Robotic external ventricular drain placement for acute neurosurgical care in low-resource settings: feasibility considerations and a prototype design

OBJECTIVE Emergency neurosurgical care in lower-middle-income countries faces pronounced shortages in neurosurgical personnel and infrastructure. In instances of traumatic brain injury (TBI), hydrocephalus, and subarachnoid hemorrhage, the timely placement of external ventricular drains (EVDs) strongly dictates prognosis and can provide necessary stabilization before transfer to a higher-level center of care that has access to neurosurgery. Accordingly, the authors have developed an inexpensive and portable robotic navigation tool to allow surgeons who do not have explicit neurosurgical training to place EVDs. In this article, the authors aimed to highlight income disparities in neurosurgical care, evaluate access to CT imaging around the world, and introduce a novel, inexpensive robotic navigation tool for EVD placement. METHODS By combining the worldwide distribution of neurosurgeons, CT scanners, and gross domestic product with the incidence of TBI, meningitis, and hydrocephalus, the authors identified regions and countries where development of an inexpensive, passive robotic navigation system would be most beneficial and feasible. A prototype of the robotic navigation system was constructed using encoders, 3D-printed components, machined parts, and a printed circuit board. RESULTS Global analysis showed Montenegro, Antigua and Barbuda, and Seychelles to be primary candidates for implementation and feasibility testing of the novel robotic navigation system. To validate the feasibility of the system for further development, its performance was analyzed through an accuracy study resulting in accuracy and repeatability within 1.53 ± 2.50 mm (mean ± 2 × SD, 95% CI). CONCLUSIONS By considering regions of the world that have a shortage of neurosurgeons and a high incidence of EVD placement, the authors were able to provide an analysis of where to prioritize the development of a robotic navigation system. Subsequently, a proof-of-principle prototype has been provided, with sufficient accuracy to target the ventricles for EVD placement.

Laboratory for Validation of Rolling-Resistance Models

In this paper, a versatile drum setup for measuring rolling resistance of small wheels is presented. The purpose is to provide a flexible setup for testing of models for rolling resistance under controlled circumstances. To demonstrate this, measurements of rolling resistance with a series of sandpapers of different grit sizes representing surface textures were carried out. The measurements show a clear increase in the rolling-resistance coefficient with increasing surface roughness, rolling speed and load. Numerical calculations in the time domain for a visco-elastic contact model run on equivalent surfaces agree with the trends found experimentally. We conclude that this approach to simplifying the experiment in order to obtain a high degree of control, accuracy and repeatability is useful for validating and testing models for calculating the rolling resistance for a given surface texture.

Oil as an Enabler for Efficient Materials Removal in Three-Dimensional Scanning Probe Microscopy Applications

The ever-increasing complexity of semiconductor devices requires innovative three-dimensional materials characterization techniques for confined volumes. Multiple atomic force microscopy (AFM)-based methodologies, using a slice-and-measure approach have been proposed to meet this demand. They consist of scanning AFM probes that erode locally the sample’s material at a relatively high load while sensing with the secondary AFM channel, thus accessing in-depth information compared to the standard surface-limited analysis. Nonetheless, the rapid tip apex wear caused by the high forces involved, and the debris accumulation at the tip apex and inside/around the scan area, have been identified as major limitations to the accuracy and repeatability of the existing tomographic AFM sensing methods. Here we explore the use of oil as a suitable medium to overcome some of the issues such as the scan debris accumulation and the removal variability when working in air. We show how the use of oil preserves the tomographic operation while improving the efficiency in material removal for large depth sensing at a reduced debris accumulation. This is reported by comparing the results between air and oil environments, where the removal rate, depth accuracy, and tip-contamination are benchmarked. Finally, we provide the first demonstration of electrical AFM sensing using scanning spreading resistance microscopy (SSRM) in oil.

The Internet of Sensors IoS in Oil and Gas Industry

In a highly sensitivity oil and gas upstream conditions, there is a need for a real-time interaction platform to cope with harsh environment. The oil and gas business faces data validity constraints in terms of reliability, accuracy, and repeatability to name a few. The Internet of Sensors (IoS), with appropriate utilization, will play a major role in the industry's digital transformation. Predetermined IoS platforms with applicable characteristics are functioning in critical oil and gas environment applications. For example, some oil and gas wells produces harmful gases, like hydrogen sulfide (H2S). Fiber-optic sensors can be used as a leak detection tool for H2S resistance to inform oil and gas curfew if harmful gas is detected at the well site using cloud computing. Scale and corrosion monitoring of external pipelines is one of the integrity challenges. Ultrasonic sensors are embedding for real-time scale thickness feedback and corrosion monitoring by utilizing wireless transmission directly to end-user devices. A paradigm shift is happening with the IoS applications in oil and gas operations for sensitivity, reliability, and accuracy that will add intelligence, smart decisions, and control to the operational landscape. A comprehensive review of the art in oil and gas IoS presented in this paper. The target is to evaluate state-of-the-art IoS platforms for hazardous environments such as oil and gas facilities in terms of type of sensors used, applicability, functionalities, linearity, and accuracy, type of output signals, outputs range, and materials used. This work establishes classification and comparison of the IoS for better data collection, communication, connectivity, observation, and reporting in the world of oil and gas sensors. The IoS platforms classified and compared in tables consisting of different characteristics for the best-suited IoS platform designs in oil and gas appliance applications. This will provide references for IoS design engineers.

Robust control of robot manipulators with an adaptive fuzzy unmodelled parameter estimation law

Summary For robot manipulators, there are two types of disturbances. One is model parametric uncertainty; the other is unmodelled parameters such as joint friction forces and external disturbances. Unmodelled joint frictions and external disturbances reduce performance in terms of positioning accuracy and repeatability. In order to compensate for unmodelled parameters, the design of a new controller is considered. First, the modelled and unmodelled parameters are included in a dynamic model. Then, based on the dynamic model, a new Lyapunov function is developed. After that, new nonlinear joint friction and external disturbance estimation laws are derived as an analytic solution from the Lyapunov function; thus, the stability of the closed system is guaranteed. Better values of the adaptive dynamic compensators can be extracted by fuzzy rules according to the tracking error. Limitations and knowledge about friction and external disturbances are not required for the design of the controller. The controller compensates for all possible model parameter uncertainties, all possible unknown joint frictions and external disturbances.

Feasibility and Performance Validation of a Leap Motion Controller for Upper Limb Rehabilitation

The leap motion controller is a commercial low-cost marker-less optical sensor that can track the motion of a human hand by recording various parameters. Upper limb rehabilitation therapy is the treatment of people having upper limb impairments, whose recovery is achieved through continuous motion exercises. However, the repetitive nature of these exercises can be interpreted as boring or discouraging while patient motivation plays a key role in their recovery. Thus, serious games have been widely used in therapies for motivating patients and making the therapeutic process more enjoyable. This paper explores the feasibility, accuracy, and repeatability of a leap motion controller (LMC) to be applied in combination with a serious game for upper limb rehabilitation. Experimental feasibility tests are carried out by using an industrial robot that replicates the upper limb motions and is tracked by using an LMC. The results suggest a satisfactory performance in terms of tracking accuracy although some limitations are identified and discussed in terms of measurable workspace.

Transcranial Sonography in the Diagnosis of Pituitary Tumor—A Direct Comparison With MRI

BackgroundTranscranial sonography (TCS) is a convenient tool for detecting certain brain diseases, such as brain tumors. Few studies have reported on the use of TCS in the area of Sella turcica. The accuracy and repeatability of Sella turcica with or without pituitary tumor is not clear.PurposeThis study aimed to investigate the feasibility and accuracy of TCS to measure the size of Sella turcica according to the measurement in MRI and determine its diagnostic performance in individuals with pituitary tumor.Materials and MethodsIn this cross-sectional comparative study, healthy volunteers and patients with pituitary tumor were enrolled for examination of TCS and MRI between October 2020 and July 2021. The transverse diameter (D1, cm) of Sella turcica and the volume of the pituitary tumor were measured by TCS and MRI, respectively, and compared by using Student’s t-test or Mann–Whitney test, using the receiver operating characteristic (ROC) curve to analyze the diagnostic value of D1 in TCS for pituitary tumor.ResultsA total of 75 healthy volunteers and 51 patients with pituitary tumor were evaluated. In healthy volunteers, the mean D1 was 1.30 ± 0.35 (range, 0.82–3.22) by TCS and 1.32 ± 0.29 (range, 0.94–3.02) by MRI (P = 0.054). In patients with pituitary tumor, the mean D1 was 2.0 ± 0.65 (range, 0.90–3.48) by TCS and 2.42 ± 1.0 (range, 0.80–4.70) by MRI (P = 0.000). The median measurement volume was 4.41 and 6.59 cm3 in TCS and MR, respectively (P = 0.000). The mean D1 was 1.31 ± 0.35 in healthy volunteers and 2.0 ± 0.65 cm in patients with pituitary tumor (P = 0.000). In the ROC curve analysis, the area under the curve was 0.836, and the optimal cutoff value (1.56) exhibited a sensitivity and specificity of 67.31 and 88.0%, respectively.ConclusionThe consistency between the two imaging technologies performed well in D1 measurement, while the volume of the pituitary tumor was smaller as assessed by TCS than by MRI. D1 in TCS had good diagnostic performance in pituitary tumor.

In Vitro Simulation of Shoulder Motion Driven by 3D Scapular and Humeral Kinematics

In vitro simulation of 3D shoulder motion using in vivo kinematics obtained from human subjects allows investigation of clinical conditions in the context of physiologically relevant biomechanics. Herein we present a framework for laboratory simulation of subject-specific kinematics that combines individual 3D scapular and humeral control in cadavers. The objectives were to: 1) robotically simulate 7 healthy subject-specific 3D scapulothoracic and glenohumeral kinematic trajectories in 6 cadavers, 2) characterize system performance using kinematic orientation accuracy and repeatability, and muscle force repeatability metrics and 3) analyze effects of input kinematics and cadaver specimen variability. Using an industrial robot to orient the scapula range of motion (ROM), errors with repeatability of ±0.1 mm and <0.5° were achieved. Using a custom robot and a trajectory prediction algorithm to orient the humerus relative to the scapula, orientation accuracy for glenohumeral elevation, plane of elevation, and axial rotation of <3° mean absolute error was achieved. Kinematic accuracy was not affected by varying input kinematics or cadaver specimens. Muscle forces over 5 repeated setups showed variability typically <33% relative to the overall simulations. Varying cadaver specimens and subject-specific human motions showed effects on muscle forces, illustrating that the system was capable of differentiating changes in forces due to input conditions. The anterior and middle deltoid, specifically, showed notable variations in patterns across the ROM that were affected by subject-specific motion. This machine provides a platform...(truncated to fit word count, missing text in main PDF includes R2 changes).