Selected Publications

Last updated: 9 Apr 2025

You can find my Google Scholar profile here.

2025

R. Chaisaen, P. Autthasan, A. Ditthapron and T. Wilaiprasitporn, AlphaGrad: Normalized Gradient Descent for Adaptive Multi-loss Functions in EEG-based Motor Imagery Classification, in IEEE Journal of Biomedical and Health Informatics, doi: 10.1109/JBHI.2025.3572197. [PDF]

N. Banluesombatkul, E. Mignot, and T. Wilaiprasitporn, Comprehensive evaluation of odds ratio product and spectral slope as continuous sleep depth measures: Advancing sleep staging and clinical applications, SLEEP, doi: 10.1093/sleep/zsaf130

P. Sawangjai, N. Seesawad and T. Wilaiprasitporn, Removal of Motion Artifacts From the PPG Signal Using Attentive Generative Adversarial Networks With Dual Discriminator, in IEEE Transactions on Instrumentation and Measurement, vol. 74, pp. 1-10, 2025, Art no. 2504210, doi: 10.1109/TIM.2025.3529546. [PDF]

N. Kumchaiseemak, F. Fioranelli and T. Wilaiprasitporn, Capturing Head Poses Using FMCW Radar and Deep Neural Networks, in IEEE Transactions on Aerospace and Electronic Systems, doi: 10.1109/TAES.2025.3529412. [PDF]

2024

P. Lakhan et al., EEG-BBNet: A Hybrid Framework for Brain Biometric Using Graph Connectivity, in IEEE Sensors Letters, vol. 9, no. 2, pp. 1-4, Feb. 2025, Art no. 6001904, doi: 10.1109/LSENS.2024.3522981. [PDF]

T. Choksatchawathi et al., ApSense: Data-Driven Algorithm in PPG-Based Sleep Apnea Sensing, in IEEE Internet of Things Journal, vol. 11, no. 20, pp. 33915-33926, 15 Oct.15, 2024, doi: 10.1109/JIOT.2024.3433500. [PDF]

Phurin Rangpong, Akima Connelly, Pengcheng Li, Theerawit Wilaiprasitporn, Tohru Yagi, The Effect of Virtual Reality Head-Mounted Display Stimulus in Sit-Stand Motor Imagery Training Paradigm, IEEJ Transactions on Electronics, Information and Systems, 2024, Volume 144, Issue 6, Pages 528-534, Released on J-STAGE June 01, 2024, Online ISSN 1348-8155, Print ISSN 0385-4221, doi: 10.1541/ieejeiss.144.528.

N. Seesawad et al., PseudoCell: Hard Negative Mining as Pseudo Labeling for Deep Learning-Based Centroblast Cell Detection, in IEEE Open Journal of Engineering in Medicine and Biology, vol. 5, pp. 514-523, 2024, doi: 10.1109/OJEMB.2024.3407351. [PDF]

P. Autthasan, R. Chaisaen, H. Phan, M. D. Vos and T. Wilaiprasitporn, MixNet: Joining Force of Classical and Modern Approaches Toward the Comprehensive Pipeline in Motor Imagery EEG Classification, in IEEE Internet of Things Journal, vol. 11, no. 17, pp. 28539-28554, 1 Sept.1, 2024, doi: 10.1109/JIOT.2024.3402254. [PDF]

Akima Connelly, Pengcheng Li, Phurin Rangpong, Theerawit Wilaiprasitporn, Tohru Yagi, Addressing Motor Imagery Performance Bias in Neurofeedback Training to Improve BCI Performance, IEEJ Transactions on Electronics, Information and Systems, 2024, Volume 144, Issue 5, Pages 431-437, Released on J-STAGE May 01, 2024, Online ISSN 1348-8155, Print ISSN 0385-4221, doi: 10.1541/ieejeiss.144.431.

P. Piamjinda et al., CHIVID: A Rapid Deployment of Community and Home Isolation During COVID-19 Pandemics, in IEEE Journal of Translational Engineering in Health and Medicine, vol. 12, pp. 390-400, 2024, doi: 10.1109/JTEHM.2024.3377258. [PDF]

2023

B. Leelakittisin, M. Trakulruangroj, S. Sangnark, T. Wilaiprasitporn and T. Sudhawiyangkul, Enhanced Lightweight CNN Using Joint Classification With Averaging Probability for sEMG-Based Subject-Independent Hand Gesture Recognition, in IEEE Sensors Journal, vol. 23, no. 17, pp. 20348-20356, 1 Sept.1, 2023, doi: 10.1109/JSEN.2023.3296649. [PDF]

P. Osathitporn et al., RRWaveNet: A Compact End-to-End Multiscale Residual CNN for Robust PPG Respiratory Rate Estimation, in IEEE Internet of Things Journal, vol. 10, no. 18, pp. 15943-15952, 15 Sept.15, 2023, doi: 10.1109/JIOT.2023.3265980. [PDF]

C. Boonnag et al., PACMAN: A Framework for Pulse Oximeter Digit Detection and Reading in a Low-Resource Setting, in IEEE Internet of Things Journal, vol. 10, no. 15, pp. 13196-13204, 1 Aug.1, 2023, doi: 10.1109/JIOT.2023.3262205.[PDF]

J. Nukitram et al., ANet: Autoencoder-Based Local Field Potential Feature Extractor for Evaluating an Antidepressant Effect in Mice After Administering Kratom Leaf Extracts, in IEEE Transactions on Biomedical Circuits and Systems, vol. 17, no. 1, pp. 67-76, Feb. 2023, doi: 10.1109/TBCAS.2023.3234280. [PDF]

2022

A. Chinkamol et al., OCTAve: 2D En Face Optical Coherence Tomography Angiography Vessel Segmentation in Weakly-Supervised Learning With Locality Augmentation, in IEEE Transactions on Biomedical Engineering, vol. 70, no. 6, pp. 1931-1942, June 2023, doi: 10.1109/TBME.2022.3232102. [PDF]

P. Cherachapridi et al., Prescreening MCI and Dementia Using Shank-Mounted IMU During TUG Task, in IEEE Sensors Journal, vol. 22, no. 24, pp. 24550-24558, 15 Dec.15, 2022, doi: 10.1109/JSEN.2022.3220238. [PDF]

N. Kumchaiseemak et al., Toward Ant-Sized Moving Object Localization Using Deep Learning in FMCW Radar: A Pilot Study, in IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-10, 2022, Art no. 5112510, doi: 10.1109/TGRS.2022.3169642. [PDF]

W. Saengmolee et al., Consumer-Grade Brain Measuring Sensor in People With Long-Term Kratom Consumption, in IEEE Sensors Journal, vol. 22, no. 6, pp. 6088-6097, 15 March15, 2022, doi: 10.1109/JSEN.2022.3147207. [PDF]

2021

R. Assabumrungrat et al., Ubiquitous Affective Computing: A Review, in IEEE Sensors Journal, vol. 22, no. 3, pp. 1867-1881, 1 Feb.1, 2022, doi: 10.1109/JSEN.2021.3138269. [PDF]

P. Autthasan et al., MIN2Net: End-to-End Multi-Task Learning for Subject-Independent Motor Imagery EEG Classification, in IEEE Transactions on Biomedical Engineering, vol. 69, no. 6, pp. 2105-2118, June 2022, doi: 10.1109/TBME.2021.3137184. [PDF]

P. Thuwajit et al., EEGWaveNet: Multiscale CNN-Based Spatiotemporal Feature Extraction for EEG Seizure Detection, in IEEE Transactions on Industrial Informatics, vol. 18, no. 8, pp. 5547-5557, Aug. 2022, doi: 10.1109/TII.2021.3133307. [PDF]

P. Sawangjai et al., EEGANet: Removal of Ocular Artifacts From the EEG Signal Using Generative Adversarial Networks, in IEEE Journal of Biomedical and Health Informatics, vol. 26, no. 10, pp. 4913-4924, Oct. 2022, doi: 10.1109/JBHI.2021.3131104. [PDF]

S. Kongwudhikunakorn et al., A Pilot Study on Visually Stimulated Cognitive Tasks for EEG-Based Dementia Recognition, in IEEE Transactions on Instrumentation and Measurement, vol. 70, pp. 1-10, 2021, Art no. 4007810, doi: 10.1109/TIM.2021.3120131. [PDF]

Flynn-Evans, E.E., Wong, L.R., Kuriyagawa, Y. et al. Supervision of a self-driving vehicle unmasks latent sleepiness relative to manually controlled driving. Sci Rep 11, 18530 (2021). doi: 10.1038/s41598-021-92914-5. [PDF]

T. Pianpanit, S. Lolak, P. Sawangjai, T. Sudhawiyangkul and T. Wilaiprasitporn, Parkinson’s Disease Recognition Using SPECT Image and Interpretable AI: A Tutorial, in IEEE Sensors Journal, vol. 21, no. 20, pp. 22304-22316, 15 Oct.15, 2021, doi: 10.1109/JSEN.2021.3077949. [PDF]

S. Sangnark et al., Revealing Preference in Popular Music Through Familiarity and Brain Response, in IEEE Sensors Journal, vol. 21, no. 13, pp. 14931-14940, 1 July1, 2021, doi: 10.1109/JSEN.2021.3073040. [PDF]

P. Leelaarporn et al., Sensor-Driven Achieving of Smart Living: A Review, in IEEE Sensors Journal, vol. 21, no. 9, pp. 10369-10391, 1 May1, 2021, doi: 10.1109/JSEN.2021.3059304. [PDF]

2020

K. Ueafuea et al., Potential Applications of Mobile and Wearable Devices for Psychological Support During the COVID-19 Pandemic: A Review, in IEEE Sensors Journal, vol. 21, no. 6, pp. 7162-7178, 15 March15, 2021, doi: 10.1109/JSEN.2020.3046259. [PDF]

P. Gajbhiye, N. Mingchinda, W. Chen, S. C. Mukhopadhyay, T. Wilaiprasitporn and R. K. Tripathy, Wavelet Domain Optimized Savitzky–Golay Filter for the Removal of Motion Artifacts From EEG Recordings, in IEEE Transactions on Instrumentation and Measurement, vol. 70, pp. 1-11, 2021, Art no. 4002111, doi: 10.1109/TIM.2020.3041099. [PDF]

N. Banluesombatkul et al., MetaSleepLearner: A Pilot Study on Fast Adaptation of Bio-Signals-Based Sleep Stage Classifier to New Individual Subject Using Meta-Learning, in IEEE Journal of Biomedical and Health Informatics, vol. 25, no. 6, pp. 1949-1963, June 2021, doi: 10.1109/JBHI.2020.3037693. [PDF]

M. Piriyajitakonkij et al., SleepPoseNet: Multi-View Learning for Sleep Postural Transition Recognition Using UWB, in IEEE Journal of Biomedical and Health Informatics, vol. 25, no. 4, pp. 1305-1314, April 2021, doi: 10.1109/JBHI.2020.3025900. [PDF]

T. Wilaiprasitporn, A. Ditthapron, K. Matchaparn, T. Tongbuasirilai, N. Banluesombatkul and E. Chuangsuwanich, Affective EEG-Based Person Identification Using the Deep Learning Approach, in IEEE Transactions on Cognitive and Developmental Systems, vol. 12, no. 3, pp. 486-496, Sept. 2020, doi: 10.1109/TCDS.2019.2924648. [PDF]

T. Choksatchawathi et al., Improving Heart Rate Estimation on Consumer Grade Wrist-Worn Device Using Post-Calibration Approach, in IEEE Sensors Journal, vol. 20, no. 13, pp. 7433-7446, 1 July1, 2020, doi: 10.1109/JSEN.2020.2979191. [PDF]

P. Sawangjai, S. Hompoonsup, P. Leelaarporn, S. Kongwudhikunakorn and T. Wilaiprasitporn, Consumer Grade EEG Measuring Sensors as Research Tools: A Review, in IEEE Sensors Journal, vol. 20, no. 8, pp. 3996-4024, 15 April15, 2020, doi: 10.1109/JSEN.2019.2962874. [PDF]

P. Autthasan et al., A Single-Channel Consumer-Grade EEG Device for Brain–Computer Interface: Enhancing Detection of SSVEP and Its Amplitude Modulation, in IEEE Sensors Journal, vol. 20, no. 6, pp. 3366-3378, 15 March15, 2020, doi: 10.1109/JSEN.2019.2958210. [PDF]

R. Chaisaen et al., Decoding EEG Rhythms During Action Observation, Motor Imagery, and Execution for Standing and Sitting, in IEEE Sensors Journal, vol. 20, no. 22, pp. 13776-13786, 15 Nov.15, 2020, doi: 10.1109/JSEN.2020.3005968. [PDF]

2019

P. Lakhan et al., Consumer Grade Brain Sensing for Emotion Recognition, in IEEE Sensors Journal, vol. 19, no. 21, pp. 9896-9907, 1 Nov.1, 2019, doi: 10.1109/JSEN.2019.2928781. [PDF]

A. Ditthapron, N. Banluesombatkul, S. Ketrat, E. Chuangsuwanich and T. Wilaiprasitporn, Universal Joint Feature Extraction for P300 EEG Classification Using Multi-Task Autoencoder, in IEEE Access, vol. 7, pp. 68415-68428, 2019, doi: 10.1109/ACCESS.2019.2919143. [PDF]