Robotic Localization Based on Planar Cable Robot and Hall Sensor Array Applied to Magnetic Capsule Endoscope

Integrated Sensors for Soft Medical Robotics

Minimally invasive procedures assisted by soft robots for surgery, diagnostics, and drug delivery have unprecedented benefits over traditional solutions from both patient and surgeon perspectives. However, the translation of such technology into commercialization remains challenging. The lack of perception abilities is one of the obstructive factors paramount for a safe, accurate and efficient robot-assisted intervention. Integrating different types of miniature sensors onto robotic end-effectors is a promising trend to compensate for the perceptual deficiencies in soft robots. For example, haptic feedback with force sensors helps surgeons to control the interaction force at the tool-tissue interface, impedance sensing of tissue electrical properties can be used for tumor detection. The last decade has witnessed significant progress in the development of multimodal sensors built on the advancement in engineering, material science and scalable micromachining technologies. This review article provides a snapshot on common types of integrated sensors for soft medical robots. It covers various sensing mechanisms, examples for practical and clinical applications, standard manufacturing processes, as well as insights on emerging engineering routes for the fabrication of novel and high-performing sensing devices.

Robot-Aided Magnetic Navigation System for Wireless Capsule Manipulation

Magnetic navigation systems (MNSs) have been developed to use in the diagnosis of gastrointestinal problems. However, most conventional magnetic navigation systems are expensive and have structural problems because of their large weights and volumes. Therefore, this paper proposes C-Mag, a novel compact MNS composed of two electromagnets and a robotic arm. The two electromagnets generate a planar magnetic field, and the robotic arm rotates and translates the electromagnets to manipulate the magnetic capsule in a large 3-dimensional (3-D) space. The C-Mag design considers the payload of the robotic arm and the capacity of the power supply unit. Under these limited conditions, the C-Mag was optimized to generate the maximum magnetic field considering several major factors. Finally, the C-Mag was constructed, and the maximum magnetic field that could be generated in one direction was 18.65 mT in the downward direction. Additionally, the maximum rotating magnetic field was 13.21 mT, which was used to manipulate the capsule. The performance was verified by measuring the generated magnetic field, and it matched well with the simulated result. Additionally, the path-following experiment of the magnetic capsule showed that the proposed C-Mag can effectively manipulate the magnetic capsule in 3-D space using the robotic arm. This study is expected to contribute to the further development of magnetic navigation systems to treat gastrointestinal problems.

Electrical Optimization Method Based on a Novel Arrangement of the Magnetic Navigation System with Gradient and Uniform Saddle Coils

The magnetic navigation system (MNS) with gradient and uniform saddle coils is an effective system for manipulating various medical magnetic robots because of its compact structure and the uniformity of its magnetic field and field gradient. Since each coil of the MNS was geometrically optimized to generate strong uniform magnetic field or field gradient, it is considered that no special optimization is required for the MNS. However, its electrical characteristics can be still optimized to utilize the maximum power of a power supply unit with improved operating time and a stronger time-varying magnetic field. Furthermore, the conventional arrangement of the coils limits the maximum three-dimensional (3D) rotating magnetic field. In this paper, we propose an electrical optimization method based on a novel arrangement of the MNS. We introduce the objective functions, constraints, and design variables of the MNS considering electrical characteristics such as resistance, current density, and inductance. Then, we design an MNS using an optimization algorithm and compare it with the conventional MNS; the proposed MNS generates a magnetic field or field gradient 22% stronger on average than that of the conventional MNS with a sevenfold longer operating time limit, and the maximum three-dimensional rotating magnetic field is improved by 42%. We also demonstrate that the unclogging performance of the helical robot improves by 54% with the constructed MNS.

Design and evaluation of perception reconstruction with sensor system for artificial anal sphincter based on vector similarity

BACKGROUND

Artificial organs are playing an increasingly important role in medical field. Artificial anal sphincter, as an example, is a widely used medical device for fecal incontinence. Though it could help patients maintain continence, the issue of perception reconstruction is still unsolved, which means that patients cannot control defecation as desired.

METHODS

In this paper, a novel sensor system based on vector similarity has been analyzed and evaluated. The sensor system is a self-packaged strain gauge sensor with a small size 14.5mm x 6mm, especially for medical device implanted in body to reconstruct perception function. In order to overcome the disadvantages of single threshold judgment, a more accurate and reliable judgment standard for content pressure detection in rectum is developed by using vector similarity method. Therefore, in the novel sensor system, standard multi-parameters are comprehensive considered. Furthermore, weight-optimization of sensors are investigated since each sensor has played a different role in detection. Finally, sensor calibration, in vitro and in vivo experiments are established.

RESULTS

In sensor calibration, the result R² > 0.99 presents the strain gauge pressure sensor has a good linearity. After that, a series of in vitro experiments have been conducted. The optimized sensor system shows a high accuracy rate in perception reconstruction, which is 87.5% on early warning and 95% on the alarm. In the following in vivo experiments. The results indicate that the average accuracy of the proposed perception reconstruction module has increased by 17.7%, compared with that without optimized sensor system.

CONCLUSIONS

All of these have proven that the novel perception reconstruction module with sensor system based on vector similarity is more acceptable and reliable.

Two-Dimensional Position Tracking Using Gradient Magnetic Fields

In this work, a two-dimensional (2D) position-detection device using a single axis magnetic sensor combined with orthogonal gradient coils was designed and fabricated. The sensors used were an induction coil and a GMR spin-valve sensor GF807 from Sensitec Inc. The field profiles generated by the two orthogonal gradient coils were analyzed numerically to achieve the maximum linear range, which corresponded to the detection area of the tracking system. The two coils were driven by 1-kHz sine wave currents with a 90° phase difference to generate the fields with uniform gradients along the x- and y-axis in the plane of the tracking stage. The gradient fields were detected by a single-axis sensor incorporated with a digital dual-phase lock-in detector to retrieve the position information. A linearity correction algorithm was used to improve the location accuracy and to extend the linear range for position sensing. The mean positioning error was found to be 0.417 mm, corresponding to the relative error of 0.21% in the working range of 200 mm × 200 mm, indicating that the proposed tracking system is promising for applications requiring accurate control of the two-dimensional position.

Wireless Capsule Endoscope Localization with Phase Detection Algorithm and Adaptive Body Model

Wireless capsule endoscopes take and send photos of the human digestive tract, which are used for medical diagnosis. The capsule’s location enables exact identification of the regions with lesions. This can be carried out by analyzing the parameters of the electromagnetic wave received from the capsule. Because the human body is a complex heterogeneous environment that impacts the propagation of wireless signals, determining the distance between the transmitter and the receiver based on the received power level is challenging. An enhanced approach of identifying the location of endoscope capsules using a wireless signal phase detection algorithm is presented in this paper. For each capsule position, this technique uses adaptive estimation of human body model permittivity. This approach was tested using computer simulations in Remcom XFdtd software using a numerical, heterogeneous human body model, as well as measurements with physical phantom. The type of transmitting antenna employed in the capsule also has a significant impact on the suggested localization method’s accuracy. As a result, the helical antenna, which is smaller than the dipole, was chosen as the signal’s source. For both the numerical and physical phantom studies, the proposed technique with adaptive body model enhances localization accuracy by roughly 30%.

A Portable Intuitive Haptic Device on a Desk for User-Friendly Teleoperation of a Cable-Driven Parallel Robot

This paper presents a compact-sized haptic device based on a cable-driven parallel robot (CDPR) mechanism for teleoperation. CDPRs characteristically have large workspaces and lightweight actuators. An intuitive and user-friendly remote control has not yet been achieved, owing to the unfamiliar multiple-cable configuration of CDPRs. To address this, we constructed a portable compact-sized CDPR with the same configuration as that of a larger fully constrained slave CDPR. The haptic device is controlled by an admittance control for stiffness adjustment and implemented in an embedded microprocessor-based controller for easy installation on an operator’s desk. To validate the performance of the device, we constructed an experimental teleoperation setup by using the prototyped portable CDPR as a master and larger-size CDPR as a slave robot. Experimental results showed that a human operator can successfully control the master device from a remote site and synchronized motion between the master and slave device was performed. Moreover, the user-friendly teleoperation could intuitively address situations at a remote site and provide an operator with realistic force during the motion of the slave CDPR.

Localization and Actuation for MNPs Based on Magnetic Field-Free Point: Feasibility of Movable Electromagnetic Actuations

Targeted drug delivery (TDD) based on magnetic nanoparticles (MNPs) and external magnetic actuation is a promising drug delivery technology compared to conventional treatments usually utilized in cancer therapy. However, the implementation of a TDD system at a clinical site based on considerations for the actual size of the human body requires a simplified structure capable of both external actuation and localization. To address these requirements, we propose a novel approach to localize drug carriers containing MNPs by manipulating the field-free point (FFP) mechanism in the principal magnetic field. To this end, we devise a versatile electromagnetic actuation (EMA) system for FFP generation based on four coils affixed to a movable frame. By the Biot-Savart law, the FFP can be manipulated by appropriately controlling the gradient field strength at the target area using the EMA system. Further, weighted-norm solutions are utilized to correct the positions of FFP to improve the accuracy of FFP displacement in the region of interest (ROI). As MNPs, ferrofluid is used to experiment with 2D and 3D localizations in a blocked phantom placed in the designed ROI. The resultant root mean square error of the localizations is observed to be approximately 1.4 mm in the 2D case and 1.6 mm in the 3D case. Further, the proposed movable EMA is verified to be capable of simultaneously scanning multiple points as well as the actuation and imaging of MNPs. Based on the success of the experiments in this study, further research is intended to be conducted in scale-up system development to design precise TDD systems at clinical sites.