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Extensive efforts in providing upper limb amputees with sensory feedback have primarily focused on the restoration of tactile capabilities, while challenges in evoking proprioceptive sensations have been poorly addressed. Previously, an human–machine interface (HMI) was proposed based on permanent magnets implanted in residual muscles of an amputee, namely the myokinetic interface, to control robotic limb prostheses. Besides control, implanted magnets offer an unprecedent opportunity to trigger musculotendon proprioceptors via untethered selective vibrations. Herein, the challenge of tracking multiple moving magnets is addressed (e.g., following muscle contractions) while being vibrated by controlled magnetic fields produced by external coils. Results demonstrate the viability of a real‐time (RT) system capable of simultaneously tracking and vibrating multiple moving magnets within a three‐dimensional workspace. Highly selective torsional vibrations in the frequency span eliciting movement illusions (70, 80, and 90 Hz) are achieved on two moving magnets, with efficiencies above 0.82 (over 80% of spectral power at the desired frequency). Tracking accuracy and precision remain robust to the coil magnetic field, with position median errors below 1.2 mm and median displacement errors below 0.95 mm. This study represents a crucial step towards the development of a bench system to study proprioception in humans. [ABSTRACT FROM AUTHOR]

Extensive efforts in providing upper limb amputees with sensory feedback have primarily focused on the restoration of tactile capabilities, while challenges in evoking proprioceptive sensations have been poorly addressed. Previously, an human–machine interface (HMI) was proposed based on permanent magnets implanted in residual muscles of an amputee, namely the myokinetic interface, to control robotic limb prostheses. Besides control, implanted magnets offer an unprecedent opportunity to trigger musculotendon proprioceptors via untethered selective vibrations. Herein, the challenge of tracking multiple moving magnets is addressed (e.g., following muscle contractions) while being vibrated by controlled magnetic fields produced by external coils. Results demonstrate the viability of a real‐time (RT) system capable of simultaneously tracking and vibrating multiple moving magnets within a three‐dimensional workspace. Highly selective torsional vibrations in the frequency span eliciting movement illusions (70, 80, and 90 Hz) are achieved on two moving magnets, with efficiencies above 0.82 (over 80% of spectral power at the desired frequency). Tracking accuracy and precision remain robust to the coil magnetic field, with position median errors below 1.2 mm and median displacement errors below 0.95 mm. This study represents a crucial step towards the development of a bench system to study proprioception in humans.

Drones, or unmanned aerial vehicles (UAVs), have emerged as an indispensable tool across numerous industries due to their remarkable versatility, efficiency, and capabilities. Notwithstanding all these traits, drones are still limited by battery life. In this paper, we propose a genuine in-flight charging method without landing. The charging system consists of three orthogonal coils, among which the receiving coil is connected to the drone. The development of the model for wireless dynamic charging systems is achieved by integrating the receiver trajectory and velocity in the model. Furthermore, the model is significantly enhanced by introducing the concept of the positioning mutual coupling function for the receiver trajectory; thus, it is possible to simulate a genuine continuous trajectory for UAVs and link it to the systems' total input power consumption. The developed control algorithm can direct the magnetic field resultant to track the exact trajectory of the drone. The real-time simulation of the multiparameter discrete extremum-seeking control (ESC) algorithm on the (DSP) F28379D hardware shows that the input power is maximized up to 12 W in a response time of 2 ms for a drone-hovering velocity of 8 m/s without any feedback. [ABSTRACT FROM AUTHOR]

Purpose: Existing field generators (FGs) for magnetic tracking cause severe image artifacts in X-ray images. While FG with radio-lucent components significantly reduces these imaging artifacts, traces of coils and electronic components may still be visible to trained professionals. In the context of X-ray-guided interventions using magnetic tracking, we introduce a learning-based approach to further reduce traces of field-generator components from X-ray images to improve visualization and image guidance. Methods: An adversarial decomposition network was trained to separate the residual FG components (including fiducial points introduced for pose estimation), from the X-ray images. The main novelty of our approach lies in the proposed data synthesis method, which combines existing 2D patient chest X-ray and FG X-ray images to generate 20,000 synthetic images, along with ground truth (images without the FG) to effectively train the network. Results: For 30 real images of a torso phantom, our enhanced X-ray image after image decomposition obtained an average local PSNR of 35.04 and local SSIM of 0.97, whereas the unenhanced X-ray images averaged a local PSNR of 31.16 and local SSIM of 0.96. Conclusion: In this study, we proposed an X-ray image decomposition method to enhance X-ray image for magnetic navigation by removing FG-induced artifacts, using a generative adversarial network. Experiments on both synthetic and real phantom data demonstrated the efficacy of our method. [ABSTRACT FROM AUTHOR]

Drones, or unmanned aerial vehicles (UAVs), have emerged as an indispensable tool across numerous industries due to their remarkable versatility, efficiency, and capabilities. Notwithstanding all these traits, drones are still limited by battery life. In this paper, we propose a genuine in-flight charging method without landing. The charging system consists of three orthogonal coils, among which the receiving coil is connected to the drone. The development of the model for wireless dynamic charging systems is achieved by integrating the receiver trajectory and velocity in the model. Furthermore, the model is significantly enhanced by introducing the concept of the positioning mutual coupling function for the receiver trajectory; thus, it is possible to simulate a genuine continuous trajectory for UAVs and link it to the systems’ total input power consumption. The developed control algorithm can direct the magnetic field resultant to track the exact trajectory of the drone. The real-time simulation of the multiparameter discrete extremum-seeking control (ESC) algorithm on the (DSP) F28379D hardware shows that the input power is maximized up to 12 W in a response time of 2 ms for a drone-hovering velocity of 8 m/s without any feedback.

Abstract The use of subcutaneous devices has greatly advanced the field of medicine and surgery. However, localizing these devices internally requires imaging techniques such as X‐ray or ultrasound. A novel magnetic tracking system for subcutaneous medical devices is presented, providing the capability for precise device localization in an extremely compact and portable pocket‐size format. It is entirely benign, avoids X‐rays, and can be used to immediately confirm the proper instrument placement. It is implemented on umbilical catheters and endotracheal tubes and is characterized by bench‐test, cadaveric, and in vivo studies. The systems consist of a magnetic tip fixed to the distal end of the subcutaneous device, as well as a Magnetic Sensing‐Array Device that utilizes a matrix of magnetic field sensors to localize the magnetic tip. The bench‐tests show a high localization accuracy for a distance up to 4 cm. The accuracy is slightly reduced during cadaveric and in vivo tests, due to factors impacting the application, such as the dermal surface topography. Regardless, the magnetic subcutaneous medical device tracking system is shown to be robust in performance and functionality in real‐world clinical applications, and with its intuitive approach and portability, it has the potential to make real‐time subcutaneous device tracking widely accessible.

This study proposes an analytical model of a WPT system with three orthogonal transmitter coils organised to produce a concentrated and controlled omnidirectional magnetic field suited for charging a moving, rotating load, providing maximal energy transfer without receiving end feedback. In order to create a realistic 3D WPT simulation system and a precise controller design, the mutual coupling values in terms of the receiver angular positions are modelled using the Ansys software. In using the established model of the 3DWPT system, an extremum seeking control (ESC) is used to maximize the power transfer utilizing the input power as an objective function assigned with specified parametric values defining the WPT model. The output power transmitted by the sending-end coils to a load of a moving UAV rotating in orbit is displayed. According to simulation results, when the receiver UAV speed is close to 2250 deg/s, the controller can accomplish a maximum power transfer of 2.6w in almost 1ms. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Magnetic tracking enables instrument tracking for image-guided interventions when no line of sight is available. This paper describes the first steps towards a more cost-effective, modular, and adaptable approach that builds upon prior work in open hardware architectures for magnetic tracking in image-guided interventions. An exemplary C++ framework is implemented and demonstrated with the open-hardware Anser EMT system. System performance in speed, accuracy, and precision of the C++ implementation is analysed. Static positioning accuracy and precision are calculated within the Region of Interest (ROI) and an average position error of 1.0 ± 0.1 mm is demonstrated. Results show an indicative increase in the update rate using the C++ framework and substantially lower memory requirements, compared to the previously optimised Python and Matlab solvers. These preliminary results provide the basis for future development which will integrate the C++ framework in a 3D Slicer module, greatly extending the adaptability of the platform for customisation in advanced image-guided procedures. [ABSTRACT FROM AUTHOR]

High definition 6 degrees of freedom (6-DoF) tracking in the Personal Area Tracking (PAT) region offers a wide range of applications. In this region, inside-out trackers can potentially offer the advantage of being portable. Outside-in trackers, though offering superior performance on average, lack this portability which might limit the number of PAT applications. Thus, there is a need for developing inside-out trackers that can achieve comparable performance. To that end, a tracking system based on AC magnetic field and inertial measurement units (IMUs) has been developed. It consists of a transmitter that can be integrated into a headset and multiple wireless trackers. The tracking system is compact, portable, wireless and low power consuming. The system is optimized to minimize jitter and latency, which are crucial for providing a good user experience in Virtual/Augmented Reality (VR/AR) applications. The compact design is compatible with mobile computing units such as a smartphone. This work presents the challenges associated with the magnetic field symmetry that hinders 8-octant tracking. A method using motion correlation is implemented to perform 8-octant tracking. A position jitter of less than 1 mm up to 1 m, an update rate of 400 Hz, and a latency of about 5 ms have been achieved through sensor fusion, on-the-fly calibration, and filtering. [ABSTRACT FROM AUTHOR]

This paper presents a simulation system (“patient model”) for intraoperative neuromonitoring (IONM) applied to mastoidectomy. IONM is an electrophysiological method for monitoring the integrity and localization of nerve tracts, which helps the surgeon to avoid injuries and damage to neural risk structures (e.g. facial nerve) during surgery. To use the IONM successfully, the surgeon needs appropriate training and experience. The presented simulation system provides training possibilities in a realistic, cost-efficient and reproducible way. In the simulation system, the position of the probe during training is determined by a magnetic tracking method. Depending on the distance to the virtual nerve, a synthetic electromyogram (EMG) signal is sent to a real neuromonitor. The trainee learns to interpret the output of the neuromonitor. The trainer can choose different training scenarios, such as localization of the nerve, milling or coagulating, using a web application.

Magnetic tracking systems have been widely investigated in biomedical engineering due to the transparency of the human body to static magnetic fields. We recently proposed a novel human-machine interface for prosthetic application, namely the myokinetic interface. This controls multi-articulated prostheses by tracking magnets implanted in the residual muscles of individuals with amputation. Previous studies in this area focused solely on the choice and tuning of the localization algorithm. Here, we addressed the role of the intrinsic properties of the sensors, by analysing their effects on the tracking accuracy and on the computation time of the localization algorithm, through experimentally-verified computer simulations. We observed that the tracking accuracy is primarily affected by the localization rate, which is directly related to the sampling frequency of the sensors, and less significantly affected by the sensor resolution. The computation time, instead, proved positively correlated to the number of MMs, and negatively correlated with the localization rate. Our results may contribute to the development of novel human-machine interfaces for prosthetic limbs and could be extended to a broad range of applications involving magnetic tracking. [ABSTRACT FROM AUTHOR]

Passive magnetic localization is a wireless motion tracking method that can determine position and orientation of objects with embedded magnets. The magnetic field around the magnetic object can be detected using magnetometers. Afterward, using an optimization algorithm, the difference between the measured and calculated magnetic field (from the mathematical model of the magnetic field produced around the magnetic object) is minimized. However, using numerical optimization methods faces two main challenges: low computation speed to reach desirable accuracy and convergence to a local minimum. In this paper, we propose a method to analytically calculate the magnet’s orientation in terms of the magnet’s position. Therefore, the optimization problem is solved only to find the position unknowns. The experimental results demonstrate that the average position error is 2.0 mm and orientation error is 2.3° for a cube magnet with a 5 mm edge length. According to the experiments, by employing this method, computation speed becomes 2.1 times faster with respect to the conventional method. Furthermore, in contrast to the conventional method, the proposed technique is robust with respect to the initial conditions and the technique always converges towards the global minimum and gives the correct solution regardless of the initial guess. [ABSTRACT FROM AUTHOR]

This study proposes an analytical model of a WPT system with three orthogonal transmitter coils organised to produce a concentrated and controlled omnidirectional magnetic field suited for charging a moving, rotating load, providing maximal energy transfer without receiving end feedback. In order to create a realistic 3D WPT simulation system and a precise controller design, the mutual coupling values in terms of the receiver angular positions are modelled using the Ansys software. In using the established model of the 3DWPT system, an extremum seeking control (ESC) is used to maximize the power transfer utilizing the input power as an objective function assigned with specified parametric values defining the WPT model. The output power transmitted by the sending-end coils to a load of a moving UAV rotating in orbit is displayed. According to simulation results, when the receiver UAV speed is close to 2250 deg/s, the controller can accomplish a maximum power transfer of 2.6w in almost 1ms.

Multi-arm wire-driven continuum robots can provide dexterous maneuvers during minimally invasive surgeries (MISs). To ensure safety during MIS, it is critical to obtain feedback information such as the poses of end effectors on all arms. However, precise and real-time pose information of multi-object cannot be obtained within the human body due to the high computational cost in the current optimization approach of magnetic tracking systems. In this article, we propose to track the poses of multiple end effectors of a multi-arm continuum robot by permanent magnetic tracking technology. A permanent magnet is mounted at each distal end of the flexible arms and a sensor array is used to sample the magnetic field signals. The extended Kalman filter (EKF) algorithm is utilized to fuse the poses estimated from the kinematic model and the magnetic field model to realize multi-target positioning for surgical navigation. The proposed method is validated by experiments. The mean position error is 1.32 mm and the computing time is 1.5 ms. As a result, the proposed method can effectively provide accurate tracking results and meanwhile decrease the tracking latency for real-time applications. [ABSTRACT FROM AUTHOR]

Magnetic tracking has been well studied for the localization of wireless capsule robots. However, most of the existing magnetic localization systems require a stable background magnetic field, which is not suitable for wearable applications as the movement of the human body inevitably changes the magnetic field to each sensor. The purpose of this study is to reduce the disturbance of the ambient magnetic field for localizations in different background scenarios. The proposed approach applies the magnetic density of multiple sampling points for simultaneous localization. By subtracting the magnetic field value in different positions, the background noise (BGN) field can be offset. As a result, multipoint simultaneous positioning can be achieved by using an optimization algorithm. The influence of the signal-to-noise ratio on localization accuracy has been determined through simulation analysis. Experiments first verified the feasibility of multipoint simultaneous positioning and then conducted in different geomagnetic noise and permanent magnet environments. The results show that the proposed method has been verified to be robust in different BGN environments. The proposed method is expected to be used in wearable systems for tracking magnetic capsule endoscope (MCE). [ABSTRACT FROM AUTHOR]

The largest disadvantage of modern day minimally invasive surgery is the required use of X‐ray or fluoroscopic imaging for locating or tracking medical catheters and tubes. The implications are increased costs and effort, limited availability for instance in less developed countries, and the cumulative exposure to contrast dyes and ionizing radiation are detrimental to health, especially in young patients and neonates with increased sensitivity. In order to reduce the use of X‐ray imaging and provide a wider accessibility, a facile magnetic system is proposed for subcutaneous medical device localization. It consists of a lightweight and flexible, biocompatible, and permanent magnet at the tip of the subcutaneous device and a sensing device to scan the dermal surface and locate the magnetic tip. The mechanical and magnetic properties of the magnetic tip are tailored to fit the requirements of the delicate catheter application. Evaluation of the tracking system using a 5 Fr magnetic tip resulted in a depth‐dependent position and orientation error of 0.75 mm and 3.7°. Additionally, a maximum placement depth error of 0.96 mm is achieved. Evaluation of the system in vivo revealed its practicality and accuracy as well as the influence of potential user errors. [ABSTRACT FROM AUTHOR]

The magnetic tracking system, which is based on a permanent magnet and a magnetometer array, has numerous potential applications in the biomedical and industrial area. However, its tracking accuracy drops off sharply with the increase of tracking distance because of both the interference of environmental magnetic field and sensor measurement noise. To extend the magnetic tracking range, two novel methods were proposed in this study. First, the state-of-the-art tri-axial tunnel magnetoresistance (TMR) sensors, which possess the most significant field sensitivity and signal-to-noise ratio (SNR) over other types of magnetoresistive sensors, were adopted to construct the sensor array. Second, a fusion approach was proposed for tracking range extending. The particle swarm optimization-Levenberg Marquardt (PSO-LM) method based on the magnetic dipole model was applied in the near field (i.e., near-source zone), and the prior knowledge based back propagation neural network (PKBPNN) was adopted to the far field (i.e., far-source zone). In the transition zone, these two algorithms were fused by using an adaptive sigmoid function. The trained artificial neural network (ANN) model embodied the physical model errors, the sensor installation errors, and the inherent characteristics of adopted magnetometers. Therefore, it has greater tracking performance than singly using the PSO-LM in the far-source zone. The experimental results show that the tracking errors decrease from (18.24 ± 9.37mm, 12.45 ± 3.37°) to (8.95 ± 1.74mm, 7.97 ± 2.08°) in the tracking range between 216 and 296 mm. Besides, the tracking distance is extended to 396 mm, with the position error of less than 25 mm. It can be concluded that this approach has significantly extended the tracking range of the magnetic tracking system.

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.

• Magnetic Tracking in a stirred media mill with an internal deflector wheel. • Following a single magnetic tracer. • Determination of tracer bead velocity and stress conditions. • Viscosity influences grinding by axial grinding media distribution. • The tip speed especially influences the highest bead velocities. Fine grinding in stirred media mills is an important process in mineral, chemical and pharmaceutical industry. The stressing mechanism in these mills is grinding through compression and shearing by grinding beads. A few studies have examined grinding bead transport in stirred media mills. Radiometric methods detect the local filling degree, but little is known about the experimental motion of the grinding beads in the mill. This study aims to investigate the position, velocity and radial circulation of individual grinding beads at different operation parameters (viscosity and tip speed) by a fast and inexpensive measurement technique. Additional information about stresses in the mill were derived, such as a relation between axial grinding media distribution and grinding bead velocity. As a result, the two investigated operation parameter (viscosity and tip speed) effect the grinding bead velocity and grinding bead transport in the mill. The mentioned results can be used to validate DEM simulation results. [ABSTRACT FROM AUTHOR]

We recently introduced the concept of a new human-machine interface (the myokinetic control interface) to control hand prostheses. The interface tracks muscle contractions via permanent magnets implanted in the muscles and magnetic field sensors hosted in the prosthetic socket. Previously we showed the feasibility of localizing several magnets in non-realistic workspaces. Here, aided by a 3D CAD model of the forearm, we computed the localization accuracy simulated for three different below-elbow amputation levels, following general guidelines identified in early work. To this aim we first identified the number of magnets that could fit and be tracked in a proximal (T1), middle (T2) and distal (T3) representative amputation, starting from 18, 20 and 23 eligible muscles, respectively. Then we ran a localization algorithm to estimate the poses of the magnets based on the sensor readings. A sensor selection strategy (from an initial grid of 840 sensors) was also implemented to optimize the computational cost of the localization process. Results showed that the localizer was able to accurately track up to 11 (T1), 13 (T2) and 19 (T3) magnetic markers (MMs) with an array of 154, 205 and 260 sensors, respectively. Localization errors lower than 7% the trajectory travelled by the magnets during muscle contraction were always achieved. This work not only answers the question: “how many magnets could be implanted in a forearm and successfully tracked with a the myokinetic control approach?”, but also provides interesting insights for a wide range of bioengineering applications exploiting magnetic tracking. [ABSTRACT FROM AUTHOR]

The subject of research is the process of forming signals in magnetic tracking systems including those used for spatial position calculation within the concepts of Industry 4.0 and Industrial Internet of Things. Such systems are based on calculating the spatial position of objects upon measurements of reference magnetic fields in low-frequency electromagnetic radiation spectrum. The goal is to develop and verify a signal model for spatial position calculating in magnetic tracking systems. The signal model is developed upon experimentally obtained dependencies of the informative signals on the distances and angles between sensor and actuator coils. Objectives: analysis of signals in magnetic tracking systems, development of tools for experimental study, mathematical interpretation of the research results along with development of the signal model, verification and use of the developed model. General scientific methods were used, including experiment, measurement, analysis, synthesis, probabilistic and statistical methods. We have obtained the following results: The structure of a signal chain of the programmable magnetic tracking systems and its implementation on the basis of PSoC of 5LP Family by Cypress Semiconductor has been disclosed. Experimental results obtained at different distances and angles between the actuator and sensor coils have been presented. For spatial positions calculation signal models that describe distribution of magnetic fields and signals of sensor coils are used. We have analyzed typical inaccuracies and ways of their minimization. For verification of the introduced signal model we propose to use the mean square deviation of normalized signals. Conclusions. A signal model for the mutual position of actuators and sensors in magnetic tracking systems has been developed. The model describes functional dependencies whose main parameters are the distances and angles between coils. Further development of the presented results implies the proposed signal model to be used when solving problems of developing and specifying algorithms of spatial position calculation, system debugging and rapid analysis, optimization of calibration procedures.

Passive magnetic localization is a feasible method to perform a small-scale localization for robotics and biomedical devices, for instance, wireless capsule endoscopy. Suffering from the magnetic noises such as geomagnetic noise and magnetic disturbance in the environment, the localization accuracy of the passive magnetic localization is drastically influenced without a careful system design. In this article, the signal–noise ratio (SNR) of each sensor measurement is defined and applied in the design of both the localization algorithm and the measurement system. Simulations are conducted to verify the relationship between the measurement SNR and the accuracy of the distance estimation. In addition, strategies on the selection of the target magnet, effective SNR threshold of the localization algorithm, and the optimal sensors’ distribution are proposed based on the SNR evaluation results. Extended experimental results show that by setting the SNR threshold at 6 dB and adopting the optimal sensors’ distribution, the root-mean-square localization error is improved from 0.0529 to 0.0364 mm and the orientation error is improved from 17.3° to 13.7° compared to the uniform sensors’ distribution. The proposed algorithm can be used for accurate localization and tracking for untethered devices or biomedical devices, e.g., wireless capsule endoscopy. [ABSTRACT FROM AUTHOR]

Purpose: An intraoperative real-time respiratory tumor motion prediction system with magnetic tracking technology is presented. Based on respiratory movements in different body regions, it provides patient and single/multiple tumor-specific prediction that facilitates the guiding of treatments. Methods: A custom-built phantom patient model replicates the respiratory cycles similar to a human body, while the custom-built sensor holder concept is applied on the patient's surface to find optimum sensor number and their best possible placement locations to use in real-time surgical navigation and motion prediction of internal tumors. Automatic marker localization applied to patient's 4D-CT data, feature selection and Gaussian process regression algorithms enable off-line prediction in the preoperative phase to increase the accuracy of real-time prediction. Results: Two evaluation methods with three different registration patterns (at fully/half inhaled and fully exhaled positions) were used quantitatively at all internal target positions in phantom: The statical method evaluates the accuracy by stopping simulated breathing and dynamic with continued breathing patterns. The overall root mean square error (RMS) for both methods was between 0.32 ± 0.06 mm and 3.71 ± 0.79 mm . The overall registration RMS error was 0.6 ± 0.4 mm . The best prediction errors were observed by registrations at half inhaled positions with minimum 0.27 ± 0.02 mm , maximum 2.90 ± 0.72 mm . The resulting accuracy satisfies most radiotherapy treatments or surgeries, e.g., for lung, liver, prostate and spine. Conclusion: The built system is proposed to predict respiratory motions of internal structures in the body while the patient is breathing freely during treatment. The custom-built sensor holders are compatible with magnetic tracking. Our presented approach reduces known technological and human limitations of commonly used methods for physicians and patients. [ABSTRACT FROM AUTHOR]

Objective: The quest for an intuitive and physiologically appropriate human-machine interface for the control of dexterous prostheses is far from being completed. To control a hand prosthesis, a possible approach could consist in using information related to the displacement of forearm muscles of an amputee during contraction. We recently proposed that muscle displacement could be monitored by implanting passive magnetic markers (MMs– i.e., permanent magnets) in them. We dubbed this the myokinetic interface. However, besides the system feasibility, how much its accuracy, precision and computation time are affected by the number and distribution of both the MMs and the sensors used to record the MF was not quantified. Methods: Here we investigated, through simulations validated with a physical system, the performance of a system capable to track position and orientation of up to 9 MMs using information from up to 112 sensors in a volume resembling the dimensions of the human forearm. Results: The system was able to track up to 7 MMs in 450 ms, demonstrating position/orientation accuracies in the range of 1 mm/5°. The comparison with the experimental recordings demonstrated a median difference with the simulations in the order of 0.45 mm. Conclusion: We were able to formulate general guidelines for the implementation of magnetic tracking systems. Significance: Our results pave the way towards the development of new human-machine interfaces for the control of artificial limbs, but they are also interesting for the whole range of biomedical engineering applications exploiting magnetic tracking. [ABSTRACT FROM AUTHOR]

Magnetic-based localization technique has been widely studied to provide accurate position and orientation information of intra-body objects, such as capsule endoscopes. However, the magnetic field decays rapidly, which is inversely proportional to the cubic of the distance. As a result, the tracking range is limited. In this paper, a magnetic servo approach is proposed for intra-body objects that move in a large volume, such as the whole digestive tract. A static tracking system formed with 8 Hall sensors is linked with a movable platform with motors. The proposed method utilizes the static tracking system to provide a precise positioning result within a small tracking range. When the distance between the object and the static tracking system exceeds a certain threshold, static tracking system will be controlled by the motors to move automatically based on a magnetic servo method to ensure accurate tracking results in a large range. Experimental results show that the proposed servo tracking method can provide a high accuracy of positioning and orientation results within a large range that as good as stationary method in small range. Within the range of 600 mm $\times500$ mm, the average position error is 2.04 mm and orientation error is 2.45°. The proposed localization method would be beneficial to the clinical examination and navigation. [ABSTRACT FROM AUTHOR]

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Purpose : A robotic intraoperative laser guidance system with hybrid optic-magnetic tracking for skull base surgery is presented. It provides in situ augmented reality guidance for microscopic interventions at the lateral skull base with minimal mental and workload overhead on surgeons working without a monitor and dedicated pointing tools. Methods : Three components were developed: a registration tool (Rhinospider), a hybrid magneto-optic-tracked robotic feedback control scheme and a modified robotic end-effector. Rhinospider optimizes registration of patient and preoperative CT data by excluding user errors in fiducial localization with magnetic tracking. The hybrid controller uses an integrated microscope HD camera for robotic control with a guidance beam shining on a dual plate setup avoiding magnetic field distortions. A robotic needle insertion platform (iSYS Medizintechnik GmbH, Austria) was modified to position a laser beam with high precision in a surgical scene compatible to microscopic surgery. Results : System accuracy was evaluated quantitatively at various target positions on a phantom. The accuracy found is 1.2 mm ± 0.5 mm. Errors are primarily due to magnetic tracking. This application accuracy seems suitable for most surgical procedures in the lateral skull base. The system was evaluated quantitatively during a mastoidectomy of an anatomic head specimen and was judged useful by the surgeon. Conclusion : A hybrid robotic laser guidance system with direct visual feedback is proposed for navigated drilling and intraoperative structure localization. The system provides visual cues directly on/in the patient anatomy, reducing the standard limitations of AR visualizations like depth perception. The custom- built end-effector for the iSYS robot is transparent to using surgical microscopes and compatible with magnetic tracking. The cadaver experiment showed that guidance was accurate and that the end-effector is unobtrusive. This laser guidance has potential to aid the surgeon in finding the optimal mastoidectomy trajectory in more difficult interventions. [ABSTRACT FROM AUTHOR]

Electromagnetic tracking (EMT) systems play an important role in medicine, robotics, and virtual reality applications by providing accurate position and orientation referencing within a fixed volume around a magnetic field generator. Advances in sensor technology provide increasingly small, lightweight sensors capable of being integrated into hand-held devices for medical simulation, gaming, and image-guided surgery. The need for customizable tracking volumes becomes of interest as the uptake of EMT technology increases. This paper proposes a new method of creating custom tracking volumes from multiple planar field generators. A monolithic, low-cost printed circuit board design allows for tiling of multiple generators to create a larger tracking volume. Experiments were performed with two generators at different angles. Successful tracking is demonstrated with increased positional accuracy observed when transmitters are inclined with respect to one another. Horizontal tiling configurations are most accurate when a common edge is shared between adjacent field generators. [ABSTRACT FROM AUTHOR]

We characterize the performance of a system based on a magnetoresistor array. This instrument is developed to map the magnetic field, and to track a dipolar magnetic source in the presence of a static homogeneous field. The position and orientation of the magnetic source with respect to the sensor frame is retrieved together with the orientation of the frame with respect to the environmental field. A nonlinear best-fit procedure is used, and its precision, time performance, and reliability are analyzed. This analysis is performed in view of the practical application for which the system is designed that is an eye-tracking diagnostics and rehabilitative tool for medical purposes, which require high speed (≥100 Sa/s) and sub-millimetric spatial resolution. A throughout investigation on the results makes it possible to list several observations, suggestions, and hints, which will be useful in the design of similar setups.

Based on a permanent magnet and a magnetometer array, magnetic tracking approach has some advantages such as wireless, real-time, and no line-of-sight problem. However, its tracking accuracy will be greatly deteriorated by the magnetometer array’s rotating during the tracking process. The reason lies in the relative variation of triaxial geomagnetic components, which should be calibrated before the tracking process. In this paper, we proposed an inertial sensor-based geomagnetic compensation method to reduce the intervention of the triaxial geomagnetic components for the magnetic tracking performance. An inertial measurement unit, which is situated on the magnetometer array, can capture the triaxial rotation of the magnetometer array in real time. As the vector sum of the triaxial geomagnetic components is constant, the rotation vector of the magnetometer array can be converted to the variation of the triaxial geomagnetic components. Thus, the triaxial geomagnetic components, which are included in the magnetometer outputs, can be separated from the sensing signals of permanent magnet even if the magnetometer array is rotating. The experimental results indicate that the magnetic tracking accuracy has been significantly improved. This method extends the application scope of the magnetic tracking approach because it enables both the magnetometer array and magnet to rotate during the tracking process. [ABSTRACT FROM AUTHOR]

Pose tracking based on a permanent magnet is not limited by line of sight. In general, a high-remanence and axially magnetized cylindrical permanent magnet is utilized as the magnetic source, which is regarded as a magnetic dipole model. However, this magnetic tracking approach cannot estimate the rotation information along the direction of the magnetic moment. Thus, only 3-D linear motion and 2-D rotational motion of the magnet can be tracked. On the other hand, inertial sensors provide effective 3-D orientation tracking. In this paper, an inertial measurement unit was attached on the surface of a permanent magnet. Then, the tracking information of these two modes was fused based on the adaptive weighted fusion algorithm. Experiments show that the full 6-D pose is acquired with an improved orientation accuracy, where the average orientation errors for $\alpha $ , $\beta $ , and $\gamma $ , obtained by the fusion algorithm, were 0.81°, 0.93°, and 1.26°, respectively. This paper is helpful to those who want to accurately track the full 6-D pose of an object. [ABSTRACT FROM AUTHOR]

We propose a method for calibration of the systems with multicomponent emitter and sensor. This method guarantees the possibility of simultaneous determination of a collection of parameters of this system. The magnetic-field induction is measured at the points of location of components of the sensor in its motion over the plane with marking specified by a single parameter (size of the cell). The objective function is formed according to the processed data of measurements and its global minimum is found by the methods of nonlinear programming. This problem has a unique solution if one of the magnetic parameters of the system, namely, the transmission coefficient of one component of the sensor or the magnetic moment of one component of the emitter, is a priori known. We propose a procedure for the evaluation of the error of positioning of the multicomponent emitter and magnetic-field sensor. [ABSTRACT FROM AUTHOR]

Magnetically manipulated untethered robot, such as an active wireless capsule endoscope, has shown great potential for controlled inspection inside the gastrointestinal tract. To enable the effective manipulation of the robot, real-time pose (position and orientation) information of the robot must be obtained as an important sensory feedback. Usually, a magnetic tracking method is used to provide the pose information. Due to the magnetic disturbance, a traditional magnetic tracking method cannot work simultaneously with the magnetic manipulation system. In this paper, a simultaneously tracking and navigation method is proposed to realize a closed-loop control of the magnetically manipulated untethered robot. The main approach is to conduct a multi-object tracking of the involved magnetic objects. With the proposed method, real-time pose information can be estimated during the manipulation, and both the tracking and manipulation are carried out by a magnetic manner. Therefore, the mobile navigation of the magnetically manipulated untethered robot can be achieved by using a pre-defined map. Experimental results verified the proposed method, and a mean position error of 1.2 mm for the passive magnet has been obtained.

Magnetic tracking is a popular technique that exploits static and low-frequency magnetic fields for positioning of quasi-stationary objects. One important system design aspect, which substantially influences the performance of the tracking system, is how to collect as much information as possible with a given number of measurements. In this work, we optimize the allocation of measurements given a large number of possible measurements of a generic magnetic tracking system that exploits time-division multiplexing. We exploit performance metrics based on the Fisher information matrix. In particular, the performance metrics measure worst-case or average performance in a measurement domain, i.e. the domain where the tracking is to be performed. An optimization problem with integer variables is formulated. By relaxing the constraint that the variables should be integer, a convex optimization problem is obtained. The two performance metrics are compared for several realistic measurement scenarios with planar transmitter constellations. The results show that the worst performance is obtained in the most distant parts of the measurement domain. Furthermore, measurement allocations optimized for worst-case performance require measurements in a larger area than measurement allocations optimized for average performance. [ABSTRACT FROM AUTHOR]