based on this optoelectronic principle. To measure force/torque components, two identical three-DoF force/torque sensor structures (comprised of three beams) are mounted on top of each other. Photo sensors and mirrors are fixed inside the structure to measure the six beam deflections. In this paper, we describe the sensor structure, design, fabrication, calibration, and verify our sensor development methodology.

This paper proposes a soft, inflatable manipulator that is antagonistically actuated by tendons and pneumatics. The combination of the two actuation mechanisms in this antagonistic robot structure is inspired by the octopus which uses its longitudinal and transversal muscles to steer, elongate, shrink and also stiffen its continuum arms. By “activating” its antagonistic muscle groups at the same time, the octopus can achieve multiple motion patterns as well as stiffen their arms. Being organized in a similar fashion, our robot manipulator uses, on the one hand, pneumatic actuation and, on the other hand, tendon-based actuation - one opposing the other, achieving an overall antagonistic actuation framework. Controlling the pressure inside the robot while at the same time controlling the tendons' displacements, the robot can be moved into a wide range of configurations while simultaneously controlling the arm's stiffness. This paper builds on earlier work by the authors: Here, we present a new conic-shaped manipulator structure and the control architecture. Using a constant curvature model, we have derived an approach suitable for controlling the robot manipulator. The manipulator's reachable workspace is analyzed and proof-of-concept experiments were conducted to show the robot's stiffness control and motion abilities.

Materials and textures identification is a desired ability for robots. Developing such systems require tactile sensors that have enough sensitivity and spatial resolution, and the computational intelligence to meaningfully interpret sensor data. This paper introduces a texture classification algorithm utilizing support vector machine (SVM) classifier. Data taken from a novel three axis tactile sensor that utilize magnetic flux measurements for transduction was used to obtain the three dimensional tactile data. Frobenius norm calculated from the covariance matrix of the above data and the mean values of the three dimensional sensor data were used as features. Palpation velocity and small vertical load variances had minimum influence on the proposed algorithm. We have compared this algorithm with two other classification methods. They are: classify using the feature spatial period that is calculated from principal frequencies of the textures/material, and classify using neural network classifier with special properties of each material's tactile signals as features. For eight classes of material, the proposed algorithm performed faster and more accurately than the comparators when the scanning velocity and the vertical load varied.

This paper presents a highly compact fibre-optic system based on light intensity modulation for multi-segment flex sensing in pliable robot arms, e.g., articulated surgical instruments. This fibre-optic arrangement is 7.5 mm in diameter and is comprised of a two-segment flexible and stretchable Steiner chain arm section with twelve housings at the distal side which accommodates passive cables. The displacement of each cable will be used to determine the bending. This Steiner chain section is followed by a basal rigid fibre-optic sensing unit integrated with a low-friction retractable distance modulation array which couples the motion of the passive cables with light-emitting optical fibres. The low-friction retractable distance modulation array uses steel spring-needle double sliders to reduce the hysteresis and to recover reference sensor values when the arm returns to its original straight configuration. The U-shape loopback design of the optical fibres allows integration of all electronics away from the sensing site. The experimental results indicate a maximum bending angle error of 6° in one individual segment of the two-segment arm with respect to reference angle values calculated from camera images.

To efficiently explore a surface using the sense of touch, a novel contact sensing finger was created and a surface following control algorithm for the finger was devised. Based on the accurate estimation of contact locations, and the direction and magnitude of the normal and tangential forces, the finger can robustly and rapidly follow surfaces with large change in curvature while maintaining a desired constant normal force. In this paper, the design and testing of the contact sensing finger are presented and the control algorithm for surface contour following is proposed and validated using objects with different shapes and surface materials. The results demonstrate that using the developed finger and the control algorithm, a surface can be efficiently explored with rapid sliding speed. To demonstrate the potential applications of the proposed approach, the friction properties of an explored object surface are computed and, for a known object, its pose is estimated.

This paper presents an innovative approach of utilising visual feedback to determine physical interaction forces with soft tissue during Minimally Invasive Surgery (MIS). This novel force sensing device is composed of a linear retractable mechanism and a spherical visual feature. The sensor mechanism can be adapted to endoscopic cameras used in MIS. As the distance between the camera and feature varies due to the sliding joint, interaction forces with anatomical surfaces can be computed based on the visual appearance of the feature in the image. Hence, this device allows the measurement of forces without introducing new stand-alone sensors. A mathematical model was derived based on validation data tests and preliminary experiments were conducted to verify the model's accuracy. Experimental results confirm the effectiveness of our vision based approach.

This paper introduces an optical based three axis force sensor which can be integrated with the robot arm of the EU project STIFF-FLOP (STIFFness controllable Flexible and Learnable Manipulator for Surgical Operations) in order to measure applied external forces. The structure of the STIFF-FLOP arm is free of metal components and electric circuits and, hence, is inherently safe near patients during surgical operations. In addition, this feature makes the performance of this sensing system immune against strong magnetic fields inside magnetic resonance (MR) imaging scanners. The hollow structure of the sensor allows the implementation of distributed actuation and sensing along the body of the manipulator. In this paper, we describe the design and calibration procedure of the proposed three axis optics-based force sensor. The experimental results confirm the effectiveness of our optical sensing approach and its applicability to determine the force and momentum components during the physical interaction of the robot arm with its environment.

Robotic manipulators for Robot-assisted Minimally Invasive Surgery (RMIS) pass through small incisions into the patient's body and interact with soft internal organs. The performance of traditional robotic manipulators such as the da Vinci Robotic System is limited due to insufficient flexibility of the manipulator and lack of haptic feedback. Modern surgical manipulators have taken inspiration from biology e.g. snakes or the octopus. In order for such soft and flexible arms to reconfigure itself and to control its pose with respect to organs as well as to provide haptic feedback to the surgeon, tactile sensors can be integrated with the robot's flexible structure. The work presented here takes inspiration from another area of biology: cucumber tendrils have shown to be ideal tactile sensors for the plant that they are associated with providing useful environmental information during the plant's growth. Incorporating the sensing principles of cucumber tendrils, we have created miniature sensing elements that can be distributed across the surface of soft manipulators to form a sensor network capable of acquire tactile information. Each sensing element is a retractable hemispherical tactile measuring applied pressure. The actual sensing principle chosen for each tactile makes use of optic fibres that transfer light signals modulated by the applied pressure from the sensing element to the proximal end of the robot arm. In this paper, we describe the design and structure of the sensor system, the results of an analysis using Finite Element Modeling in ABAQUS as well as sensor calibration and experimental results. Due to the simple structure of the proposed tactile sensor element, it is miniaturisable and suitable for MIS. An important contribution of this work is that the developed sensor system can be ”loosely” integrated with a soft arm effectively operating independently of the arm and without affecting the arm's motion during bending or elongation.

Neurologic examination procedures require not only abundant knowledge but also prominent skills. During medical education and training, several methods will be put to use such as watching video, reading books, making use of the simulated patient (SP), and so on. These can help medical staffs, especially novices, to master the skills and accumulate experiences. To make up for the drawbacks of the above methods, such as lack of active interactions, limitation of multi-symptom reproductions, etc, the medical training simulators have been developed to improve training effectiveness. However, most of these simulators only mimic the symptoms. They have no the abilities to show the pathology of diseases. This limits the training effectiveness. In this paper, we propose an elbow robot named WKE-1(Waseda Kyotokagaku Elbow Robot No.1) for neurologic examination training as one part of the whole body patient robot named WKP (Waseda Kyotokagaku Patient). In this robot, we simulate various symptoms occurring during the examination of elbow force, biceps tendon reflex, involuntary action, and also make a physiological neurological model to simulate the pathology of the nervous system. Taking advantage of this robot, the trainee can get a systematic training on both the skills and knowledge. Finally, we take a set of experiments to verify our proposed mechanism and system. The experimental results lead to the consideration that the approach is worth following in further research.

Neurologic examination takes an important role in diagnosis of the nerve system diseases. Neurologic medical staffs, especially the novices, need to be trained on this skill. There are many methodologies which can help to accumulate experiences, such as watching video, reading books, making use of the simulated patient (SP), and so on. However, the best way is to practice on the real patient. All the above methods have their own drawbacks such as lack of active interactions, limitation of multi-symptoms' reproducing, etc. To improve the training effectiveness, an arm robot is proposed in this paper for neurologic examination training as one part of the whole body patient robot named Waseda Kyotokagaku Patient (WKP). In this robot, various symptoms of the elbow force, biceps tendon reflex, involuntary action, and so on, are simulated and shown to the trainee. Finally, a set of experiments was carried out to verify our proposed mechanism and control system. Three neurologists with over 30 years' experience were invited to show their opinions on the reproductions of patients' symptoms, and to discuss the results. The effectiveness of this system was confirmed. The experimental results lead to the consideration that the approach is worth following in further research.

In recent years advanced robotic technology has seen more use in the medical field to assist in the development of efficient training systems. Such training systems must fulfill the following criteria: they must provide quantitative information, must simulate the real-world conditions of the task, and assure training effectiveness. We developed Waseda Kyotokagaku Airway series to fulfill all of those requirements. The WKA series we had developed does not consider external appearance such as patient skin, or internal appearance such as the pharynx, larynx, and esophagus. Moreover, the tongue mechanism of the previous system can not precisely measure the force applied by medical devices and cannot simulate muscle stiffness. In addition, the mandible mechanism of the previous system could not adequately reproduce various airway difficulties or apply force control. For these reasons, we propose the WKA-4, which has high-fidelity simulated human anatomy, and we have improved the mechanism over the previous system. We have also attached a lung to the proposed system to improve simulation of the real-world conditions of the task. In this paper, we present how to design several organs with various embedded sensors and actuators, for a conventional patient model with high-fidelity simulated human anatomy. We also present the control system for the WKA-4. Finally, we present a set of experiments carried out using doctors as subjects, and they gave their valuable opinions about our system.

Many patients suffer from swallowing disorders (dysphagia). There are many treatments for these disorders, such as swallowing therapy, surgery, and dietary modification. In our study, we focuse on dietary modification, a common approach. Normally, the swallowing is affected by food bolus properties such as hardness, stickiness and rheological characteristics, and dietary modifications can prevent swallowing disorder patients from suffering dysphagia (aspiration), as well as promote good nutrition. Based on these facts, our goal is to find foods which do not cause dysphagia, and develop food for swallowing disorder patients accordingly. Therefore, we are proposing an in-vitro Dynamic VFSS (Video Fluorographic Swallowing Study) simulation system which uses advanced robotics technology to mimic the dynamic process of swallowing and monitors the status and movement of the food bolus inside the system, for objective evaluation of the swallowing process. The dynamic VFSS simulation system consists of a head, mandible, neck, tongue, pharynx, and larynx which reproduce human anatomy. It is driven by 16 actuators with wire driving mechanisms. In this paper, we will present the dynamic VFSS simulation unit in detail. In addition, we will detail a set of the experiments carried out to determine whether food bolus properties can affect dysphagia or not. To observe the movement of the food bolus, we use a Video Fluoroscopy (VF) unit. The results of the experiments show that thickened boluses have a tendency to leave residue in the epiglottic vallecula. In contrast, liquids cause less residue, and increase the risk of dysphagia (aspiration). Moreover, this study shows that the frontal image, as well as the lateral image, is important for evaluating residual food in the oral- pharyngeal space.

Recently, in medical field, different training methods for medical staff have been proposed. However, the lack of knowledge on the real improvements of trainees makes difficult the real effectiveness of those proposed methods. Therefore, we are proposing an Active Training system for the effective medical training. The Active training system is characterized by providing quantitative information of the trainee's performance of the task to the trainee, simulating real-world conditions of the task, and assuring training effectiveness. In order to fulfill each of these characteristics, we have developed Waseda Kyotokagaku Airway No.3 (WKA-3) which makes it possible to obtain quantitative information for the trainee's performance and reproduce the various cases, individual differences for the airway difficulties for the simulating real-world conditions of the task. In this paper, we are proposing a patient scenario generation which can reproduce the characteristics of the patient simulating real-world conditions of the task for WKA-3. In emergent situation or surgical operation, the characteristics of patients are presented in the three parameters such as: patient initial conditions, time variant status change, and reflex action. By adjusting, and combining each of the three parameters, we can reproduce the various patient scenarios. In this paper, we also state how to generate the Patient Scenario Generation using the position control and virtual compliance control. Finally, a set of experiments has been carried out to the doctor subjects in order to verify effectiveness of the proposed Patient Scenario Generation, and discuss the doctors about the result of the experiments.

An active training system is characterized by providing quantitative information of the trainee's performance of the task to the trainee, simulating real-world conditions of the task, and assuring training effectiveness. For this purpose, the authors have been developing an Airway management training system. In particular, we have previously presented an evaluation model system to acquire quantitative information for the trainee's performance, and an actuated model system for real-world conditions of the task. In order to fulfill all of the characteristics of the active training system; in this paper, we would like to propose an integrated system, Waseda Kyotokagaku Airway No.3 (WKA-3) which integrates the function of both system models. For this reason, we have focused on embedding sensors and actuators with the link drive mechanism and the wire drive mechanism to a conventional patient model towards the development of a patient robot. In this paper, we present WKA-3 how to design the mechanism and how to redesign several organs to embed the sensors for the measurement of the trainee's performance. A set of experiment have been carried out to doctor subjects using the WKA-3 to verify the effectiveness of the proposed system by asking doctors to evaluate the proposed system.

The emerging field of medical robotics aims to introduce intelligent tools to assist a physician. The main challenges for developing efficient medical robotic training systems are simulating real-world conditions of the task and assuring training effectiveness. High anatomic fidelity has been achieved in current systems. However, those training systems are designed to reproduce specific conditions of the task (passive training). In this research, we are focusing in developing an airway management training systems designed to reproduce various cases of difficult airway. Such difficulties (i.e. restricted mouth opening, various shapes of oral cavity including tongue swallowing, etc) may provoke traumas on different organs of the patient during an emergency situation. For this purpose, the authors have proposed the development of more advanced training tools. For this purpose, we have focused in embedding sensors and actuators to a conventional patient model towards the development of a patient robot (in previous research, authors have presented the evaluation model which embeds sensors). In this paper, we present an airway training system which embeds actuators into a mannequin. In particular, the mechanism design of the Waseda Kyotokagaku Airway No.2 (WKA-2) is detailed. The WKA-2 is composed of twelve active and one passive degrees of freedom; which are designed to reproduce the various cases of difficult airway. For this purpose, the WKA-2 reproduces the human muscles around the upper airway based on a wire driving mechanisms (a total of sixteen wires are used). In particular, the head of the model is composed of a tongue and mandible with translational and rotational movements around kinematic axis. In addition, we present the details of the kinematic model of WKA-2 which enable the robot to reproduce the airway difficulties. Finally, we presented the design of a tension sensor designed to measure the applied tension on each of the wire driving mechanism of WKA-2. As preliminary experiments, we reproduce several cases of difficult airways using WKA-2.

Airway management is provided by emergency medical technicians or anesthetists in order to save unconscious patients who are unable to breathe. Even though it is a basic technique, many accidents may occur when the procedure is not provided followed. In order to avoid any risks to patients, emergency medical technicians are required to practice airway management using training devices such as mannequins; which are designed to accurately reproduce the human anatomy. However, such training devices do not provide any quantitative information about the learning progress of trainees (passive training). For that purpose, we have proposed the development of a airway management training system which is designed to embed array of sensors so that quantitative information of trainees' performance can be acquired. In this paper, we are presenting the Waseda-KyotoKagaku airway No. 1 (WKA-1). The WKA-1 consists of three different kinds of array of sensors which are embedded into a conventional mannequin. In order to embed the array of sensors, we have simplified the design of some of the simulated organs (upper airway, oral cavity, tongue and teeth) of the mannequin. A set of evaluation parameters were proposed based on the information collected through the sensors. A set of experiments were proposed to experimentally verify the effectiveness of the proposed evaluation parameters to quantitatively detect differences among different levels of skills (anesthetists and unskilled persons).