Decoding EEG Rhythms During Action Observation, Motor Imagery, and Execution for Standing and SittingRattanaphon Chaisaen, Theerawit Wilaiprasitporn, Suppakorn Tammajarung et al.|IEEE Sensors Journal|2020Cited by 117
A Single-Channel Consumer-Grade EEG Device for Brain–Computer Interface: Enhancing Detection of SSVEP and Its Amplitude ModulationPhairot Autthasan, Theerawit Wilaiprasitporn, Jetsada Arnin et al.|IEEE Sensors Journal|2019Cited by 53
Towards an Integrated Approach to Simultaneously Estimating the Frequency and Amplitude Modulations of SSVEP Signals from Consumer-grade EEGPhairot Autthasan, Theerawit Wilaiprasitporn, Maneesha Perera et al.|arXiv (Cornell University)|2018Cited by 1
Predictive Model for SSVEP Magnitude Variation: Applications to Continuous Control in Brain-Computer InterfacesPhairot Autthasan, Theerawit Wilaiprasitporn, Nannapas Banluesombatkul et al.|arXiv (Cornell University)|2018Cited by 0
EEG-based dataset explicitly targets the transitions between sitting and standing for exploring neural activation patterns in motor imagery and executionBenjakarn Uengsawapak, Theerawit Wilaiprasitporn, Wipamas Polpakdee et al.|GigaScience|2026Cited by 0