Avinash Tandle, Nandini Jog, Pancham D’cunha and Monil Chheta, “Classification of artefacts in EEG signal recordings and EOG artefact removal using EOG subtraction,” Communication on Applied Electronics. vol. 4, pp.12-19, 2016.
Dharmadhikari, A., Tandle, A., Jaiswal, S., Sawant, V., Vahia, V., & Jog, N. (2018). Frontal theta asymmetry as a biomarker of depression. East Asian Archives of Psychiatry, 28(1), 17–22. https://search.informit.org/doi/10.3316/
Tandle, A.L., Joshi, M.S., Dharmadhikari, A.S. et al. Mental state and emotion detection from musically stimulated EEG. Brain Inf. 5, 14 (2018). https://doi.org/10.1186/s40708-018-0092-z
Dharmadhikari, A., Jaiswal, S., Tandle, A., Sinha, D., & Jog, N. (2019). Study of frontal alpha asymmetry in mild depression: A potential biomarker or not? Journal of Neurosciences in Rural Practice, 10(2), 250-255. doi: https://doi.org/10.4103/jnrp.jnrp_293_18
Conferences
A Tandle, N Jog, “Classification of artefacts in eeg signal recordings and overview of removing techniques,” 2015 International Journal of Computer Applications.
A. Tandle, N. Jog, A. Dharmadhikari and S. Jaiswal, “Estimation of valence of emotion from musically stimulated EEG using frontal theta asymmetry,” 2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD), Changsha, China, 2016, pp. 63-68,
http://doi.org/ 10.1109/FSKD.2016.7603152.
A. Tandle, N. Jog, A. Dharmadhikari, S. Jaiswal and V. Sawant, “Study of valence of musical emotions and its laterality evoked by instrumental Indian classical music: An EEG study,” 2016 International Conference on Communication and Signal Processing (ICCSP), Melmaruvathur, India, 2016, pp. 0327-0331, http://doi.org/10.1109/ICCSP.2016.7754149.
Tandle Avinash, Lal Dikshant, Shah Seema, Methods of Neuromarketing and Implication of the Frontal Theta Asymmetry induced due to musical stimulus as choice modeling, Procedia Computer Science Volume 132, 2018, Pages 55-67, ISSN 1877-0509, https://doi.org/10.1016/j.procs.2018.05.059.
V. Shah, A. Tandle, N. Sharma and V. Sheth, “Genre Based Music Classification using Machine Learning and Convolutional Neural Networks,” 2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT), Kharagpur, India, 2021, pp. 1-8, http://doi.org/10.1109/ICCCNT51525.2021.9579597.
R. Sule, A. Kolekar, K. Patel and A. Tandle, “Selective Noise Cancellation using Machine Learning,” 2023 International Conference in Advances in Power, Signal, and Information Technology (APSIT), Bhubaneswar, India, 2023, pp. 645-650, http://doi.org/10.1109/APSIT58554.2023.10201773.
Agarwal, A., Tandle, A. (2022). Determining the Number of Bit Encryption That Is Optimum for Image Steganography in 8 Bit Images. In: Patnaik, S., Kountchev, R., Jain, V. (eds) Smart and Sustainable Technologies: Rural and Tribal Development Using IoT and Cloud Computing. Advances in Sustainability Science and Technology. Springer, Singapore. https://doi.org/10.1007/978-981-19-2277-0_15
Chapters
Book Chapter – Tandle, A.L. (2022). Valence of Emotion Recognition Using EEG. In: Gupta, D., Goswami, R.S., Banerjee, S., Tanveer, M., Pachori, R.B. (eds) Pattern Recognition and Data Analysis with Applications. Lecture Notes in Electrical Engineering, vol 888. Springer, Singapore. https://doi.org/10.1007/978-981-19-1520-8_6 Publisher: Springer
