Results 21 to 30 of about 6,719 (207)

Sensory System for Implementing a Human—Computer Interface Based on Electrooculography

Sensors, 2010
This paper describes a sensory system for implementing a human–computer interface based on electrooculography. An acquisition system captures electrooculograms and transmits them via the ZigBee protocol.
Sergio Ortega, Elena López, Jose Manuel Rodriguez-Ascariz, Luciano Boquete, Rafael Barea   +4 more
doaj   +2 more sources

Señales EOG: una revisión sobre procesamiento y aplicaciones

Mundo Fesc, 2022
This paper presents a review of electrooculography signal processing and applications. First, it presents a general framework for using these signals. It then describes cutting-edge research on systems based on electrooculography signals.
David Escobar-Valencia, Fernando Jesús Regino-Ubarnes, Diana Yamileth Velásquez-Maldonado   +2 more
doaj   +1 more source

The Relationship between Stress Levels Measured by a Questionnaire and the Data Obtained by Smart Glasses and Finger Pulse Oximeters among Polish Dental Students

Applied Sciences, 2021
Stress is a physical, mental, or emotional response to a change and is a significant problem in modern society. In addition to questionnaires, levels of stress may be assessed by monitoring physiological signals, such as via photoplethysmogram (PPG ...
Katarzyna Mocny-Pachońska, Rafał J. Doniec, Szymon Sieciński, Natalia J. Piaseczna, Marek Pachoński, Ewaryst J. Tkacz   +5 more
doaj   +1 more source

Technical Performance of Textile-Based Dry Forehead Electrodes Compared With Medical-Grade Overnight Home Sleep Recordings

IEEE Access, 2021
The current clinically used electroencephalography (EEG) sensors are not self-applicable. This complicates the recording of the brain’s electrical activity in unattended home polysomnography (PSG).
Matias Rusanen, Samu Kainulainen, Henri Korkalainen, Laura Kalevo, Katja Myllymaa, Timo Leppanen, Juha Toyras, Erna Sif Arnardottir, Sami Myllymaa   +8 more
doaj   +1 more source

Implementation of a Convolutional Neural Network for Eye Blink Artifacts Removal From the Electroencephalography Signal

Frontiers in Neuroscience, 2022
Electroencephalography (EEG) signals are disrupted by technical and physiological artifacts. One of the most common artifacts is the natural activity that results from the movement of the eyes and the blinking of the subject.
Marcin Jurczak, Marcin Kołodziej, Andrzej Majkowski   +2 more
doaj   +1 more source

The challenge of measuring physiological parameters during motor imagery engagement in patients after a stroke

Frontiers in Neuroscience, 2023
IntroductionIt is suggested that eye movement recordings could be used as an objective evaluation method of motor imagery (MI) engagement. Our investigation aimed to evaluate MI engagement in patients after stroke (PaS) compared with physical execution ...
Szabina Gäumann, Efe Anil Aksöz, Frank Behrendt, Frank Behrendt, Jasmin Wandel, Letizia Cappelletti, Annika Krug, Daniel Mörder, Annika Bill, Katrin Parmar, Katrin Parmar, Hans Ulrich Gerth, Hans Ulrich Gerth, Leo H. Bonati, Leo H. Bonati, Leo H. Bonati, Corina Schuster-Amft, Corina Schuster-Amft, Corina Schuster-Amft   +18 more
doaj   +1 more source

Review Article. Role of Electrophysiological Methods in Diagnosis of Hereditary Retinal Dystrophies [PDF]

International Journal Bioautomation, 2021
The aim of the study is to present the different electrophysiological methods (EF) for study the retinal function and to highlight their importance in the diagnosis of hereditary retinal dystrophies (HRDs).
Elena Mermeklieva
doaj   +1 more source

Sensor-Based Classification of Primary and Secondary Car Driver Activities Using Convolutional Neural Networks

Sensors, 2023
To drive safely, the driver must be aware of the surroundings, pay attention to the road traffic, and be ready to adapt to new circumstances. Most studies on driving safety focus on detecting anomalies in driver behavior and monitoring cognitive ...
Rafał Doniec, Justyna Konior, Szymon Sieciński, Artur Piet, Muhammad Tausif Irshad, Natalia Piaseczna, Md Abid Hasan, Frédéric Li, Muhammad Adeel Nisar, Marcin Grzegorzek   +9 more
doaj   +1 more source

Temporal Feature Extraction and Machine Learning for Classification of Sleep Stages Using Telemetry Polysomnography

Brain Sciences, 2023
Accurate sleep stage detection is crucial for diagnosing sleep disorders and tailoring treatment plans. Polysomnography (PSG) is considered the gold standard for sleep assessment since it captures a diverse set of physiological signals.
Utkarsh Lal, Suhas Mathavu Vasanthsena, Anitha Hoblidar   +2 more
doaj   +1 more source

Use of Force Feedback Device in a Hybrid Brain-Computer Interface Based on SSVEP, EOG and Eye Tracking for Sorting Items

Sensors, 2021
Research focused on signals derived from the human organism is becoming increasingly popular. In this field, a special role is played by brain-computer interfaces based on brainwaves.
Arkadiusz Kubacki
doaj   +1 more source