Lucas R. Trambaiolli
Lucas R. Trambaiolli
Research Fellow, McLean Hospital, Harvard Medical School
Verified email at - Homepage
Cited by
Cited by
Improving Alzheimer's disease diagnosis with machine learning techniques
LR Trambaiolli, AC Lorena, FJ Fraga, PAM Kanda, R Anghinah, R Nitrini
Clinical EEG and neuroscience 42 (3), 160-165, 2011
Imaging brain function with functional near-infrared spectroscopy in unconstrained environments
JB Balardin, GA Zimeo Morais, RA Furucho, L Trambaiolli, P Vanzella, ...
Frontiers in human neuroscience 11, 258, 2017
EEG amplitude modulation analysis for semi-automated diagnosis of Alzheimer's disease
TH Falk, FJ Fraga, L Trambaiolli, R Anghinah
EURASIP Journal on Advances in Signal Processing, 192, 2012
Feature selection before EEG classification supports the diagnosis of Alzheimer’s disease
LR Trambaiolli, N Spolaôr, AC Lorena, R Anghinah, JR Sato
Clinical Neurophysiology 128 (10), 2058-2067, 2017
EEG spectro-temporal modulation energy: a new feature for automated diagnosis of Alzheimer's disease
LR Trambaiolli, TH Falk, FJ Fraga, R Anghinah, AC Lorena
2011 Annual International Conference of the IEEE Engineering in Medicine and …, 2011
Does EEG montage influence Alzheimer's disease electroclinic diagnosis?
LR Trambaiolli, AC Lorena, FJ Fraga, P Kanda, R Nitrini, R Anghinah
International journal of Alzheimer's disease 2011, 2011
Clinician’s road map to wavelet EEG as an Alzheimer’s disease biomarker
PAM Kanda, LR Trambaiolli, AC Lorena, FJ Fraga, LFI Basile, R Nitrini, ...
Clinical EEG and neuroscience 45 (2), 104-112, 2014
Towards an EEG-based biomarker for Alzheimer's disease: Improving amplitude modulation analysis features
FJ Fraga, TH Falk, LR Trambaiolli, EF Oliveira, WHL Pinaya, PAM Kanda, ...
2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013
Impact of communicative head movements on the quality of functional near-infrared spectroscopy signals: negligible effects for affirmative and negative gestures and consistent …
JB Balardin, GAZ Morais, RA Furucho, LR Trambaiolli, JR Sato
Journal of Biomedical Optics 22 (4), 046010, 2017
The relevance of feature selection methods to the classification of obsessive-compulsive disorder based on volumetric measures
LR Trambaiolli, CE Biazoli Jr, JB Balardin, MQ Hoexter, JR Sato
Journal of affective disorders 222, 49-56, 2017
Functional near-infrared spectroscopy-based affective neurofeedback: feedback effect, illiteracy phenomena, and whole-connectivity profiles
LR Trambaiolli, CE Biazoli, AM Cravo, TH Falk, JR Sato
Neurophotonics 5 (3), 035009, 2018
Predicting affective valence using cortical hemodynamic signals
LR Trambaiolli, CE Biazoli, AM Cravo, JR Sato
Scientific reports 8 (1), 1-12, 2018
Support vector machines in the diagnosis of Alzheimer’s disease
LR Trambaiolli, AC Lorena, FJ Fraga, R Anghinah
Proceedings of the ISSNIP Biosignals and Biorobotics Conference 1, 1-6, 2010
Uso de aprendizado de máquina no auxílio ao diagnóstico de Alzheimer
LR Trambaiolli, AC Lorena, FJ Fraga, R Anghinah
Rev Elet Inic Científ 3, 1-15, 2009
Hybrid brain–computer interfaces for wheelchair control: a review of existing solutions, their advantages and open challenges
LR Trambaiolli, TH Falk
Smart Wheelchairs and Brain-Computer Interfaces, 229-256, 2018
Subject-independent decoding of affective states using functional near-infrared spectroscopy
L Trambaiolli, J Tossato, A Cravo, C Biazoli, J Sato
bioRxiv, 228007, 2019
Resting-awake EEG amplitude modulation can predict performance of an fNIRS-based neurofeedback task
L Trambaiolli, R Cassani, C Biazoli, A Cravo, J Sato, T Falk
2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2018
Neurofeedback training in major depressive disorder: a systematic review of clinical efficacy, study quality and reporting practices
L Trambaiolli, SH Kohl, DEJ Linden, DMA Mehler
PsyArXiv, 2020
EEG spectro-temporal amplitude modulation as a measurement of cortical hemodynamics: an EEG-fNIRS study
LR Trambaiolli, R Cassani, TH Falk
2020 42nd Annual International Conference of the IEEE Engineering in …, 2020
Resting-state global EEG connectivity predicts depression and anxiety severity
LR Trambaiolli, CE Biazoli
2020 42nd Annual International Conference of the IEEE Engineering in …, 2020
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