Trafačka: Young Artists in an Alternative Space (Life of D.I.Y.)

This paper documents the functions and internal structure of Trafačka, an experimental arts space located in the Prague 9 district. There is very little research on the presence and significance of alternative culture in Prague today, and the term itself is difficult to define. Using personal interviews conducted by the author and some background research on Czech alternative culture and spaces, the study highlights the stories of the residents and artists of Trafačka in light of the debate on alternative culture. The author explains how Trafačka is an example alternative space and describes the complexities of being separated from other mainstream art institutions. The conclusion expresses the relevance of Trafačka for young and emerging artists in Prague today

IT’S ABOUT HOW WELL YOU USE IT: SKATING STRIDE IN NOVICE, INTERMEDIATE AND ADVANCED INLINE SKATERS

Adequate skating technique is imperative to roller sports. Characteristics that differ between inline skating competencies have not been addressed. This study assessed skating parameters associated with coaching cues across three levels of experience. Inline-skaters (n=24) were divided into novice, intermediate and advanced groups based on experience. Skate trajectories were captured through 3D analysis as participants skated maximally down a 10 m runway. One-way ANOVA was used to compare differences for the skating parameters between skill levels. Significant differences (P < 0.016) were found for stride-width, recovery, stride-width-recovery and stride-length-recovery and stride rate. Results have implications for delivery of coaching and skating skill development

IT’S ABOUT HOW WELL YOU USE IT: SKATING STRIDE IN NOVICE, INTERMEDIATE AND ADVANCED INLINE SKATERS

Adequate skating technique is imperative to roller sports. Characteristics that differ between inline skating competencies have not been addressed. This study assessed skating parameters associated with coaching cues across three levels of experience. Inline-skaters (n=24) were divided into novice, intermediate and advanced groups based on experience. Skate trajectories were captured through 3D analysis as participants skated maximally down a 10 m runway. One-way ANOVA was used to compare differences for the skating parameters between skill levels. Significant differences (P < 0.016) were found for stride-width, recovery, stride-width-recovery and stride-length-recovery and stride rate. Results have implications for delivery of coaching and skating skill development

Online Classifier Adaptation in Brain-Computer Interfaces

Brain-computer interfaces (BCIs) aim to provide a new channel of communication by enabling the subject to control an external systems by using purely mental commands. One method of doing this without invasive surgical procedures is by measuring the electrical activity of the brain on the scalp through electroencephalography (EEG). A major obstacle to developing complex EEG-based BCI systems that provide a number of intuitive mental commands is the high variability of EEG signals. EEG signals from the same subject vary considerably within a single session and between sessions on the same or different days. To deal with this we are investigating methods of adapting the classifier while it is being used by the subject. By keeping the classifier constantly tuned to the EEG signals of the current session we hope to improve the performance of the classifier and allow the subject to learn to use the BCI more effectively. This paper discusses preliminary offline and online experiments towards this goal, focusing on the initial training period when the task that the subject is trying to achieve is known and thus supervised adaptation methods can be used. In these experiments the subjects were asked to perform three mental commands (imagination of left and right hand movements, and a language task) and the EEG signals were classified with a Gaussian classifier

Towards a Robust BCI: Error Potentials and Online Learning

Recent advances in the field of Brain-Computer Interfaces (BCIs) have shown that BCIs have the potential to provide a powerful new channel of communication, completely independent of muscular and nervous systems. However, while there have been successful laboratory demonstrations, there are still issues that need to be addressed before BCIs can be used by non-experts outside the laboratory. At IDIAP we have been investigating several areas that we believe will allow us to improve the robustness, flexibility and reliability of BCIs. One area is recognition of cognitive error states, that is, identifying errors through the brain's reaction to mistakes. The production of these error potentials (ErrP) in reaction to an error made by the user is well established. We have extended this work by identifying a similar but distinct ErrP that is generated in response to an error made by the interface, (a misinterpretation of a command that the user has given). This ErrP can be satisfactorily identified in single trials and can be demonstrated to improve the theoretical performance of a BCI. A second area of research is online adaptation of the classifier. BCI signals change over time, both between sessions and within a single session, due to a number of factors. This means that a classifier trained on data from a previous session will probably not be optimal for a new session. In this paper we present preliminary results from our investigations into supervised online learning that can be applied in the initial training phase. We also discuss the future direction of this research, including the combination of these two currently separate issues to create a potentially very powerful BCI

Prospects of brain–machine interfaces for space system control

The dream of controlling and guiding computer-based systems using human brain signals has slowly but steadily become a reality. The available technology allows real-time implementation of systems that measure neuronal activity, convert their signals, and translate their output for the purpose of controlling mechanical and electronic systems. This paper describes the state of the art of non-invasive brain-machine interfaces (BMIs) and critically investigates both the current technological limits and the future potential that BMIs have for space applications. We present an assessment of the advantages that BMIs can provide and justify the preferred candidate concepts for space applications together with a vision of future directions for their implementation. © 2008 Elsevier Ltd. All rights reserved

Non-Invasive Brain Computer Interface for Mental Control of a Simulated Wheelchair

This poster presents results obtained from experiments of driving a brain-actuated simulated wheelchair that incorporates the shared-control intelligence method. The simulated wheelchair is controlled offline using band power features. The task is to drive the wheelchair along a corridor avoiding two obstacles. We have analyzed data from 4 na�ve subjects during 25 sessions carried out in two days. To measure the performance of the brain-actuated wheelchair we have compared the final position of the wheelchair with the end point of the desired trajectory. The experiments show that the incorporation of a higher intelligence level in the control device significantly helps the subject to drive the robot device

Acute Administration of the GLP-1 Receptor Agonist Lixisenatide Diminishes Postprandial Insulin Secretion in Healthy Subjects But Not in Type 2 Diabetes, Associated with Slowing of Gastric Emptying

Published online 22 April 2022Introduction: It is uncertain whether lixisenatide has postprandial insulinotropic effects when its effect on slowing gastric emptying is considered, in healthy subjects and type 2 diabetes mellitus (T2DM). We evaluated the effects of single administration of 10 lg sc lixisenatide on glycaemia, insulin secretion and gastric emptying (GE), measured using the ‘gold standard’ technique of scintigraphy following an oral glucose load (75 g glucose). Methods: Fifteen healthy subjects (nine men, six women; age 67.2 ± 2.3 years) and 15 patients with T2DM (nine men, six women; age 61.9 ± 2.3 years) had measurements of GE, plasma glucose, insulin and C-peptide for 180 min after a radiolabeled 75 g glucose drink on two separate days. All subjects received lixisenatide (10 lg sc) or placebo in a randomised, double-blind, crossover fashion 30 min before the drink. Insulin secretory response (ISR) was determined using the C-peptide deconvolution method. Results: GE was markedly slowed by lixisenatide compared with placebo in both healthy subjects (1.45 ± 0.10 kcal/min for placebo vs. 0.60 ± 0.14 kcal/min for lixisenatide) and diabetes (1.57 ± 0.06 kcal/min for placebo vs. 0.75 ± 0.13 kcal/min for lixisenatide) (both P\0.001) with no difference between the two groups (P = 0.42). There was a moderate to strong inverse correlation between the early insulin secretory response calculated at 60 min and gastric retention at 60 min with lixisenatide treatment in healthy subjects (r = - 0.8, P = 0.0003) and a trend in type 2 diabetes (r = - 0.4, P = NS), compared with no relationships in the placebo arms (r = - 0.02, P = NS, healthy subjects) and (r = - 0.16, P = NS, type 2 diabetes). Conclusion: The marked slowing of GE of glucose induced by lixisenatide is associated with attenuation in the rise of postprandial glucose in both healthy subjects and diabetes and early insulin secretory response in healthy subjects.Chinmay S. Marathe . Hung Pham . Tongzhi Wu . Laurence G. Trahair . Rachael S. Rigda . Madeline D. M. Buttfield . Seva Hatzinikolas . Kylie Lange . Christopher K. Rayner . Andrea Mari . Michael Horowitz . Karen L. Jone