Abhilash Pandya

NASA TLX: Software for assessing subjective mental workload

The NASA Task Load Index (TLX) is a popular technique for measuring subjective mental workload. It relies on a multidimensional construct to derive an overall workload score based on a weighted average of ratings on six subscales: mental demand, physical demand, temporal demand, performance, effort, and frustration level. A program for implementing a computerized version of the NASA TLX is described. The software version assists in simplifying collection, postprocessing, and storage of raw data. The program collects raw data from the subject and calculates the weighted (or unweighted) workload score, which is output to a text file. The program can also be tailored to a specific experiment using a simple input text file, if desired. The program was designed in Visual Studio 2005 and is capable of running on a Pocket PC with Windows CE or on a PC with Windows 2000 or higher. The NASA TLX program is available for free download.

A Review of Active Mechanical Driving Principles of Spherical Robots

Spherical robotics is an emerging research field due to a ball’s characteristic to be holonomic, have a sealed internal environment, and rebound from collisions easily. As the research moves forward, individual groups have begun to develop unique methods of propulsion, each having distinctive engineering trade-offs: weight is sacrificed for power; speed is forfeited for control accuracy, etc. Early spherical robots operated similar to a hamster ball and had a limited torque and a high-energy loss due to internal friction. Researchers have begun to develop various novel concepts to maneuver and control this family of robot. This article is an overview of the current research directions that various groups have taken, the nomenclature used in this subdiscipline, and the various uses of the fundamental principles of physics for propelling a spherical robot.

Control of vehicle platoons for highway safety and efficient utility: Consensus with communications and vehicle dynamics

Platoon formation of highway vehicles is a critical foundation for autonomous or semiautonomous vehicle control for enhanced safety, improved highway utility, increased fuel economy, and reduced emission toward intelligent transportation systems. Platoon control encounters great challenges from vehicle control, communications, team coordination, and uncertainties. This paper introduces a new method for coordinated control of platoons by using integrated network consensus decisions and vehicle control. To achieve suitable coordination of the team vehicles based on terrain and environmental conditions, the emerging technology of network consensus control is modified to a weighted and constrained consensus-seeking framework. Algorithms are introduced and their convergence properties are established. The methodology employs neighborhood information through on-board sensors and V2V or V2I communications, but achieves global coordination of the entire platoon. The ability of the methods in terms of robustness, disturbance rejection, noise attenuation, and cyber-physical interaction is analyzed and demonstrated with simulated case studies.

Improved Telemanipulator Navigation During Display-Control Misalignments Using Augmented Reality Cues

An augmented reality (AR) cueing method designed to improve teleoperator performance under conditions of display-control misalignment is investigated. The teleoperation task was designed to mimic the operation of space robot arms, which are manipulated using hand controllers (HCs) to orient and translate the body-fixed coordinates at the end effector (EE). Cameras provide visual feedback. However, the pose of the EE seen through the camera hinders operator performance due to misalignments between the displayed EE axes and the HC axes. In this paper, the coordinate system of the EE is graphically overlaid in three dimensions on the video views with uniquely colored axes using AR. The same color scheme is used to label the corresponding axes on the HCs. Operators use these color cues to map each axis on the HCs to the corresponding colored axis of the augmented coordinates at the EE to obtain EE movement in the desired direction. Between-groups and within-participant experiments comparing EE trajectory distance, deviation from path, navigation errors, and HC axis usage were used to determine the effectiveness of the augmented coordinates over conventional teleoperation without augmented coordinates. Significant reductions in EE trajectory distance, deviation from path, navigation errors, and single-axis HC usage were observed when participants manipulated the remote robot with augmented coordinates. The results demonstrate that the use of simple AR cues in remote robot arm teleoperation is beneficial to the operator.

Diagnosis of neuroblastoma and ganglioneuroma using Raman spectroscopy.

BACKGROUND Raman spectroscopy has proven to be useful in studying premalignant and malignant lesions in adults. This is the first report to evaluate Raman spectroscopy in the diagnosis and classification of neuroblastoma in children. METHODS A biopsy or resection of fresh tissue samples from normal adrenal glands, neuroblastomas, ganglioneuromas, nerve sheath tumors, and pheochromocytoma at our hospital were equally divided between routine histology and spectroscopic studies. At least 12 spectra were collected from different regions of each sample using a Renishaw Raman microscope. Raw spectra were processed to remove noise, fluorescence, and shot noise, and then analyzed using principle component analysis and discriminant function analysis. RESULTS We collected 698 spectra from 16 neuroblastomas, 5 ganglioneuromas, 3 normal adrenal glands, 6 nerve sheath tumors, and 1 pheochromocytoma. Raman spectroscopy differentiated between normal adrenal gland, and neuroblastoma and ganglioneuroma with 100% sensitivity and 100% specificity. It correlated well with the Shimada histologic classification system with 100% sensitivity and 100% specificity. It was also able to differentiate neuroblastoma from nerve sheath tumors and pheochromocytoma with high sensitivity and specificity. CONCLUSION This technique can differentiate neuroblastoma from ganglioneuroma and other tumors. It has a potential as a noninvasive real-time diagnostic tool in classifying pediatric tumors.

Raman spectroscopy detects and distinguishes neuroblastoma and related tissues in fresh and (banked) frozen specimens

BACKGROUND Raman spectroscopy has been shown to accurately distinguish different neural crest-derived pediatric tumors. This study tests the ability of Raman spectroscopy to accurately identify cryopreserved tissue specimens using a classification algorithm designed from fresh tumor data and vice versa. METHODS Fresh specimens of neuroblastoma and other pediatric neural crest tumors were analyzed with Raman spectroscopy. After analysis, the specimens were stored at -80 degrees C. At a later date, the specimens were thawed and reanalyzed by Raman spectroscopy. A computer algorithm was used to classify the spectra from the frozen tissue against a computer model built on the fresh tissue data. This classification process was then reversed, testing fresh spectra against a model built from frozen data. RESULTS We collected 1114 spectra (862 fresh and 252 frozen) from 62 tissue samples, including 8 normal adrenal glands, 29 neuroblastomas, 14 ganglioneuromas, 8 nerve sheath tumors, and 3 pheochromocytomas. At the tissue level, frozen neuroblastoma, ganglioneuroma, nerve sheath tumor, and pheochromocytoma were distinguished from normal adrenal tissue with 100% sensitivity and specificity. Fresh tissue had the same results except for the misclassification of one specimen of nerve sheath tumor. CONCLUSIONS The representative spectra show a high correlation between fresh and frozen tissue, and a clear difference between pathologic conditions. Spectra from frozen tissue can be accurately classified against spectra from fresh tissue and vice versa. This modality makes it possible to determine in a few minutes a result that often takes 12 to 36 hours for tissue processing and consideration by a trained pathologist to achieve.

Coordinated vehicle platoon control: Weighted and constrained consensus and communication network topologies

This paper introduces a new method for enhancing highway safety and efficiency by coordinated control of vehicle platoons. One of our aims is to understand influence of communication network topologies and uncertainties on control performance. Vehicle deployment is formulated as a weighted and constrained consensus control problem. Algorithms are introduced and their convergence properties are established. The main advantages of the methods are demonstrated, including using local control to achieve a global deployment so that communication complexity is reduced; scalability to accommodate dynamic changes of the member vehicles and communication networks; robustness against road conditions and communication uncertainties.

Evaluation of pancreatic cancer with Raman spectroscopy in a mouse model.

Objectives: Detection of neoplastic changes using optical spectroscopy has been an active area of research in recent times. Raman spectroscopy is a vibrational spectroscopic technique that can be used to diagnose various tumors with high sensitivity and specificity. We evaluated the ability of Raman spectroscopy to differentiate normal pancreatic tissue from malignant tumors in a mouse model. Methods: We collected 920 spectra, 475 from 31 normal pancreatic tissue and 445 from 29 tumor nodules using a 785-nm near-infrared laser excitation. Discriminant function analysis was used for classification of normal and tumor samples. Results: Using principal component analysis, we were able to highlight subtle chemical differences in normal and malignant tissue. Using histopathology as the gold standard, Raman analysis gave sensitivities between 91% and 96% and specificities between 88% and 96%. Conclusions: Raman spectroscopy along with discriminant function analysis is a useful method to detect cancerous changes in the pancreas. Pancreatic tumors were characterized by increased collagen content and decreased DNA, RNA, and lipids components compared with normal pancreatic tissue.

Design, implementation and accuracy of a prototype for medical augmented reality

Objective: This paper is focused on prototype development and accuracy evaluation of a medical Augmented Reality (AR) system. The accuracy of such a system is of critical importance for medical use, and is hence considered in detail. We analyze the individual error contributions and the system accuracy of the prototype. Materials and Methods: A passive articulated arm is used to track a calibrated end-effector-mounted video camera. The live video view is superimposed in real time with the synchronized graphical view of CT-derived segmented object(s) of interest within a phantom skull. The AR accuracy mostly depends on the accuracy of the tracking technology, the registration procedure, the camera calibration, and the image scanning device (e.g., a CT or MRI scanner). Results: The accuracy of the Microscribe arm was measured to be 0.87 mm. After mounting the camera on the tracking device, the AR accuracy was measured to be 2.74 mm on average (standard deviation = 0.81 mm). After using data from a 2-mm-thick CT scan, the AR error remained essentially the same at an average of 2.75 mm (standard deviation = 1.19 mm). Conclusions: For neurosurgery, the acceptable error is approximately 2–3 mm, and our prototype approaches these accuracy requirements. The accuracy could be increased with a higher-fidelity tracking system and improved calibration and object registration. The design and methods of this prototype device can be extrapolated to current medical robotics (due to the kinematic similarity) and neuronavigation systems.

A Review of Camera Viewpoint Automation in Robotic and Laparoscopic Surgery

Complex teleoperative tasks, such as surgery, generally require human control. However, teleoperating a robot using indirect visual information poses many technical challenges because the user is expected to control the movement(s) of the camera(s) in addition to the robot’s arms and other elements. For humans, camera positioning is difficult, error-prone, and a drain on the user’s available resources and attention. This paper reviews the state of the art of autonomous camera control with a focus on surgical applications. We also propose potential avenues of research in this field that will support the transition from direct slaved control to truly autonomous robotic camera systems.