Ho Levesque (juneden4)

This approach also ensures computational when disturbed by uncertainties in system.The traditional P300 speller system uses the flashing row or column spelling paradigm. However, the classification accuracy and information transfer rate of the P300 speller are not adequate for real-world application. To improve the performance of the P300 speller, we devised a new spelling paradigm in which the flashing row or column of a virtual character matrix is covered by a translucent green circle with a red dot in either the upper or lower half (GC-RD spelling paradigm). We compared the event-related potential (ERP) waveforms with a control paradigm (GC spelling paradigm), in which the flashing row or column of a virtual character matrix was covered by a translucent green circle only. Our experimental results showed that the amplitude of P3a at the parietal area and P3b at the frontal-central-parietal areas evoked by the GC-RD paradigm were significantly greater than those induced by the GC paradigm. Higher classification accuracy and information transmission rates were also obtained in the GC-RD system. Our results indicated that the added red dots increased attention and visuospatial information, resulting in an amplitude increase in both P3a and P3b, thereby improving the performance of the P300 speller system.Electromyography (EMG)-driven musculoskeletal modeling relies on high-quality measurements of muscle electrical activity to estimate muscle forces. However, a critical challenge for practical deployment of this approach is missing EMG data from muscles that contribute substantially to joint moments. This situation may arise due to either the inability to measure deep muscles with surface electrodes or the lack of a sufficient number of EMG channels. Muscle synergy analysis (MSA) is a dimensionality reduction approach that decomposes a large number of muscle excitations into a small number of time-varying synergy excitations along with time-invariant synergy weights that define the contribution of each synergy excitation to all muscle excitations. This study evaluates how well missing muscle excitations can be predicted using synergy excitations extracted from muscles with available EMG data (henceforth called "synergy extrapolation" or SynX). The method was evaluated using a gait data set collected from a strand with the greatest robustness to EMG normalization method. Furthermore, the associated joint moment matching accuracy was comparable to that produced by initial EMG-driven model calibration using all 16 EMG channels per leg. SynX may facilitate the assessment of human neuromuscular control and biomechanics when important EMG signals are missing.The hippocampus is known to be comprised of several subfields, but the developmental trajectories of these subfields are under debate. In this study, we analyzed magnetic resonance imaging (MRI) data from a cross-sectional sample (198 healthy Chinese) using an automated segmentation tool to delineate the development of the hippocampal subregions from 6 to 26 years of age. We also examined whether gender and hemispheric differences influence the development of these subregions. For the whole hippocampus, the trajectory of development was observed to be an inverse-u. A significant increase in volume with age was found for most of the subregions, except for the L/R-parasubiculum, L/R-fimbria, and L-HATA. Gender-related differences were also found in the development of most subregions, especially for the hippocampal tail, CA1, molecular layer HP, GC-DG, CA3, and CA4, which showed a consistent increase in females and an early increase followed by a decrease in males. A comparison of the average volumes showed that the right whole hippocampus was significantly larger, along with the R-presubiculum, R-hippocampal-fissure, L/R-CA1, and L/R-molecular layer HP in males in comparison to females. Additionally, the average volume of the right hemisphere was shown to be significantly larger f