Mechanical characterization of the varian Exact-arm and R-arm support systems for eight aS500 electronic portal imaging devices

The aim of this study is to compare the positioning accuracy at different gantry angles of two electronic portal imaging devices (EPIDs) support arm systems by using EPID difference images as a measure for displacement. This work presents a comparison of the mechanical performance of eight Varian aS500 (Varian Medical Systems, Palo Alto, CA) EPIDs, mounted using either the Varian Exact-arm or R-arm.

SMART Arm with outcome-triggered electrical stimulation:a pilot randomized clinical trial

The SMART (SensoriMotor Active Rehabilitation Training) Arm is a nonrobotic device designed to allow stroke survivors with severe paresis to practice reaching. It can be used with or without outcome-triggered electrical stimulation (OT-stim) to augment movement. The aim of this study was to evaluate the efficacy of SMART Arm training when used with or without OT-stim, in addition to usual care, as compared with usual care alone during inpatient rehabilitation.

The efficacy of SMART Arm training early after stroke for stroke survivors with severe upper limb disability:a protocol for a randomised controlled trial

Recovery of upper limb function after stroke is poor. The acute to subacute phase after stroke is the optimal time window to promote the recovery of upper limb function. The dose and content of training provided conventionally during this phase is however, unlikely to be adequate to drive functional recovery, especially in the presence of severe motor disability. The current study concerns an approach to address this shortcoming, through evaluation of the SMART Arm, a non-robotic device that enables intensive and repetitive practice of reaching by stroke survivors with severe upper limb disability, with the aim of improving upper limb function. The outcomes of SMART Arm training with or without outcome-triggered electrical stimulation (OT-stim) to augment movement and usual therapy will be compared to usual therapy alone.

Improved APF strategies for dual-arm local motion planning

Manipulator motion planning is a classic problem in robotics, with a number of complete solutions available for their motion in controlled (industrial) environments. Owing to recent technological advances in the field of robotics, there has been a significant development of more complex robots with high-fidelity sensors and more computational power. One such example has been a rise in the production of humanoid robots equipped with dual-arm manipulators which require complex motion planning algorithms. Also, the technological advances have resulted in a shift from using manipulators in strictly controlled environments, to investigating the deployment of manipulators in dynamic or unknown environments. As a result, a greater emphasis has been put on the development of local motion planners, which can provide real-time solutions to these problems. Artificial Potential Fields (APFs) is one such popular local motion planning technique, which can be applied to manipulator motion planning, however, the basic algorithm is severely prone to local minima problems. Here, two modified APF-based strategies for solving the dual-arm motion planning task in unknown environments are proposed. Both techniques make use of configuration sampling and subgoal selection to assist the APFs in avoiding these local minima scenarios. Extensive simulation results are presented to validate the efficacy of the proposed methodology.

Power Modeling and Capping for Heterogeneous ARM/FPGA SoCs

Low-power processors and accelerators that were originally designed for the embedded systems market are emerging as building blocks for servers. Power capping has been actively explored as a technique to reduce the energy footprint of high-performance processors. The opportunities and limitations of power capping on the new low-power processor and accelerator ecosystem are less understood. This paper presents an efficient power capping and management infrastructure for heterogeneous SoCs based on hybrid ARM/FPGA designs. The infrastructure coordinates dynamic voltage and frequency scaling with task allocation on a customised Linux system for the Xilinx Zynq SoC. We present a compiler-assisted power model to guide voltage and frequency scaling, in conjunction with workload allocation between the ARM cores and the FPGA, under given power caps. The model achieves less than 5% estimation bias to mean power consumption. In an FFT case study, the proposed power capping schemes achieve on average 97.5% of the performance of the optimal execution and match the optimal execution in 87.5% of the cases, while always meeting power constraints.