In this thesis the development of a remotely controlled system used for visual monitoring of surgical procedures at distant locations in described. The system has been developed for laboratory testing, where in the longer term it is to be verified under field conditions. Using existing technology in areas of serial communication and videoconferencing in a new configuration, it has been possible to achieve such a system. The system is intended to assist in performing complex surgical procedures at remote locations where specialist surgeons are normally unavailable. With the prototype system developed in this thesis, a remotely based general surgeon performing an operation can consult and interact with other specialist surgeons through visual operation and voice communications. The teleoperated system consists of two computers, a commercially available robot and a videoconferencing unit / Master of Engineering (Hons)

Thesis (M.S.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2005. Directed by Stephen DeWeerth. / Dr. Stephen DeWeerth, Committee Chair ; Dr. Robert Butera, Committee Member ; Dr. Lena Ting, Committee Member. Includes bibliographical references.

Thesis (Ph. D.)--University of Notre Dame, 2004. / Includes bibliographical references (leaves 277-280). Also available online (PDF file) by a subscription to the set or by purchasing the individual file.

Unilateral deficits resulting from stroke manifest as reduced velocity, decreased cadence and asymmetries in temporal, spatial and force parameters during ambulation. Gait asymmetries and compensatory strategies employed during gait result in a higher mechanical energy cost that limits activity and community participation. Despite conventional rehabilitation efforts, individuals often remain with chronic gait deficits after stroke. Robotic-based therapies have been developed as an alternative to conventional rehabilitation. These therapies offer the means to provide task-specific training at an intensity greater than that of conventional approaches; however, to date outcomes have been similar to that of conventional training. One factor potentially contributing to the limited efficacy of robotic training is the active-assist control strategy that is often employed. This type of training strategy reduces the users’ engagement in the learning process and limits skilled learning. The tethered pelvic assist device (TPAD) is a robotic device that employs actuated tethers at the pelvis to guide the user along a pre-set movement trajectory. While other robotic devices restrict movement to a fixed trajectory, the TPAD promotes shifting weight onto the paretic limb, but permits users to freely move the limb to navigate spatiotemporal aspects of training independently. This allows individuals to participate in the problem-solving process required for motor learning to occur, facilitating a more active role in the motor task itself, and thus promoting learning. Earlier work utilized the TPAD to reduce gait asymmetry in a population of individuals in the chronic phase after stroke in a single training session (Bishop et al., 2015; Vashista, 2015). Results demonstrated an increase in propulsive forces of the affected limb as a result of the intervention, but these gains did not transfer to overground gait. A follow up study explored the feasibility and efficacy of two different training strategies using the TPAD (Bishop et al., 2017). Both training strategies proved feasible and similarly efficacious. The current work examines the feasibility and preliminary efficacy of a five-day intervention using the TPAD with faded visual feedback and a short bout of task-specific overground training to reduce gait asymmetry in a population of individuals at least six months after stroke. Participants underwent a series of three Pre Test assessments within a one-week interval prior to initiating the intervention. Training occurred over five consecutive days, with a Post Test assessment administered on conclusion of Day 5 of training. A one-week Follow Up assessment was also recorded. Results demonstrated this intervention coupling TPAD training with additional tenets of motor learning including visual feedback and salient task-specific overground training was feasible in terms of safety, tolerance and adherence. Further, while participant’s load asymmetry was not significantly reduced on the treadmill from Baseline to Post Training (p >0.05), there was a significant improvement in stance symmetry during overground gait (F = 8.498, p = 0.002). These results suggest that the integration of motor learning tenets with robotic TPAD training was useful in facilitating gains to overground walking. Implications to the broader scope of robotic training suggest that creating an environment in which the user plays a more active role is useful at maximizing effects of robotic training. Future work should include comparison groups (TPAD treadmill training, overground training, and combined TPAD and overground training) with a more robust sample size for a longer duration of training to parse out contributing factors to overground gains. Future work should also consider a longer training and follow up interval in an effort to determine whether individuals are able to maintain improvements longer than the immediate post training period.

Upper body control is required to complete many daily tasks. One needs to stabilize the head and trunk over the pelvis, as one shifts the center of mass to interact with the world. While healthy individuals can perform activities that require leaning, reaching, and grasping readily, those with neurological and musculoskeletal disorders present with control deficits. These deficits can lead to difficulty in shifting the body center of mass away from the stable midline, leading to functional limitations and a decline in the quality of activity. Often these patient groups use canes, walkers, and wheelchairs for support, leading to occasional strapping or joint locking of the body for trunk stabilization. Current rehabilitation strategies focus on isolated components of stability. This includes strengthening, isometric exercises, hand-eye coordination tasks, isolated movement, and proprioceptive training. Although all these components are evidence based and directly correlate to better stability, motor learning theories such as those by Nikolai Bernstein, suggest that task and context specific training can lead to better outcomes. In specific, based on our experimentation, we believe functional postural exploration, while encompassing aspects of strengthening, hand-eye coordination, and proprioceptive feedback can provide better results. In this work, we present two novel cable robotic platforms for seated and standing posture training. The Trunk Support Trainer (TruST) is a platform for seated posture rehabilitation that provides controlled external wrench on the human trunk in any direction in real-time. The Stand Trainer is a platform for standing posture rehabilitation that can control the trunk, pelvis, and knees, simultaneously. The system works through the use of novel force-field algorithms that are modular and user-specific. The control uses an assist-as-needed strategy to apply forces on the user during regions of postural instability. The device also allows perturbations for postural reactive training. We have conducted several studies using healthy adult populations and pilot studies on patient groups including cerebral palsy, cerebellar ataxia, and spinal cord injury. We propose new training methods that incorporate motor learning theory and objective interventions for improving posture control. We identify novel methods to characterize posture in form of the “8-point star test”. This is to assess the postural workspace. We also demonstrate novel methods for functional training of posture and balance. Our results show that training with our robotic platforms can change the trunk kinematics. Specifically, healthy adults are able to translate the trunk further and rotate the trunk more anteriorly in the seated position. In the standing position, they can alter their reach strategy to maintain the upper trunk more vertically while reaching. Similarly, Cerebral Palsy patients improve their trunk translations, reaching workspace, and maintain a more vertical posture after training, in the seated position. Our results also showed that an Ataxia patient was able to improve their reaching workspace and trunk translations in the standing position. Finally, our results show that the robotic platforms can successfully reduce trunk and pelvis sway in spinal cord injury patients. The results of the pilot studies suggest that training with our robotic platforms and methods is beneficial in improving trunk control.

Whole-cell patch clamp electrophysiology of neurons in vivo enables the recording of electrical events in cells with great precision, and supports a wide diversity of morphological and molecular analysis experiments important for the understanding of single-cell and network functions in the intact brain. However, high levels of skill are required in order to perform in vivo patching, and the process is time-consuming and painstaking. Robotic systems for in vivo patching would not only empower a great number of neuroscientists to perform such experiments, but would also open up fundamentally new kinds of experiment enabled by the resultant high throughput and scalability. We discovered that in vivo blind whole cell patch clamp electrophysiology could be implemented as a straightforward algorithm and developed an automated robotic system that was capable of performing this algorithm. We validated the performance of the robot in both the cortex and hippocampus of anesthetized mice. The robot achieves yields, cell recording qualities, and operational speeds that are comparable to, or exceed, those of experienced human investigators. Building upon this framework, we developed a multichannel version of “autopatcher” robot capable establishing whole cell patch clamp recordings from pairs and triplets of neurons in the cortex simultaneously. These algorithms can be generalized to control arbitrarily large number of electrodes and the high yield, throughput and automation of complex set of tasks results in a practical solution for conducting patch clamp recordings in potentially dozens of interconnected neurons in vivo.

The objective of this research effort is to further rehabilitation techniques for children by developing and validating the core technologies needed to integrate therapy instruction with child-robot play interaction in order to improve upper-arm rehabilitation. Using computer vision techniques such as Motion History Imaging (MHI), Multimodal Mean, edge detection, and Random Sample Consensus (RANSAC), movements can be quantified through robot observation. Also incorporating three-dimensional data obtained via an infrared projector coupled with a Principle Component Analysis (PCA), depth information can be utilized to create a robust algorithm. Finally, utilizing prior knowledge regarding exercise data, physical therapeutic metrics, and novel approaches, a mapping to therapist instructions can be created allowing robotic feedback and intelligent interaction.

Robotic haptics has been and continues to be an area of intense research, primarily in medical and exploration industries. This is due to an ability to provide high data throughput between human and machine. In medical applications, it is possible to detect and compensate errors such as a hand tremor in a surgeon. It is possible to apply scaling factors to assist in microsurgery situations, and can allow leading experts to perform procedures from anywhere on the globe. As part of a collaboration to develop a robotic method of femur fracture realignment between Auckland University, Auckland District Health Board, and Massey University, the project seeks to provide a haptic driven HMI for the realignment system. To reduce construction required, an existing manipulation arm (Mitsubishi RV-M1) is used as the hardware interface device. A new motor controller is designed to provide additional functionality as the standard controller provides no force control or real-time feedback of position. A software interface is developed (using version 3 of the C# programming language, developed by Microsoft, and version 3.5 of the Microsoft .NET Framework) with the ultimate specification of becoming being the primary interface platform for the realignment system. The interface has been implemented to the point of providing a simulated environment for the haptic device. It was found that the configuration of the RV-M1 provides a tight area of high dexterity as a haptic device, and as such, similar kinematic configurations are poor candidates for practical implementation. The implication of which, is that a new manipulator should be designed which grants a larger volume of high dexterity space.

Thesis (M. E.) (Honours) -- University of Western Sydney, 2002. / Thesis submitted in fulfilment of the requirements for the degree of Master of Engineering (Honours), University of Western Sydney, School of Engineering & Industrial Design, March 2002. Bibliography : p. 99-104.

Thesis (M.S.)--Oregon State University, 2009. / Printout. Includes bibliographical references (leaves 68-71). Also available on the World Wide Web.