| 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 | 178 | 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 | 107 | 2013 |
| Passive Brain-Computer Interfaces for Enhanced Human-Robot Interaction M Alimardani, K Hiraki Frontiers in Robotics and AI 7, 125, 2020 | 85 | 2020 |
| 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 | 85 | 2016 |
| 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 | 75 | 2022 |
| 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 | 71 | 2014 |
| 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 | 62 | 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 | 60 | 2020 |
| Aviation and neurophysiology: A systematic review E van Weelden, M Alimardani, TJ Wiltshire, MM Louwerse Applied ergonomics 105, 103838, 2022 | 51 | 2022 |
| Functional connectivity analysis in motor-imagery brain computer interfaces N Leeuwis, S Yoon, M Alimardani Frontiers in Human Neuroscience 15, 732946, 2021 | 44 | 2021 |
| 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 | 43 | 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 | 40 | 2020 |
| 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 | 40 | 2018 |
| 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 | 39 | 2021 |
| 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 | 33 | 2016 |
| 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 | 29 | 2021 |
| Scoping review of the neural evidence on the uncanny valley J Vaitonytė, M Alimardani, MM Louwerse Computers in Human Behavior Reports 9, 100263, 2023 | 27 | 2023 |
| Deep learning for neuromarketing; classification of user preference using EEG signals M Alimardani, M Kaba 12th Augmented human international conference, 1-7, 2021 | 27 | 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 | 25 | 2021 |
| A framework for application of consumer neuroscience in pro-environmental behavior change interventions N Leeuwis, T van Bommel, M Alimardani Frontiers in human neuroscience 16, 886600, 2022 | 23 | 2022 |
Shuichi NishioOsaka UniversityVerifierad e-postadress på botransfer.org