Localization accuracy of multiple magnets in a myokinetic control interface

Restoration of grasping in an upper limb amputee using the myokinetic prosthesis with implanted magnets

The loss of a hand disrupts the sophisticated neural pathways between the brain and the hand, severely affecting the level of independence of the patient and the ability to carry out daily work and social activities. Recent years have witnessed a rapid evolution of surgical techniques and technologies aimed at restoring dexterous motor functions akin to those of the human hand through bionic solutions, mainly relying on probing of electrical signals from the residual nerves and muscles. Here, we report the clinical implementation of an interface aimed at achieving this goal by exploiting muscle deformation, sensed through passive magnetic implants: the myokinetic interface. One participant with a transradial amputation received an implantation of six permanent magnets in three muscles of the residual limb. A truly self-contained myokinetic prosthetic arm embedding all hardware components and the battery within the prosthetic socket was developed. By retrieving muscle deformation caused by voluntary contraction through magnet localization, we were able to control in real time a dexterous robotic hand following both a direct control strategy and a pattern recognition approach. In just 6 weeks, the participant successfully completed a series of functional tests, achieving scores similar to those achieved when using myoelectric controllers, a standard-of-care solution, with comparable physical and mental workloads. This experience raised conceptual and technical limits of the interface, which nevertheless pave the way for further investigations in a partially unexplored field. This study also demonstrates a viable possibility for intuitively interfacing humans with robotic technologies.

To What Extent Implanting Single vs Pairs of Magnets Per Muscle Affect the Localization Accuracy of the Myokinetic Control Interface? Evidence From a Simulated Environment

OBJECTIVE

We recently proposed a new concept of human-machine interface to control hand prostheses which we dubbed the myokinetic control interface. Such interface detects muscle displacement during contraction by localizing permanent magnets implanted in the residual muscles. So far, we evaluated the feasibility of implanting one magnet per muscle and monitoring its displacement relative to its initial position. However, multiple magnets could actually be implanted in each muscle, as using their relative distance as a measure of muscle contraction could improve the system robustness against environmental disturbances.

METHODS

Here, we simulated the implant of pairs of magnets in each muscle and we compared the localization accuracy of such system with the one magnet per muscle approach, considering first a planar and then an anatomically appropriate configuration. Such comparison was also performed when simulating different grades of mechanical disturbances applied to the system (i.e., shift of the sensor grid).

RESULTS

We found that implanting one magnet per muscle always led to lower localization errors under ideal conditions (i.e., no external disturbances). Differently, when mechanical disturbances were applied, magnet pairs outperformed the single magnet approach, confirming that differential measurements are able to reject common mode disturbances.

CONCLUSION

We identified important factors affecting the choice of the number of magnets to implant in a muscle.

SIGNIFICANCE

Our results provide important guidelines for the design of disturbance rejection strategies and for the development of the myokinetic control interface, as well as for a whole range of biomedical applications involving magnetic tracking.

Detection, Location, and Classification of Multiple Dipole-like Magnetic Sources Based on L2 Norm of the Vertical Magnetic Gradient Tensor Data

In recent years, there has been a growing interest in the detection, location, and classification (DLC) of multiple dipole-like magnetic sources based on magnetic gradient tensor (MGT) data. In these applications, the tilt angle is usually used to detect the number of sources. We found that the tilt angle is only suitable for the scenario where the positive and negative signs of the magnetic sources' inclination are the same. Therefore, we map the L2 norm of the vertical magnetic gradient tensor on the arctan function, denoted as the VMGT2 angle, to detect the number of sources. Then we use the normalized source strength (NSS) to narrow the parameters' search space and combine the differential evolution (DE) algorithm with the Levenberg-Marquardt (LM) algorithm to solve the sources' locations and magnetic moments. Simulation experiments and a field demonstration show that the VMGT2 angle is insensitive to the sign of inclination and more accurate in detecting the number of magnetic sources than the tilt angle. Meanwhile, our method can quickly locate and classify magnetic sources with high precision.

Clinical implementation of a bionic hand controlled with kineticomyographic signals

Sensing the proper signal could be a vital piece of the solution to the much evading attributes of prosthetic hands, such as robustness to noise, ease of connectivity, and intuitive movement. Towards this end, magnetics tags have been recently suggested as an alternative sensing mechanism to the more common EMG signals. Such sensing technology, however, is inherently invasive and hence only in simulation stages of magnet localization to date. Here, for the first time, we report on the clinical implementation of implanted magnetic tags for an amputee's prosthetic hand from both the medical and engineering perspectives. Specifically, the proposed approach introduces a flexor-extensor tendon transfer surgical procedure to implant the tags, artificial neural networks to extract human intention directly from the implanted magnet's magnetic fields -in short KineticoMyoGraphy (KMG) signals- rather than localizing them, and a game strategy to examine the proposed algorithms and rehabilitate the patient with his new prosthetic hand. The bionic hand's ability is then tested following the patient's intended gesture type and grade. The statistical results confirm the possible utility of surgically implanted magnetic tags as an accurate sensing interface for recognizing the intended gesture and degree of movement between an amputee and his bionic hand.

Current trends in three-dimensional visualization and real-time navigation as well as robot-assisted technologies in hepatobiliary surgery

With the continuous development of digital medicine, minimally invasive precision and safety have become the primary development trends in hepatobiliary surgery. Due to the specificity and complexity of hepatobiliary surgery, traditional preoperative imaging techniques such as computed tomography and magnetic resonance imaging cannot meet the need for identification of fine anatomical regions. Imaging-based three-dimensional (3D) reconstruction, virtual simulation of surgery and 3D printing optimize the surgical plan through preoperative assessment, improving the controllability and safety of intraoperative operations, and in difficult-to-reach areas of the posterior and superior liver, assistive robots reproduce the surgeon’s natural movements with stable cameras, reducing natural vibrations. Electromagnetic navigation in abdominal surgery solves the problem of conventional surgery still relying on direct visual observation or preoperative image assessment. We summarize and compare these recent trends in digital medical solutions for the future development and refinement of digital medicine in hepatobiliary surgery.