COMPARISON OF MARKER AND MARKER-LESS AUTOMATED MOTION CAPTURE FOR BASEBALL PITCHING BIOMECHANICS

The purpose of this study was to measure baseball pitching kinematics with a marker-less motion capture system and compare the results against marker-based measurements. A sample of 114 pitches were captured at 240 Hz simultaneously with a 9-camera marker-less system and a 12-camera marker system. The pitches were thrown by nine baseball pitchers (age 17.0 ± 4.0 yrs). For each trial, the data were time-synchronized between the two systems using the instant of ball release. Coefficient of Multiple Correlations (CMC) were computed to assess the similarity of waveforms between the two systems. Paired t-tests were used to compare differences between the two systems for 3 temporal and 18 kinematic measurements. The CMC for all eight time series analyzed were excellent, ranging from 0.90 to 0.99. Timing of events between the two systems varied by two frames (0.0083 s) or less. Angular positions differed between the two systems up to 14 degrees. Thus, the marker-based and marker-less motion capture systems produced similar patterns for baseball pitching kinematics. However, based on the variations between the systems, it is recommended that a database of normative ranges should be established for each system individually

Intrinsic phase separation in superconducting K0.8Fe1.6Se2 (Tc= 31.8 K) single crystals

Temperature dependent single-crystal x-ray diffraction (XRD) in transmission mode probing the bulk of the newly discovered K0.8Fe1.6Se2 superconductor (Tc = 31.8 K) using synchrotron radiation is reported. A clear evidence of intrinsic phase separation at 520 K between two competing phases, (i) a first majority magnetic phase with a ThCr2Si2-type tetragonal lattice modulated by the iron vacancy ordering and (ii) a minority non-magnetic phase having an in-plane compressed lattice volume and a weak superstructure, is reported. The XRD peaks due to the Fe vacancy ordering in the majority phase disappear by increasing the temperature at 580 K, well above phase separation temperature confirming the order-disorder phase transition. The intrinsic phase separation at 520K between a competing first magnetic phase and a second non-magnetic phase in the normal phase both having lattice superstructures (that imply different Fermi surface topology reconstruction and charge density) is assigned to a lattice-electronic instability of the K0.8Fe1.6Se2 system typical of a system tuned at a Lifshitz critical point of an electronic topological transition that gives a multi-gaps superconductor tuned a shape resonance.Comment: 10 pages, 4 figure

Bio-signal based control in assistive robots: a survey

Recently, bio-signal based control has been gradually deployed in biomedical devices and assistive robots for improving the quality of life of disabled and elderly people, among which electromyography (EMG) and electroencephalography (EEG) bio-signals are being used widely. This paper reviews the deployment of these bio-signals in the state of art of control systems. The main aim of this paper is to describe the techniques used for (i) collecting EMG and EEG signals and diving these signals into segments (data acquisition and data segmentation stage), (ii) dividing the important data and removing redundant data from the EMG and EEG segments (feature extraction stage), and (iii) identifying categories from the relevant data obtained in the previous stage (classification stage). Furthermore, this paper presents a summary of applications controlled through these two bio-signals and some research challenges in the creation of these control systems. Finally, a brief conclusion is summarized

Caffeine Ingestion Reverses the Circadian Rhythm Effects on Neuromuscular Performance in Highly Resistance-Trained Men

Purpose: To investigate whether caffeine ingestion counteracts the morning reduction in neuromuscular performance associated with the circadian rhythm pattern. Methods: Twelve highly resistance-trained men underwent a battery of neuromuscular tests under three different conditions; i) morning (10:00 a.m.) with caffeine ingestion (i.e., 3 mg kg 21; AMCAFF trial); ii) morning (10:00 a.m.) with placebo ingestion (AMPLAC trial); and iii) afternoon (18:00 p.m.) with placebo ingestion (PMPLAC trial). A randomized, doubleblind, crossover, placebo controlled experimental design was used, with all subjects serving as their own controls. The neuromuscular test battery consisted in the measurement of bar displacement velocity during free-weight full-squat (SQ) and bench press (BP) exercises against loads that elicit maximum strength (75 % 1RM load) and muscle power adaptations (1 m s 21 load). Isometric maximum voluntary contraction (MVCLEG) and isometric electrically evoked strength of the right knee (EVOK LEG) were measured to identify caffeine’s action mechanisms. Steroid hormone levels (serum testosterone, cortisol and growth hormone) were evaluated at the beginning of each trial (PRE). In addition, plasma norepinephrine (NE) and epinephrine were measured PRE and at the end of each trial following a standardized intense (85 % 1RM) 6 repetitions bout of SQ (POST). Results: In the PM PLAC trial, dynamic muscle strength and power output were significantly enhanced compared with AM PLA

A Comparison of Physiological Signal Analysis Techniques and Classifiers for Automatic Emotional Evaluation of Audiovisual Contents

This Document is Protected by copyright and was first published by Frontiers. All rights reserved. it is reproduced with permissionThis work focuses on finding the most discriminatory or representative features that allow to classify commercials according to negative, neutral and positive effectiveness based on the Ace Score index. For this purpose, an experiment involving forty-seven participants was carried out. In this experiment electroencephalography (EEG), electrocardiography (ECG), Galvanic Skin Response (GSR) and respiration data were acquired while subjects were watching a 30-min audiovisual content. This content was composed by a submarine documentary and nine commercials (one of themthe ad under evaluation). After the signal pre-processing, four sets of features were extracted from the physiological signals using different state-of-the-art metrics. These features computed in time and frequency domains are the inputs to several basic and advanced classifiers. An average of 89.76% of the instances was correctly classified according to the Ace Score index. The best results were obtained by a classifier consisting of a combination between AdaBoost and RandomForest with automatic selection of features. The selected features were those extracted from GSR and HRV signals. These results are promising in the audiovisual content evaluation field by means of physiological signal processing.This work has been supported by the Heineken Endowed Chair in Neuromarketing at the Universitat Politecnica de Valencia in order to research and apply new technologies and neuroscience in communication, distribution and consumption fields.Colomer Granero, A.; Fuentes-Hurtado, FJ.; Naranjo Ornedo, V.; Guixeres Provinciale, J.; Ausin-Azofra, JM.; Alcañiz Raya, ML. (2016). A Comparison of Physiological Signal Analysis Techniques and Classifiers for Automatic Emotional Evaluation of Audiovisual Contents. Frontiers in Computational Neuroscience. 10(74):1-16. doi:10.3389/fncom.2016.00074S116107

Stimulus-dependent relationships between behavioral choice and sensory neural responses

Understanding perceptual decision-making requires linking sensory neural responses to behavioral choices. In two-choice tasks, activity-choice covariations are commonly quantified with a single measure of choice probability (CP), without characterizing their changes across stimulus levels. We provide theoretical conditions for stimulus dependencies of activity-choice covariations. Assuming a general decision-threshold model, which comprises both feedforward and feedback processing and allows for a stimulus-modulated neural population covariance, we analytically predict a very general and previously unreported stimulus dependence of CPs. We develop new tools, including refined analyses of CPs and generalized linear models with stimulus-choice interactions, which accurately assess the stimulus- or choice-driven signals of each neuron, characterizing stimulus-dependent patterns of choice-related signals. With these tools, we analyze CPs of macaque MT neurons during a motion discrimination task. Our analysis provides preliminary empirical evidence for the promise of studying stimulus dependencies of choice-related signals, encouraging further assessment in wider data sets

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