Rehabilitation exercise with real-time muscle simulation based EMG and AR

2011 ◽  
Author(s):  
Yee Mon Aung ◽  
Adel Al-Jumaily
Keyword(s):  
Real Time ◽  
Simulation Based ◽  
Rehabilitation Exercise ◽  
Muscle Simulation

Real-time cloth simulation based on particle constraints

2011 ◽  
Vol 31 (1) ◽  
pp. 289-292
Author(s):  
Zhong-hua LU ◽  
Ding-fang CHEN
Keyword(s):  
Real Time ◽  
Cloth Simulation ◽  
Simulation Based

A novel microfluidic microelectrode chip for a significantly enhanced monitoring of NPY-receptor activation in live mode

Lab on a Chip ◽  
2017 ◽  
Vol 17 (24) ◽  
pp. 4294-4302 ◽  
Author(s):  
Franziska D. Zitzmann ◽  
Heinz-Georg Jahnke ◽  
Felix Nitschke ◽  
Annette G. Beck-Sickinger ◽  
Bernd Abel ◽  
...  
Keyword(s):  
Real Time ◽  
Microfluidic Chip ◽  
Microelectrode Array ◽  
Fem Simulation ◽  
Receptor Activation ◽  
Living Cells ◽  
Real Time Monitoring ◽  
Non Invasive ◽  
Npy Receptor ◽  
Simulation Based

We present a FEM simulation based step-by-step development of a microelectrode array integrated into a microfluidic chip for the non-invasive real-time monitoring of living cells.

Real-time, Simulation-based Identification of Cyber-Security Attacks of Industrial Plants

2021 ◽  
Author(s):  
Abhi Patel ◽  
Tim Schenk ◽  
Steffi Knorn ◽  
Heiko Patzlaff ◽  
Dragan Obradovic ◽  
...  
Keyword(s):  
Real Time ◽  
Cyber Security ◽  
Security Attacks ◽  
Industrial Plants ◽  
Real Time Simulation ◽  
Time Simulation ◽  
Simulation Based

scholarly journals A simulation-based approach to improve decoded neurofeedback performance

2018 ◽  
Author(s):  
Ethan Oblak ◽  
James Sulzer ◽  
Jarrod Lewis-Peacock
Keyword(s):  
Real Time ◽  
Brain Activity ◽  
Processing Parameters ◽  
Orientation Tuning ◽  
Design Parameters ◽  
Visual Orientation ◽  
Brain Functions ◽  
Simulation Based ◽  
Using Data ◽  
The Right

AbstractThe neural correlates of specific brain functions such as visual orientation tuning and individual finger movements can be revealed using multivoxel pattern analysis (MVPA) of fMRI data. Neurofeedback based on these distributed patterns of brain activity presents a unique ability for precise neuromodulation. Recent applications of this technique, known as decoded neurofeedback, have manipulated fear conditioning, visual perception, confidence judgements and facial preference. However, there has yet to be an empirical justification of the timing and data processing parameters of these experiments. Suboptimal parameter settings could impact the efficacy of neurofeedback learning and contribute to the ‘non-responder’ effect. The goal of this study was to investigate how design parameters of decoded neurofeedback experiments affect decoding accuracy and neurofeedback performance. Subjects participated in three fMRI sessions: two ‘finger localizer’ sessions to identify the fMRI patterns associated with each of the four fingers of the right hand, and one ‘finger finding’ neurofeedback session to assess neurofeedback performance. Using only the localizer data, we show that real-time decoding can be degraded by poor experiment timing or ROI selection. To set key parameters for the neurofeedback session, we used offline simulations of decoded neurofeedback using data from the localizer sessions to predict neurofeedback performance. We show that these predictions align with real neurofeedback performance at the group level and can also explain individual differences in neurofeedback success. Overall, this work demonstrates the usefulness of offline simulation to improve the success of real-time decoded neurofeedback experiments.

Sign in / Sign up

Export Citation Format

Share Document