This article illuminates the major and often overlooked challenge of untethering soft robotic systems through the context of recent work, in which soft robotic gripper technology enabled by jamming of granular media was applied to a prosthetic jamming terminal device (PJTD). The PJTD's technical and market feasibility was evaluated in a pilot study with two upper-limb amputees. A PJTD prototype was tested against a commercial device (Motion Control electric terminal service with a one degree-of-freedom pinching mechanism) using two existing hand function tests: the first quantified the device's speed in picking and placing small blocks and the second evaluated a person's ability to perform activities of daily living (ADLs). The PJTD prototype performed slightly slower than its commercial counterpart in the first test. While both participants successfully completed all the ADLs with both devices in the second test, the commercial device scored marginally higher. Results suggested that PJTD can have potential benefits over existing terminal devices, such as providing the capability to firmly grasp tools due to the ability of PJTD to conform to arbitrary surfaces and reducing compensatory shoulder movements due to its axisymmetric design. Some downsides were that users reported fatigue while operating the PJTD, as most operations require pushing the PJTD against target objects to adequately conform to them. The greatest drawback for the PJTD is also a major roadblock preventing a number of soft robotic research projects from making an impact in real-world applications: pneumatic technology required for operating the PJTD is currently too large and heavy to enable compact untethered operation.

This paper presents the development, preclinical evaluation, and preliminary clinical study of a robotic system for targeted transperineal prostate biopsy under direct interventional magnetic resonance imaging (MRI) guidance. The clinically integrated robotic system is developed based on a modular design approach, comprised of surgical navigation application, robot control software, MRI robot controller hardware, and robotic needle placement manipulator. The system provides enabling technologies for MRI-guided procedures. It can be easily transported and setup for supporting the clinical workflow of interventional procedures, and the system is readily extensible and reconfigurable to other clinical applications. Preclinical evaluation of the system is performed with phantom studies in a 3 Tesla MRI scanner, rehearsing the proposed clinical workflow, and demonstrating an in-plane targeting error of 1.5mm. The robotic system has been approved by the institutional review board (IRB) for clinical trials. A preliminary clinical study is conducted with the patient consent, demonstrating the targeting errors at two biopsy target sites to be 4.0mm and 3.7mm, which is sufficient to target a clinically significant tumor foci. First-in-human trials to evaluate the system’s effectiveness and accuracy for MR image-guide prostate biopsy are underway.

Surface electromyogram-controlled powered hand/wrist prostheses return partial upper-limb function to limb-absent persons. Typically, one degree of freedom (DoF) is controlled at a time, with mode switching between DoFs. Recent research has explored using large-channel EMG systems to provide simultaneous, independent and proportional (SIP) control of two joints—but such systems are not practical in current commercial prostheses. Thus, we investigated site selection of a minimum number of conventional EMG electrodes in an EMG-force task, targeting four sites for a two DoF controller. In a laboratory experiment with 10 able-bodied subjects and three limb-absent subjects, 16 electrodes were placed about the proximal forearm. Subjects produced 1-DoF and 2-DoF slowly force-varying contractions up to 30% maximum voluntary contraction (MVC). EMG standard deviation was related to forces via regularized regression. Backward stepwise selection was used to retain those progressively fewer electrodes that exhibited minimum error. For 1-DoF models using two retained electrodes (which mimics the current state of the art), subjects had average RMS errors of (depending on the DoF): 7.1–9.5 %MVC for able-bodied and 13.7–17.1 %MVC for limb-absent subjects. For 2-DoF models, subjects using four electrodes had errors on 1-DoF trials of 6.7–8.5 %MVC for able-bodied and 11.9–14.0 %MVC for limb-absent; and errors on 2-DoF trials of 9.9–11.2 %MVC for able-bodied and 15.8–16.7 %MVC for limb-absent subjects. For each model, retaining more electrodes did not statistically improve performance. The able-bodied results suggest that backward selection is a viable method for minimum error selection of as few as four electrode sites for these EMG-force tasks. Performance evaluation in a prosthesis control task is a necessary and logical next step for this site selection method.

The use of magnetic resonance imaging (MRI) for guiding robotic surgical devices has shown great potential for performing precisely targeted and controlled interventions. To fully realize these benefits, devices must work safely within the tight confines of the MRI bore without negatively impacting image quality. Here we expand on previous work exploring MRI guided robots for neural interventions by presenting the mechanical design and assessment of a device for positioning, orienting, and inserting an interstitial ultrasound-based ablation probe. From our previous work we have added a 2 degree of freedom (DOF) needle driver for use with the aforementioned probe, revised the mechanical design to improve strength and function, and performed an evaluation of the mechanism’s accuracy and effect on MR image quality. The result of this work is a 7-DOF MRI robot capable of positioning a needle tip and orienting it’s axis with accuracy of 1.37 ± 0.06mm and 0.79° ± 0.41°, inserting it along it’s axis with an accuracy of 0.06 ± 0.07mm, and rotating it about it’s axis to an accuracy of 0.77° ± 1.31°. This was accomplished with no significant reduction in SNR caused by the robot’s presence in the MRI bore, ≤ 10.3% reduction in SNR from running the robot’s motors during a scan, and no visible paramagnetic artifacts.

Intra-operative imaging is sometimes available to assist needle biopsy, but typical open-loop insertion does not account for unmodeled needle deflection or target shift. Closed-loop image-guided compensation for deviation from an initial straight-line trajectory through rotational control of an asymmetric tip can reduce targeting error. Incorporating robotic closed-loop control often reduces physician interaction with the patient, but by pairing closed-loop trajectory compensation with hands-on cooperatively controlled insertion, a physician's control of the procedure can be maintained while incorporating benefits of robotic accuracy. A series of needle insertions were performed with a typical 18G needle using closed-loop active compensation under both fully autonomous and user-directed cooperative control. We demonstrated equivalent improvement in accuracy while maintaining physician-in-the-loop control with no statistically significant difference (p > 0.05) in the targeting accuracy between any pair of autonomous or individual cooperative sets, with average targeting accuracy of 3.56 mm. With cooperatively controlled insertions and target shift between 1 and 10 mm introduced upon needle contact, the system was able to effectively compensate up to the point where error approached a maximum curvature governed by bending mechanics. These results show closed-loop active compensation can enhance targeting accuracy, and that the improvement can be maintained under user directed cooperative insertion.

While the interaction between a needle and the surrounding tissue is known to cause a significant targeting error in prostate biopsy leading to false-negative results, few studies have demonstrated how it impacts in the actual procedure. We performed a pilot study on robot-assisted MRI-guided prostate biopsy with an emphasis on the in-depth analysis of the needle-tissue interaction in vivo. The data were acquired during in-bore transperineal prostate biopsies in patients using a 4 degrees-of-freedom (DoF) MRI-compatible robot. The anatomical structures in the pelvic area and the needle path were reconstructed from MR images, and quantitatively analyzed. We analyzed each structure individually and also proposed a mathematical model to investigate the influence of those structures in the targeting error using the mixed-model regression. The median targeting error in 188 insertions (27 patients) was 6.3 mm. Both the individual anatomical structure analysis and the mixed-model analysis showed that the deviation resulted from the contact between the needle and the skin as the main source of error. On contrary, needle bending inside the tissue (expressed as needle curvature) did not vary among insertions with targeting errors above and below the average. The analysis indicated that insertions crossing the bulbospongiosus presented a targeting error lower than the average. The mixed-model analysis demonstrated that the distance between the needle guide and the patient skin, the deviation at the entry point, and the path length inside the pelvic diaphragm had a statistically significant contribution to the targeting error (p < 0.05). Our results indicate that the errors associated with the elastic contact between the needle and the skin were more prominent than the needle bending along the insertion. Our findings will help to improve the preoperative planning of transperineal prostate biopsies.

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A significant hurdle of accurate needle tip placement in percutaneous needle-based prostate interventions is unmodeled needle deflection and tissue deformation during insertion. This paper introduces a robotic platform for developing synergistic, cooperatively controlled needle insertion algorithms decoupled from closed-loop image-guided needle steering. Shared control of the surgical workspace through human-robot synergy creates a balance between the accuracy of robotic autonomy while still providing ultimate control of the procedure to the physician. Validation tests were performed using camera-based image-guided feedback control of needle steering with cooperative hands-on needle insertion. Locations were targeted inside a transparent gelatin phantom with an average total error of 2.68 ± 0.34mm and in-plane error of 2.59 ± 0.30mm.