S. Paszkiel

发表

Muscle activity measurement using visible light and infrared

Mariusz Sikora, S. Paszkiel, M. Sikora, 2019, IFAC-PapersOnLine.

The Impact of Different Sounds on Stress Level in the Context of EEG, Cardiac Measures and Subjective Stress Level: A Pilot Study

S. Paszkiel, P. Dobrakowski, Adam Łysiak, 2020, Brain sciences.

Gait Kinematics Analysis of Flatfoot Adults

M. A. Castro, Filipa Sousa, S. Paszkiel, 2021, Applied Sciences.

Influence of Cognitive Task Difficulty in Postural Control and Hemodynamic Response in the Prefrontal Cortex during Static Postural Standing

J. Vilas-Boas, S. Paszkiel, M. Saraiva, 2022, Applied Sciences.

Using the Raspberry PI2 Module and the Brain-Computer Technology for Controlling a Mobile Vehicle

Szczepan Paszkiel, S. Paszkiel, 2019, AUTOMATION.

Data Analysis of Human Brain Activity Using MATLAB Environment with EEGLAB

Szczepan Paszkiel, S. Paszkiel, 2019, Analysis and Classification of EEG Signals for Brain–Computer Interfaces.

Methods of Acquisition, Archiving and Biomedical Data Analysis of Brain Functioning

Szczepan Paszkiel, Piotr Szpulak, S. Paszkiel, 2018, IC BCI.

Characteristics of Question of Blind Source Separation Using Moore-Penrose Pseudoinversion for Reconstruction of EEG Signal

Szczepan Paszkiel, S. Paszkiel, 2017, AUTOMATION.

The use of Brain Computer Interfaces in control processes based on the industrial PC in terms of the methods of EEG signal analyses

S. Paszkiel, S. Paszkiel, 2013 .

A Method to Obtain Parameters of One-Column Jansen–Rit Model Using Genetic Algorithm and Spectral Characteristics

S. Paszkiel, Adam Łysiak, 2021, Applied Sciences.

Using Brain-Computer Interface Technology for Modeling 3D Objects in Blender Software

Szczepan Paszkiel, Mateusz Zając, S. Paszkiel, 2021, J. Autom. Mob. Robotics Intell. Syst..

Using the Moore-Penrose Pseudoinverse for the EEG Signal Reconstruction

Szczepan Paszkiel, S. Paszkiel, 2019, Analysis and Classification of EEG Signals for Brain–Computer Interfaces.

Using LORETA Method Based on the EEG Signal for Localizing the Sources of Brain Waves Activity

S. Paszkiel, S. Paszkiel, 2016 .

Brain–Computer Interface Technology

Szczepan Paszkiel, S. Paszkiel, 2019, Analysis and Classification of EEG Signals for Brain–Computer Interfaces.

Review of solutions for the application of example of machine learning methods for Motor Imagery in correlation with Brain-Computer Interfaces

S. Paszkiel, 2021, PRZEGLĄD ELEKTROTECHNICZNY.

A Pilot Study of Game Design in the Unity Environment as an Example of the Use of Neurogaming on the Basis of Brain–Computer Interface Technology to Improve Concentration

M. A. Castro, S. Paszkiel, Ningrong Lei, 2021, NeuroSci.

The Use of Multilayer ConvNets for the Purposes of Motor Imagery Classification

Szczepan Paszkiel, Pawel Dobrakowski, S. Paszkiel, 2021, AUTOMATION.

EEG Analysis and Neurofeedback Therapy of Concentration Problems in Mother and Child

Szczepan Paszkiel, Magda Zolubak, S. Paszkiel, 2021, IC BCI.

Brain–computer technology-based training system in the field of motor imagery

S. Paszkiel, P. Dobrakowski, 2020, IET Science, Measurement & Technology.

BCI Wheelchair Control Using Expert System Classifying EEG Signals Based on Power Spectrum Estimation and Nervous Tics Detection

S. Paszkiel, Dawid Pawuś, 2022, Applied Sciences.

Application of EEG Signals Integration to Proprietary Classification Algorithms in the Implementation of Mobile Robot Control with the Use of Motor Imagery Supported by EMG Measurements

S. Paszkiel, Dawid Pawuś, 2022, Applied Sciences.

The Application of Integration of EEG Signals for Authorial Classification Algorithms in Implementation for a Mobile Robot Control Using Movement Imagery—Pilot Study

S. Paszkiel, Dawid Pawuś, 2022, Applied Sciences.

Using EEG Based Brain-Computer Interface to Control Actions in Applications - The Way to Provide New Possibilities for Disabled People

Szczepan Paszkiel, Mateusz Adamczyk, S. Paszkiel, 2021, IC BCI.

Concept of Using the Brain-Computer Interface to Control Hand Prosthesis

S. Paszkiel, Julia Żaba, 2022, Journal of Automation, Mobile Robotics and Intelligent Systems.

The Use of Facial Expressions Identified from the Level of the EEG Signal for Controlling a Mobile Vehicle Based on a State Machine

Szczepan Paszkiel, S. Paszkiel, 2020, AUTOMATION.

The use of the Emotiv Epoc Flex kit in applications involving artificial intelligence

S. Paszkiel, Dawid Pawuś, 2023, ITTAP.