scholarly journals A MATLAB-BASED GUI FOR REMOTE ELECTROOCULOGRAPHY VISUAL EXAMINATION

2021 ◽  
Vol 50 (3) ◽  
pp. 101-113
Author(s):  
Tomas Stula ◽  
Antonino Proto ◽  
Jan Kubicek ◽  
Lukas Peter ◽  
Martin Cerny ◽  
...  
Keyword(s):  
User Interface ◽  
Graphical User Interface ◽  
Standard Test ◽  
University Hospital ◽  
Child Neurology ◽  
Visual Examination ◽  
Digital Era ◽  
Human Machine Interfaces ◽  
Gold Standard Test ◽  
Cerebral Diseases

In this work, a MATLAB-based graphical user interface is proposed for the visual examination of several eye movements. The proposed solution is algorithm-based, which localizes the area of the eye movement, removes artifacts, and calculates the view trajectory in terms of direction and orb deviation. To compute the algorithm, a five-electrode configuration is needed. The goodness of the proposed MATLAB-based graphical user interface has been validated, at the Clinic of Child Neurology of University Hospital of Ostrava, through the EEG Wave Program, which was considered as “gold standard” test. The proposed solution can help physicians on studying cerebral diseases, or to be used for the development of human-machine interfaces useful for the improvement of the digital era that surrounds us today.

scholarly journals Proposals and Comparisons from One-Sensor EEG and EOG Human-Machine Interfaces

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2220
Author(s):  
Francisco Laport ◽  
Daniel Iglesia ◽  
Adriana Dapena ◽  
Paula M. Castro ◽  
Francisco J. Vazquez-Araujo
Keyword(s):  
User Interface ◽  
Graphical User Interface ◽  
Signal Acquisition ◽  
Non Invasive ◽  
Human Machine Interfaces ◽  
Channel Systems

Human-Machine Interfaces (HMI) allow users to interact with different devices such as computers or home elements. A key part in HMI is the design of simple non-invasive interfaces to capture the signals associated with the user’s intentions. In this work, we have designed two different approaches based on Electroencephalography (EEG) and Electrooculography (EOG). For both cases, signal acquisition is performed using only one electrode, which makes placement more comfortable compared to multi-channel systems. We have also developed a Graphical User Interface (GUI) that presents objects to the user using two paradigms—one-by-one objects or rows-columns of objects. Both interfaces and paradigms have been compared for several users considering interactions with home elements.

Comparison of Two Tests to Determine the Maximal Aerobic Speed

2020 ◽  
Vol 60 (2) ◽  
pp. 252-262
Author(s):  
Benhammou Saddek ◽  
Jérémy B.J. Coquart ◽  
Laurent Mourot ◽  
Belkadi Adel ◽  
Mokkedes Moulay Idriss ◽  
...  
Keyword(s):  
Physiological Responses ◽  
Intraclass Correlation ◽  
Lactate Concentration ◽  
Blood Lactate Concentration ◽  
Random Order ◽  
Standard Test ◽  
Maximal Heart Rate ◽  
Distance Runners ◽  
Gold Standard Test ◽  
Maximal Aerobic Speed

SummaryThe aims of this study were (a): to compare maximal physiological responses (maximal heart rate: HRmax and blood lactate concentration: [La-]) and maximal aerobic speed (MAS) achieved during a gold standard test (T-VAM) to those during a new test entitled: the 150-50 Intermittent Test (150-50IT), and (b): to test the reliability of the 150-50IT. Eighteen middle-distance runners performed, in a random order, the T-VAM and the 150-50IT. Moreover, the runners performed a second 150-50IT (retest). The results of this study showed that the MAS obtained during 150-50IT were significantly higher than the MAS during the T-VAM (19.1 ± 0.9 vs. 17.9 ± 0.9 km.h−1, p < 0.001). There was also significant higher values in HRmax (193 ± 4 vs. 191 ± 2 bpm, p = 0.011), [La-] (11.4 ± 0.4 vs. 11.0 ± 0.5 mmol.L−1, p = 0.039) during the 150-50IT. Nevertheless, significant correlations were noted for MAS (r = 0.71, p = 0.001) and HRmax (r = 0.63, p = 0.007). MAS obtained during the first 150-50IT and the retest were not significantly different (p = 0.76) and were significantly correlated (r = 0.94, p < 0.001, intraclass correlation coefficient = 0.93 and coefficient of variation = 6.8 %). In conclusion, the 150-50IT is highly reproducible, but the maximal physiological responses derived from both tests cannot be interchangeable in the design of training programs.

HOW TO USE CROP GROWTH MODEL WOFOST FOR FORECASTING GROWTH AND YIELD OF A CROP

2016 ◽  
Vol 3 (1) ◽  
Author(s):  
LAL SINGH ◽  
PARMEET SINGH ◽  
RAIHANA HABIB KANTH ◽  
PURUSHOTAM SINGH ◽  
SABIA AKHTER ◽  
...  
Keyword(s):  
User Interface ◽  
Graphical User Interface ◽  
Input Data ◽  
Growth And Yield ◽  
Weather Data ◽  
Data Sets ◽  
Crop Growth Model ◽  
Control Center ◽  
Field Crops ◽  
Crop Calendar

WOFOST version 7.1.3 is a computer model that simulates the growth and production of annual field crops. All the run options are operational through a graphical user interface named WOFOST Control Center version 1.8 (WCC). WCC facilitates selecting the production level, and input data sets on crop, soil, weather, crop calendar, hydrological field conditions, soil fertility parameters and the output options. The files with crop, soil and weather data are explained, as well as the run files and the output files. A general overview is given of the development and the applications of the model. Its underlying concepts are discussed briefly.

Sign in / Sign up

Export Citation Format

Share Document