van Weelden, E., Wiltshire, T. J., Alimardani, M., & Louwerse, M. M. (2024). Exploring the impact of virtual reality flight simulations on EEG neural patterns and task performance. Cognitive Systems Research, 88, 101282.
Klęczek, K., Rice, A., & Alimardani, M. (2024). Robots as Mental Health Coaches: A Study of Emotional Responses to Technology-Assisted Stress Management Tasks Using Physiological Signals. Sensors, 24(13), 4032.
van Weelden, E., van Beek, C. W., Alimardani, M., Wiltshire, T. J., Ledegang, W. D., Groen, E. L., & Louwerse, M. M. (2024, May). A Passive Brain-Computer Interface for Predicting Pilot Workload in Virtual Reality Flight Training. In 2024 IEEE 4th International Conference on Human-Machine Systems (ICHMS) (pp. 1-6). IEEE.
von Groll, V. G., Leeuwis, N., Rimbert, S., Roc, A., Pillette, L., Lotte, F., & Alimardani, M. (2024). Large scale investigation of the effect of gender on mu rhythm suppression in motor imagery brain-computer interfaces. Brain-Computer Interfaces, 1-11.
Alimardani, M., Morera, G., & Hering, A. (2024, March). Virtual Day: A VR Game for Evaluation of Prospective Memory in Older Adults. In 2024 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW) (pp. 963-964). IEEE.
Leeuwis, N., Van Bommel, T., Tsakiris, M., & Alimardani, M. (2024). Uncovering the potential of evaluative conditioning in shaping attitudes toward sustainable product packaging. Frontiers in psychology, 15, 1284422.
Vrins, A., Pruss, E., Ceccato, C., Prinsen, J., De Rooij, A., Alimardani, M., & De Wit, J. (2024, March). Wizard-of-Oz vs. GPT-4: A Comparative Study of Perceived Social Intelligence in HRI Brainstorming. In Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction (pp. 1090-1094).
Vaitonytė, J., Alimardani, M., & Louwerse, M. (2024). Face Processing in Real and Virtual Faces: An EEG Study. In Proceedings of the Annual Meeting of the Cognitive Science Society (Vol. 46).
Vrins, A., Pruss, E., Ceccato, C., Prinsen, J., & Alimardani, M. (2023). Investigating the Impact of a Dual Musical Brain-Computer Interface on Interpersonal Synchrony: A Pilot Study. arXiv preprint arXiv:2309.02079.
Alimardani, M., Kocken, S., & Leeuwis, N. (2023). End-to-End Deep Transfer Learning for Calibration-free Motor Imagery Brain Computer Interfaces. arXiv preprint arXiv:2307.12827.
Atilla, F., Alimardani, M., Kawamoto, T., & Hiraki, K. (2023). Mother-child inter-brain synchrony during a mutual visual search task: A study of feedback valence and role. Social Neuroscience, 1-13.
Atilla, F., Alimardani, M., & Postma, M. (2023, June). Improving User Experience and Performance through Gamification of MI-BCI Training. In 10th International Brain-Computer Interface Meeting 2023.
Alimardani, M., von Groll, V. G., Leeuwis, N., Rimbert, S., Roc, A., Pillette, L., & Lotte, F. (2023, June). Does Gender Matter in Motor Imagery BCIs?. In 10th International BCI Meeting.
Pruss, E., Prinsen, J., Ceccato, C., Vrins, A., Ziadeh, H., Knoche, H., & Alimardani, M. (2023). Restoring Engagement in Human-Robot Interaction: A Brain-Computer Interface for Adaptive Learning with Robots. In Proceedings of IEEE SMC 2023. IEEE.
Vrins, A., Pruss, E., Prinsen, J., Ceccato, C., & Alimardani, M. (2023, February). Are You Paying Attention? The Effect of Embodied Interaction with an Adaptive Robot Tutor on User Engagement and Learning Performance. In Social Robotics: 14th International Conference, ICSR 2022, Proceedings, Part II (pp. 135-145). Cham: Springer Nature Switzerland.
Rönnback, R., Blom, F., & Alimardani, M. (2023). How do ethical concerns differ in active and passive brain-computer interfaces?. In 10th International BCI Society Meeting.
Ziadeh, H., Ceccato, C., Prinsen, J., Pruss, E., Vrins, A., Knoche, H., & Alimardani, M. (2023). "Feeling Unseen": Exploring the Impact of Adaptive Social Robots on User’s Social Agency During Learning. In Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction: HRI’23 Companion.
Bravo Perucho A. & Alimardani, M. (2023, January). Social Robots in Secondary Education: Can Robots Assist Young Adult Learners with Math Learning?. In Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction: HRI’23 Companion.
Ceccato, C., Pruss, E., Vrins, A., Prinsen, J., & Alimardani, M. (2023). BrainiBeats: A dual brain-computer interface for musical composition using inter-brain synchrony and emotional valence. In Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, pp. 1-7.
Hagedorn L., de Rooij A., Alimardani, M. (2023, April). Virtual Reality and Creativity: How do Immersive Environments Stimulate the Brain during Creative Idea Generation?. In Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems (pp. 1-7).
Leeuwis, N., van Bommel, T., & Alimardani, M. (2023). Evaluative Conditioning in Consumer Psychology: Can Affective Images of Climate Change Influence Sustainability Perception of Supermarket Products?. In 18th International Conference on Persuasive Technology, PERSUASIVE 2023
Leeuwis, N., van Bommel, T., & Alimardani, M. (2022). A framework for application of consumer neuroscience in pro-environmental behavior change interventions. Frontiers in Human Neuroscience, 16.
Alimardani, M., Harinandansingh, J., Ravin, L., & de Haas, M. (2022, August). Motivational Gestures in Robot-Assisted Language Learning: A Study of Cognitive Engagement using EEG Brain Activity. In 2022 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN) (pp. 1393-1398). IEEE.
van Weelden, E., Alimardani, M., Wiltshire, T. J., & Louwerse, M. M. (2022). Aviation and neurophysiology: A systematic review. Applied Ergonomics, 105, 103838.
Linders, G. M., Vaitonytė, J., Alimardani, M., Mitev, K. O., & Louwerse, M. M. (2022, September). A realistic, multimodal virtual agent for the healthcare domain. In Proceedings of the 22nd ACM International Conference on Intelligent Virtual Agents (pp. 1-3).
Knoben, A., Alimardani, M., Saghafi A., & Amiri, A. K. (2022). Cognitive Load Associated with Different Conceptual Modelling Approaches in Information Systems. In Proceedings of the 24th International Conference on Human-Computer Interaction (HCII2022)
Leeuwis, N., Alimardani, M. & Tom van Bommel. (2022). Neuromarketing as a Tool for Environmental Conditioning and Sustainable Consumption. In the 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022).
Alimardani, M., Duret, J. L., Jouen, A. L., & Hiraki, K. (2022, March). Robot-Assisted Language Learning Increases Functional Connectivity in Children's Brain. In Proceedings of the 2022 ACM/IEEE International Conference on Human-Robot Interaction (pp. 674-677).
Alimardani, M., & Gherman, D. E. (2022, February). Individual Differences in Motor Imagery BCIs: a Study of Gender, Mental States and Mu Suppression. In 2022 10th International Winter Conference on Brain-Computer Interface (BCI) (pp. 1-7). IEEE.
Pruss, E., Prinsen, J., Vrins, A., Ceccato, C. and Alimardani, M. (2022). A BCI-controlled Robot Assistant for Navigation and Object Manipulation in a VR Smart Home Environment. In Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies - BIODEVICES, (pp. 231-237).
Tibrewal, N., Leeuwis, N., & Alimardani, M. (2022). Classification of motor imagery EEG using deep learning increases performance in inefficient BCI users. PLoS ONE 17(7): e0268880.
Vaitonyte, J., Blomsma, P. A., Alimardani, M., & Louwerse, M. M. (2022). Generating and Recognizing Facial Expressions of Emotion in Virtual Agents: Computational and Experimental Studies in Action Units (under review)
Frangopoulou, M. S., & Alimardani, M. (2022). qEEG Analysis in the Diagnosis of Alzheimer’s Disease: A Comparison of Functional Connectivity and Spectral Analysis. Applied Sciences, 12(10), 5162.
Alimardani, M., Braak, S. V. D., Jouen, A. L., Matsunaka, R., & Hiraki, K. (2021, November). Assessment of Engagement and Learning During Child-Robot Interaction Using EEG Signals. In International Conference on Social Robotics (pp. 671-682). Springer, Cham.
Laura J. Hagedorn, Leeuwis, N., & Alimardani, M. (2021, December). Prediction of Inefficient BCI Users based on Cognitive Skills and Personality Traits. In International Conference on Neural Information Processing (pp. 81-89). Springer, Cham.
Leeuwis, N., Yoon, S., & Alimardani, M. (2021). Functional Connectivity Analysis in Motor Imagery Brain Computer Interfaces. Frontiers in Human Neuroscience, 15.
Atilla, F., Lombard, A., & Alimardani, M. (2021). Attention Classification of Drivers Using Convolutional Neural Networks. In the International Neuroergonomics Conference (NEC2021).
Atilla, F., & Alimardani, M. (2021). EEG-based Classification of Drivers Attention using Convolutional Neural Network. In 2021 IEEE 2nd International Conference on Human-Machine Systems (ICHMS) (pp. 1-4). IEEE.
van den Berg, B., van Donkelaar, S., & Alimardani, M. (2021). Inner Speech Classification using EEG Signals: A Deep Learning Approach. In the 2021 IEEE International Conference on Human-Machine Systems (ICHMS 2021). IEEE
Alimardani, M., Neve, L., & Verkaart A. (2021). Storytelling Robots for Training of Emotion Recognition in Children with Autism; Opinions from Experts and Non-experts. In International Conference on Human-Computer Interaction (pp. 223-233). Springer, Cham.
van Weelden, E., Alimardani, M., Wiltshire, T. J., & Louwerse, M. M. (2021). Advancing the Adoption of Virtual Reality and Neurotechnology to Improve Flight Training. In the 2021 IEEE International Conference on Human-Machine Systems (ICHMS 2021).
Alimardani, M., & Kaba, M. (2021, May). Deep Learning for Neuromarketing; Classification of User Preference using EEG Signals. In 12th Augmented Human International Conference (pp. 1-7).
Leeuwis, N., Paas, A., & Alimardani, M. (2021). Vividness of Visual Imagery and Personality Impact Motor-Imagery Brain Computer Interfaces. Frontiers in Human Neuroscience, 15.
Alimardani, M., & de Moor, G. (2021). Automatic Classification of Sleep Apnea Type and Severity using EEG Signals. In BIODEVICES (pp. 121-128).
Yoon, S., Alimardani, M., & Hiraki, K. (2021, March). The Effect of Robot-Guided Meditation on Intra-Brain EEG Phase Synchronization. In Companion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction (pp. 318-322).
Vaitonyte, J., Blomsma, P. A., Alimardani, M., & Louwerse, M. M. (2021). Realism of the face lies in skin and eyes: Evidence from virtual and human agents. Computers in Human Behavior Reports, 3, 100065.
Alimardani, M. & Hiraki, K. (2020). Passive Brain-Computer Interfaces for Enhanced Human-Robot Interaction. Frontiers in Robotics and AI, 7, 125.
Leeuwis, N. & Alimardani, M. (2020). High Aptitude Motor-Imagery BCI Users Have Better Visuospatial Memory. In 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 1518-1523. IEEE.
Furutani, K., Kawamoto, T., Alimardani, M., & Nakashima, K. I. (2020). Exhausted parents in Japan: Preliminary validation of the Japanese version of the Parental Burnout Assessment. New Directions for Child and Adolescent Development, 2020(174), 33-49.
Blomsma, P. A., Vaitonyte, J., Alimardani, M., & Louwerse, M. M. (2020). Spontaneous Facial Behavior Revolves Around Neutral Facial Displays. In Proceedings of the 20th ACM International Conference on Intelligent Virtual Agents (pp. 1-8).
Kont, M., & Alimardani, M. (2020). Engagement and Mind Perception Within Human-Robot Interaction: A Comparison Between Elderly and Young Adults. In International Conference on Social Robotics (pp. 344-356). Springer, Cham.
Alimardani, M., Kemmeren, L., Okumura, K., & Hiraki, K. (2020). Robot-Assisted Mindfulness Practice: Analysis of Neurophysiological Responses and Affective State Change. In proceeding of 29th IEEE International Conference on Robot and Human Interactive Communication (Ro-Man 2020).
Keshmiri, S., Alimardani, M., Shiomi, M., Sumioka, H., Ishiguro, H., & Hiraki, K. (2020). Higher Hypnotic Suggestibility Is Associated with the Lower EEG Signal Variability in Theta, Alpha, and Beta Frequency Bands. PloS one.
Alimardani, M., Hermans, A., & Tinga, A. M. (2020). Assessment of Empathy in an Affective VR Environment using EEG Signals. arXiv preprint arXiv:2003.10886.
Kuijt, A., Alimardani, M. (2020) Prediction of Human Empathy based on EEG Cortical Asymmetry. IEEE International Conference on Human-Machine Systems (ICHMS), Rome, Italy, 2020, pp. 1-5, doi: 10.1109/ICHMS49158.2020.9209561.
Biesmans, L., van Hees, P., Rombout, L. E., Alimardani, M., Fukuda, E. (2020) The Effects of Ingroup Bias on Public Speaking Anxiety in Virtual Reality. In 4th International Conference on Human Computer Interaction Theory and Applications. * Best Student Paper Award
Vaitonyte, J., Blomsma, P. A., Alimardani, M., & Louwerse, M. M. (2019, July). Generating Facial Expression Data: Computational and Experimental Evidence. In Proceedings of the 19th ACM International Conference on Intelligent Virtual Agents (pp. 94-96). ACM.
Tjon, D., Tinga, A.M., Alimardani, M., & Louwerse, M. M. (2019). Brain Activity Reflects Sense of Presence in 360° Video for Virtual Reality.
Sinnema, L., & Alimardani, M., (2019, November). The Attitude of Elderly and Young Adults Towards a Humanoid Robot as a Facilitator for Social Interaction. In International Conference on Social Robotics (pp. 24-33). Springer, Cham.
Alimardani, M., & Qurashi, S. (2019, November). Mind Perception of a Sociable Humanoid Robot: A Comparison Between Elderly and Young Adults. In Iberian Robotics conference (pp. 96-108). Springer, Cham.
Vrolijk, J., Alimardani, M., (2019, December). Classification of Noisy Epileptic EEG Signals using Fortified Long Short-Term Memory Network. In Proceedings of the 2nd International Conference on Bio-Signal and Image Processing (ICBSIP 2019).
Doan, N. N. T., Penkauskas, A., Grigoriev, G., Rombout, L.E., Mavromoustakos-Blom, P., Alimardani, M., & Atzmueller, M. (2019, November) Towards Multimodal Characterization of Dialogic Moments On Social Group Face-to-Face Interaction. In 3rd Affective Computing with Context Awareness for Ambient Intelligence Workshop (AfCAI2019).
Alimardani, M., Nishio, S., & Ishiguro, H. (2018). Brain-computer interface and motor imagery training: The role of visual feedback and embodiment, Evolving BCI Therapy - Engaging Brain State Dynamics, IntechOpen, DOI: 10.5772/intechopen.78695.
Alimardani, M., Nishio, S., & Ishiguro, H. (2018). Adjusting Brain Activity with Body Ownership Transfer. Geminoid Studies: Science and Technologies for Humanlike Teleoperated Androids, 359-373.
Alimardani, M., Nishio, S., & Ishiguro, H. (2018). Exploring Minimal Requirement for Body Ownership Transfer by Brain–Computer Interface. Geminoid Studies: Science and Technologies for Humanlike Teleoperated Androids, 329-338.
Kawamoto, T. K., Furutani, K., & Alimardani, M. (2018). Preliminary validation of Japanese version of the Parental Burnout Inventory and its relationship with perfectionism. Frontiers in Psychology, 9, 970.
Penaloza, C. I., Alimardani, M., & Nishio, S. (2018). Android feedback-based training modulates sensorimotor rhythms during motor imagery. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 26(3), 666-674.
Alimardani, M., Keshmiri, S., Sumioka, H., & Hiraki, K. (2018, October). Classification of EEG signals for a hypnotrack BCI system. In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 240-245). IEEE.
Ikeda, T., Hirata, M., Kasaki, M., Alimardani, M., Matsushita, K., Yamamoto, T., ... & Ishiguro, H. (2017). Subthalamic nucleus detects unnatural android movement. Scientific reports, 7(1), 17851.
Alimardani, M., & Hiraki, K. (2017). Development of a Real-Time Brain-Computer Interface for Interactive Robot Therapy: An Exploration of EEG and EMG Features during Hypnosis. World Academy of Science, Engineering and Technology, International Journal of Computer, Electrical, Automation, Control and Information Engineering, 11(2), 135-143. ＊Best Paper Award
Alimardani, M., Nishio, S., & Ishiguro, H. (2016). Removal of proprioception by BCI raises a stronger body ownership illusion in control of a humanlike robot. Scientific reports, 6.
Alimardani, M., Nishio, S., & Ishiguro, H. (2016). The importance of visual feedback design in BCIs; from embodiment to motor imagery learning. PloS one 11(9).
Alimardani, M., & Hiraki, K. (2016). Thermographic assessment of hand temperature during hypnosis and thermal suggestions. In Annual Conference of Society for Clinical & Experimental Hypnosis (SCEH 2016), Boston, USA.
Alimardani, M., Urushihara, M., & Hiraki, K. (2016). Monitoring EMG and EEG activities during Hypnosis; A Pilot Study Toward Real-Time Robot-Assisted Therapy. In World Conference on Innovation, Engineering, and Technology (IET 2016), Japan. ＊Best Paper Award
Alimardani, M., Nishio, S., & Ishiguro, H. (2015, September). BCI-teleoperated androids; a study of embodiment and its effect on motor imagery learning. In 2015 IEEE 19th International Conference on Intelligent Engineering Systems (INES), (pp. 347-352). IEEE.
Alimardani, M., Nishio, S., & Ishiguro, H. (2014). Effect of biased feedback on motor imagery learning in BCI- teleoperation system. Frontiers in systems neuroscience, 8.
Alimardani, M., Shuichi, N., & Ishiguro, H. (2014, August). The effect of feedback presentation on motor imagery performance during BCI-teleoperation of a humanlike robot. In Biomedical Robotics and Biomechatronics (2014 5th IEEE RAS & EMBS International Conference on (pp. 403-408). IEEE.
Vahidi, H., Mobasheri, A., Alimardani, M., Guan, Q., & Bakillah, M. (2014). Towards a Location-based Service for Early Mental Health Interventions in Disaster Response Using Minimalistic Tele-operated Android Robots Technology. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 40(4), 273.
Alimardani, M., Nishio, S., & Ishiguro, H. (2013). Humanlike robot hands controlled by brain activity arouse illusion of ownership in operators. Scientific reports, 3.
Nishio S., Alimardani, M., & Ishiguro H. (2013). Body ownership transfer to tele-operated androids. Journal of the Robotics Society of Japan, Vol. 31, No. 9, p. 854-857.
Alimardani M., Ikeda T., Yamamoto T., Hirata M., Nishio S., Matsushita K., Yoshikawa K., Nishio S. & Ishiguro H. (2013 January). BMI-operated androids reflect human's emotions for a better communication, Mechanism of brain and mind 2013, Japan.
Alimardani, M., Nishio, S., & Ishiguro, H. (2012). BMI-teleoperation of androids can transfer the sense of body ownership. In Proc. of Cognitive Neuroscience Society’s Annual Meeting (CNS2012).
Alimardani, M., Nishio, S. & Ishiguro, H. (2011,November). Body ownership transfer to tele-operated android through mind control. HAI symposium 2011, 1-2A-1, Japan.
Yamamoto, T., Hirata, M., Ikeda, T., Nishio, S., Matsushita, K., Alimardani, M., & Ishiguro, H. (2011 September). Research on BMI-Emotions through cognitive neuroscience robotics. The 29th annual conference of the robotics society of Japan 2011, 1A2-2, Japan.
Matsushita, K., Alimardani, M., & Yamamoto, T. (2011 March). A pointing device for real world objects using p300-BMI. Interaction 2011, Interactive Presentation, Japan.