Motion sensing has played an important role in the study of human biomechanics as well as the entertainment industry. Although existing technologies, such as optical or inertial based motion capture systems, have relatively high accuracy in detecting body motions, they still have inherent limitations with regards to mobility and wearability. In this paper, we present a soft motion sensing suit for measuring lower extremity joint motion. The sensing suit prototype includes a pair of elastic tights and three hyperelastic strain sensors. The strain sensors are made of silicone elastomer with embedded microchannels filled with conductive liquid. To form a sensing suit, these sensors are attached at the hip, knee, and ankle areas to measure the joint angles in the sagittal plane. The prototype motion sensing suit has significant potential as an autonomous system that can be worn by individuals during many activities outside the laboratory, from running to rock climbing. In this study we characterize the hyperelastic sensors in isolation to determine their mechanical and electrical responses to strain, and then demonstrate the sensing capability of the integrated suit in comparison with a ground truth optical motion capture system. Using simple calibration techniques, we can accurately track joint angles and gait phase. Our efforts result in a calculated trade off: with a maximum error less than 8%, the sensing suit does not track joints as accurately as optical motion capture, but its wearability means that it is not constrained to use only in a lab.
This paper presents preliminary results for the design, development and evaluation of a hand rehabilitation glove fabricated using soft robotic technology. Soft actuators comprised of elastomeric materials with integrated channels that function as pneumatic networks (PneuNets), are designed and geometrically analyzed to produce bending motions that can safely conform with the human finger motion. Bending curvature and force response of these actuators are investigated using geometrical analysis and a finite element model (FEM) prior to fabrication. The fabrication procedure of the chosen actuator is described followed by a series of experiments that mechanically characterize the actuators. The experimental data is compared to results obtained from FEM simulations showing good agreement. Finally, an open-palm glove design and the integration of the actuators to it are described, followed by a qualitative evaluation study.
In this paper, we describe our prototype of an ultrasound guidance system to address the need for an easy-touse, cost-effective, and portable technology to improve ultrasound-guided procedures. The system consists of a lockable, articulating needle guide that attaches to an ultrasound probe and a user-interface that provides real-time visualization of the predicted needle trajectory overlaid on the ultrasound image. Our needle guide ensures proper needle alignment with the ultrasound imaging plane. Moreover, the calculated needle trajectory is superimposed on the real-time ultrasound image, eliminating the need for the practitioner to estimate the target trajectory, and thereby reducing injuries from needle readjustment. Finally, the guide is lockable to prevent needle deviation from the desired trajectory during insertion. This feature will also allow the practitioner to free one hand to complete simple tasks that usually require a second practitioner to perform. Overall, our system eliminates the experience required to develop the fine hand movement and dexterity needed for traditional ultrasound-guided procedures. The system has the potential to increase efficiency, safety, quality, and reduce costs for a wide range of ultrasound-guided procedures. Furthermore, in combination with portable ultrasound machines, this system will enable these procedures to be more easily performed by unskilled practitioners in non-ideal situations such as the battlefield and other disaster relief areas.
The main challenges of Computed Tomography (CT)-guided organ puncture are the mental registration of the medical imaging data with the patient anatomy, required when planning a trajectory, and the subsequent precise insertion of a needle along it. An interventional telerobotic system, such as Robopsy, enables precise needle insertion, however, in order to minimize procedure time and number of CT scans, this system should be driven by an interface that is directly integrated with the medical imaging data. In this study we have developed and evaluated such an interface that provides the user with a point-and-click functionality for specifying the desired trajectory, segmenting the needle and automatically calculating the insertion parameters (angles and depth). In order to highlight the advantages of such an interface, we compared robotic-assisted targeting using the old interface (non-image-based) where the path planning was performed on the CT console and transferred manually to the interface with the targeting procedure using the new interface (image-based). We found that the mean procedure time (n=5) was 22±5 min (non-image-based) and 19±1 min (image-based) with a mean number of CT scans of 6±1 (non-image-based) and 5±1 (image-based). Although the targeting experiments were performed in gelatin with homogenous properties our results indicate that an image-based interface can reduce procedure time as well as number of CT scans for percutaneous needle biopsies.
Computed tomography (CT) guided percutaneous punctures of the liver for cancer diagnosis and therapy (e.g. tumor biopsy, radiofrequency ablation) are well-established procedures in clinical routine. One of the main challenges related to these interventions is the accurate placement of the needle within the lesion. Several navigation concepts have been introduced to compensate for organ shift and deformation in real-time, yet, the operator error remains an important factor influencing the overall accuracy of the developed systems. The aim of this study was to investigate whether the operator error and, thus, the overall insertion error of an existing navigation system could be further reduced by replacing the user with the medical robot Robopsy. For this purpose, we performed navigated needle insertions in a static abdominal phantom as well as in a respiratory liver motion simulator and compared the human operator error with the targeting error performed by the robot. According to the results, the Robopsy driven needle insertion system is able to more accurately align the needle and insert it along its axis compared to a human operator. Integration of the robot into the current navigation system could thus improve targeting accuracy in clinical use.