Making Bipedal Robot Experiments Reproducible and Comparable: The Eurobench Software Approach

This study describes the software methodology designed for systematic benchmarking of bipedal systems through the computation of performance indicators from data collected during an experimentation stage. Under the umbrella of the European project Eurobench, we collected approximately 30 protocols with related testbeds and scoring algorithms, aiming at characterizing the performances of humanoids, exoskeletons, and/or prosthesis under different conditions. The main challenge addressed in this study concerns the standardization of the scoring process to permit a systematic benchmark of the experiments. The complexity of this process is mainly due to the lack of consistency in how to store and organize experimental data, how to define the input and output of benchmarking algorithms, and how to implement these algorithms. We propose a simple but efficient methodology for preparing scoring algorithms, to ensure reproducibility and replicability of results. This methodology mainly constrains the interface of the software and enables the engineer to develop his/her metric in his/her favorite language. Continuous integration and deployment tools are then used to verify the replicability of the software and to generate an executable instance independent of the language through dockerization. This article presents this methodology and points at all the metrics and documentation repositories designed with this policy in Eurobench. Applying this approach to other protocols and metrics would ease the reproduction, replication, and comparison of experiments.This study is supported by the European Union’s Horizon 2020 research and innovation program under Grant Agreement no 779963, project Eurobench

Characteristics of prosthetic joint infections due to Enterococcus sp. and predictors of failure: a multi-national study

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Static magnetic field stimulation over motor cortex modulates resting functional connectivity in humans

Focal application of transcranial static magnetic field stimulation (tSMS) over the human motor cortex induces local changes in cortical excitability. Whether tSMS can also induce distant network effects, and how these local and distant effects may vary over time, is currently unknown. In this study, we applied 10 min tSMS over the left motor cortex of healthy subjects using a real/sham parallel design. To measure tSMS effects at the sensori-motor network level, we used resting-state fMRI. Real tSMS, but not sham, reduced functional connectivity within the stimulated sensori-motor network. This effect of tSMS showed time-dependency, returning to sham levels after the first 5 min of fMRI scanning. With 10 min real tSMS over the motor cortex we did not observe effects in other functional networks examined (default mode and visual system networks). In conclusion, 10 min of tSMS over a location within the sensori-motor network reduces functional connectivity within the same functional network