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ROCIO SALAZAR VARASROCIO SALAZAR VARAS
ROCIO SALAZAR VARAS

Degrees:
Doctorado en Ingeniería y Física Biomédicas, Centro de Investigación y Estudios Avanzados del Instituto Politécnico Nacional, Unidad Monterrey.
Maestría en Ciencias en Ingeniería y Física Biomédicas, Centro de Investigación y Estudios Avanzados del Instituto Politécnico Nacional, Unidad Monterrey.
Licenciatura en Ingeniería Biónica, Instituto Politécnico Nacional .

MIEMBRO DEL SISTEMA NACIONAL DE INVESTIGADORES (SNI) Nivel 1

Areas of interest:
Interfaz Cerebro-Computadora Extracción de características Señales biomédicas Reconocimiento de patrones
Rocio Salazar received her B.Sc. degree in Bionic Engineering from the Interdisciplinary Professional Unit in Engineering and Advanced Technologies, National Polytechnic Institute (UPIITA-IPN), Mexico, in 2009. She received her Master degree as well as Ph.D. degree in Biomedical Engineering and Physics from Center for Research and Advanced Studies (Cinvestav), Mexico in 2011 and 2015 respectively. During her Ph.D. she was accepted as a visiting student in the Brain-Machine Interface Systems Lab at Miguel Hernandez University, Elche, Spain. From August 2015 to June 2016, she held a postdoctoral position at the Biomedical Signal Processing Laboratory of Cinvestav Monterrey, Mexico. In August 2017 she joined the University of the Americas Puebla (UDLAP). There, she is an Associate Professor in the department of Computing, Electronics and Mechatronics. Her research interests are focused on biomedical signal processing as well as feature extraction and classification of EEG signals oriented to Brain-Computer Interface applications. In January 2017, Dr. Salazar received the appointment of national researcher by the Mexican Council for Science and Technology (Conacyt), from which she currently holds the level I.
  

 
 

Producción de investigación
Sección 
 
Año




Formación de recursos humanos, tesis dirigidas

2023
Depression detection based on quantitative features of electroencephalographic signals and SVM,

2023
A genetic algorith based approach for simultaneous feature, channel and frequency band selection on MI EEG-based BCI,

2022
Comparación de métricas lineales y no lineales de las señales de EEG en la detección de situaciones de emergencia,

2022
Uso de la varianza y el clasificador SVM para la detección de potenciales P300 y propuesta para diseño de Interfaz Cerebro-Computadora,

2021
Desarrollo de un sistema de autenticación basado en señales de electroencefalografía.,

2020
Uso de asimilación de datos para el análisis de electroencefalograma cuantitativo,



Congresos Internacionales

2020
Person Authentication Based on Standard Deviation of EEG Signals and Bayesian Classifier, Tipo de participación: Ponencia Oral Nombre del congreso: 19th Mexican International Conference on Artificial Intelligence



Artículos de investigación

2020
Using data assimilation for quantitative electroencephalography analysis, Nombre de la revista: Brain Sciences, Volumen: 10, Número: 11, Páginas: , DOI: doi: 10.3390/brainsci10110853, ISSN: 20763425

2019
Facing high EEG signals variability during classification using fractal dimension and different cutoff frequencies, Nombre de la revista: Computational Intelligence and Neuroscience, Volumen: 2019, Número: 9174307, Páginas: , DOI: 10.1155/2019/9174307, ISSN: 16875265, 16875273

2019
Evaluating the effect of the cutoff frequencies during the pre-processing stage of motor imagery EEG signals classification, Nombre de la revista: Biomedical Signal Processing and Control, Volumen: 54, Número: 101592, Páginas: , DOI: 10.1016/j.bspc.2019.101592, ISSN: 17468094



Libros Editorial Internacional

2023
Advances in Smart Healthcare Paradigms and Applications. , ISBN: 9783031373



Citas por otros autores

2023
123,

2021
82,

2020
75,

2019
27,

2019
50,

 
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