Preliminary validation of Japanese version of the parental burnout inventory and its relationship with perfectionism T Kawamoto, K Furutani, M Alimardani Frontiers in Psychology 9, 970, 2018 | 143 | 2018 |
Humanlike robot hands controlled by brain activity arouse illusion of ownership in operators M Alimardani, S Nishio, H Ishiguro Scientific reports 3 (1), 2396, 2013 | 104 | 2013 |
The importance of visual feedback design in BCIs; from embodiment to motor imagery learning M Alimardani, S Nishio, H Ishiguro PloS one 11 (9), e0161945, 2016 | 74 | 2016 |
Effect of biased feedback on motor imagery learning in BCI-teleoperation system M Alimardani, S Nishio, H Ishiguro Frontiers in systems neuroscience 8, 52, 2014 | 70 | 2014 |
Passive Brain-Computer Interfaces for Enhanced Human-Robot Interaction M Alimardani, K Hiraki Frontiers in Robotics and AI 7, 125, 2020 | 64 | 2020 |
Brain-computer interface and motor imagery training: The role of visual feedback and embodiment M Alimardani, S Nishio, H Ishiguro Evolving BCI therapy-engaging brain state dynamics 2, 64, 2018 | 55 | 2018 |
Exhausted parents in Japan: Preliminary validation of the Japanese version of the Parental Burnout Assessment K Furutani, T Kawamoto, M Alimardani, K Nakashima New Directions for Child and Adolescent Development 2020 (174), 33-49, 2020 | 53 | 2020 |
Classification of motor imagery EEG using deep learning increases performance in inefficient BCI users N Tibrewal, N Leeuwis, M Alimardani Plos one 17 (7), e0268880, 2022 | 52 | 2022 |
Android feedback-based training modulates sensorimotor rhythms during motor imagery CI Penaloza, M Alimardani, S Nishio IEEE Transactions on Neural Systems and Rehabilitation Engineering 26 (3 …, 2018 | 38 | 2018 |
Vividness of visual imagery and personality impact motor-imagery brain computer interfaces N Leeuwis, A Paas, M Alimardani Frontiers in Human Neuroscience 15, 634748, 2021 | 37 | 2021 |
Aviation and neurophysiology: A systematic review E van Weelden, M Alimardani, TJ Wiltshire, MM Louwerse Applied ergonomics 105, 103838, 2022 | 34 | 2022 |
Functional connectivity analysis in motor-imagery brain computer interfaces N Leeuwis, S Yoon, M Alimardani Frontiers in Human Neuroscience 15, 732946, 2021 | 34 | 2021 |
Robot-assisted mindfulness practice: Analysis of neurophysiological responses and affective state change M Alimardani, L Kemmeren, K Okumura, K Hiraki 2020 29th IEEE international conference on robot and human interactive …, 2020 | 34 | 2020 |
Removal of proprioception by BCI raises a stronger body ownership illusion in control of a humanlike robot M Alimardani, S Nishio, H Ishiguro Scientific reports 6 (1), 33514, 2016 | 31 | 2016 |
Inner speech classification using eeg signals: A deep learning approach B van den Berg, S van Donkelaar, M Alimardani 2021 IEEE 2nd International Conference on Human-Machine Systems (ICHMS), 1-4, 2021 | 25 | 2021 |
Assessment of engagement and learning during child-robot interaction using EEG signals M Alimardani, S van den Braak, AL Jouen, R Matsunaka, K Hiraki Social Robotics: 13th International Conference, ICSR 2021, Singapore …, 2021 | 24 | 2021 |
Deep learning for neuromarketing; classification of user preference using EEG signals M Alimardani, M Kaba 12th Augmented human international conference, 1-7, 2021 | 22 | 2021 |
Realism of the face lies in skin and eyes: Evidence from virtual and human agents J Vaitonytė, PA Blomsma, M Alimardani, MM Louwerse Computers in Human Behavior Reports 3, 100065, 2021 | 20 | 2021 |
Engagement and mind perception within human-robot interaction: A comparison between elderly and young adults M Kont, M Alimardani Social Robotics: 12th International Conference, ICSR 2020, Golden, CO, USA …, 2020 | 19 | 2020 |
The attitude of elderly and young adults towards a humanoid robot as a facilitator for social interaction L Sinnema, M Alimardani Social Robotics: 11th International Conference, ICSR 2019, Madrid, Spain …, 2019 | 19 | 2019 |