Article
Engineering, Biomedical
Carlos A. Stefano Filho, Romis Attux, Gabriela Castellano
Summary: The study investigated the impact of feedback on the outcome of a MI practice protocol, finding improvements in classification accuracy and event-related desynchronization occurrence for the neurofeedback group, but no significant enhancement for the no feedback and sham feedback groups. The results also hinted at a possible placebo effect in the sham feedback group, with significant correlations observed between EO and CA.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2022)
Article
Neurosciences
Shun Sawai, Shin Murata, Shoya Fujikawa, Ryosuke Yamamoto, Keisuke Shima, Hideki Nakano
Summary: This study aimed to examine the effect of applying tDCS directly before MI with NFB. The results showed that m-ERD significantly increased in the NFB + tDCS group compared to the NFB group, and MI vividness significantly improved before and after training. This indicates that the combination of tDCS and NFB is more effective in improving MI abilities.
FRONTIERS IN NEUROSCIENCE
(2023)
Article
Engineering, Biomedical
Nikita A. Grigorev, Andrey O. Savosenkov, Maksim Lukoyanov, Anna Udoratina, Natalia N. Shusharina, Alexander Ya Kaplan, Alexander E. Hramov, Victor B. Kazantsev, Susanna Gordleeva
Summary: The study found that applying vibrotactile feedback during motor imagery (MI) training can enhance the desynchronization level of mu-rhythm EEG patterns over the contralateral motor cortex area corresponding to the MI of the non-dominant hand and increase the motor cortical excitability in hand muscle representation corresponding to a muscle engaged by the MI.
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Shugeng Chen, Xiaokang Shu, Hewei Wang, Li Ding, Jianghong Fu, Jie Jia
Summary: This study found that in patients with hemiplegia, the BCI accuracy of motor attempt tasks was significantly higher than that of motor imagery tasks. However, both tasks showed similar cortical activation patterns. Cortical activation may influence BCI accuracy, particularly in channels CP1, CP2, and C4.
FRONTIERS IN NEUROROBOTICS
(2021)
Article
Neurosciences
Kishor Lakshminarayanan, Rakshit Shah, Sohail R. Daulat, Viashen Moodley, Yifei Yao, Puja Sengupta, Vadivelan Ramu, Deepa Madathil
Summary: The purpose of this study was to investigate the cortical activity and digit classification performance during tactile imagery in healthy individuals. The study found that compound tactile imagery can be a viable alternative to motor imagery for brain-computer interface classification.
Article
Behavioral Sciences
Puja Sengupta, Kishor Lakshminarayanan
Summary: This study compared the cortical activity and digit classification performance induced by tactile imagery (TI) and motor imagery (MI) in brain-computer interfaces (BCIs). The results showed similar cortical activity patterns and no significant difference in classification accuracy between TI and MI. This suggests the potential of TI as an effective mental strategy in BCIs, particularly for individuals unable to rely on visual cues.
BEHAVIOURAL BRAIN RESEARCH
(2024)
Article
Neurosciences
Vadivelan Ramu, Kishor Lakshminarayanan
Summary: The purpose of this study was to evaluate the effect of vibrotactile stimulation prior to repeated complex motor imagery of finger movements using the non-dominant hand on motor imagery performance. The results showed that motor imagery performance was better in terms of event-related desynchronization and digit classification with vibrotactile stimulation compared to without stimulation.
FRONTIERS IN NEUROSCIENCE
(2023)
Article
Engineering, Multidisciplinary
Pasquale Arpaia, Damien Coyle, Francesco Donnarumma, Antonio Esposito, Angela Natalizio, Marco Parvis
Summary: This paper presents a wearable brain-computer interface that enhances motor imagery training through neurofeedback in extended reality. Various feedback modalities, including visual and vibrotactile, were evaluated either singularly or simultaneously. The results showed statistically significant improvement in performance over multiple sessions, demonstrating the functionality of the motor imagery-based instrument even with minimal equipment. The best feedback modality was found to be subject-dependent, with classification accuracy exceeding 80% in some cases.
Article
Automation & Control Systems
Fatemeh Shahlaei, Niraj Bagh, M. S. Zambare, M. Ramasubba Reddy
Summary: This study proposes a technique for localizing ERD/ERS patterns in motor imagery-based BCI and accurately classifying left and right hand movements. The effectiveness of the technique is validated using a competition dataset, demonstrating its superiority over state-of-the-art approaches.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Neurosciences
Kishor Lakshminarayanan, Rakshit Shah, Sohail R. Daulat, Viashen Moodley, Yifei Yao, Deepa Madathil
Summary: This study investigated the effects of combining virtual reality (VR) and action observation on brain activity during motor imagery. The results indicate that combining VR-based action observation enhances brain rhythmic patterns and improves task differentiation compared to motor imagery without action observation.
FRONTIERS IN NEUROSCIENCE
(2023)
Article
Biology
Seho Lee, Hakseung Kim, Jung Bin Kim, Dong-Joo Kim
Summary: Motor imagery (MI)-based brain-computer interfaces play a critical role in improving the rehabilitation and quality of life for paralyzed individuals. This study analyzed brain activation patterns during motor imagery tasks in individuals with hemiplegia, revealing specific activation patterns and altered network connectivity.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Engineering, Biomedical
P. Rithwik, V. K. Benzy, A. P. Vinod
Summary: This study focuses on decoding left vs. right directional information from Motor Imagery (MI) of the dominant hand movement using EEG-based BCI. The proposed method utilizes common spatial pattern (CSP) and its variants as features, enhancing direction discriminability with regularization techniques. Results show that the filter bank-based spatially regularized CSP method (FBSRCSP) offers the highest average classification accuracy of 90% for decoding bidirectional motor imagery of hand movement, a substantial improvement compared to previous methods.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2022)
Article
Neurosciences
Kosei Nakayashiki, Hajime Tojiki, Yoshikatsu Hayashi, Shiro Yano, Toshiyuki Kondo
Summary: This study aimed to identify the dominant factor for inducing event-related desynchronization (ERD). The results showed that ERD was significantly attenuated in the absence of force feedback, while it was maintained in the presence of force feedback. Additionally, the extent of ERD was found to reflect neural activity involved in the motor planning process for changing virtual equilibrium point.
FRONTIERS IN HUMAN NEUROSCIENCE
(2021)
Article
Neurosciences
Jiaxin Xie, Maoqin Peng, Jingqing Lu, Chao Xiao, Xin Zong, Manqing Wang, Dongrui Gao, Yun Qin, Tiejun Liu
Summary: This study explored the impact of transcranial electrical stimulation on motor imagery-based brain-computer interfaces, showing that tES can enhance the performance and applicability of BCIs, with a particularly significant effect in the tDCS group.
FRONTIERS IN HUMAN NEUROSCIENCE
(2021)
Article
Engineering, Biomedical
Tangfei Tao, Yagang Jia, Guanghua Xu, Renghao Liang, Qiuxiang Zhang, Longting Chen, Yuxiang Gao, Ruiquan Chen, Xiaowei Zheng, Yunhui Yu
Summary: In this study, a novel MI training paradigm combined with the error related potential (ErrP) was proposed to improve the efficiency of MI training. By correcting the output of the MI classifier based on the imagination intention of subjects and generating simulated labels for MI online adaptive training, a higher accuracy of kinesthetic feedback was achieved. Compared to the traditional MI training strategy, this approach allows subjects to use the MI-BCI system directly and achieve better performance after only three training experiments with training left and right hands simultaneously, making it more convenient for clinical use.
JOURNAL OF NEURAL ENGINEERING
(2023)
Article
Automation & Control Systems
Megumi Miyashita, Shiro Yano, Toshiyuki Kondo
ROBOTICS AND AUTONOMOUS SYSTEMS
(2018)
Article
Neurosciences
Nicolas Thorne, Juliane J. Honisch, Toshiyuki Kondo, Slawomir Nasuto, Yoshikatsu Hayashi
FRONTIERS IN HUMAN NEUROSCIENCE
(2019)
Article
Multidisciplinary Sciences
Bao Nguyen Tran, Shiro Yano, Toshiyuki Kondo
Article
Multidisciplinary Sciences
Xinzhe Li, Bruno Mota, Toshiyuki Kondo, Slawomir Nasuto, Yoshikatsu Hayashi
Article
Clinical Neurology
Takeru Honda, Hiroshi Mitoma, Hirotaka Yoshida, Kyota Bando, Hiroo Terashi, Takeshi Taguchi, Yohane Miyata, Satoko Kumada, Takashi Hanakawa, Hitoshi Aizawa, Shiro Yana, Toshiyuki Kondo, Hidehiro Mizusawa, Mario Manto, Shinji Kakei
FRONTIERS IN NEUROLOGY
(2020)
Article
Multidisciplinary Sciences
Phuong Thi Mai Nguyen, Yoshikatsu Hayashi, Murilo Da Silva Baptista, Toshiyuki Kondo
SCIENTIFIC REPORTS
(2020)
Article
Robotics
Kotaro Nishimura, Ozge Ozlem Saracbasi, Yoshikatsu Hayashi, Toshiyuki Kondo
Summary: The study found that novice subjects showed better adaptability to others after training with a skill-level matched peer, while learning with an expert did not result in the same effect. This suggests that cooperative experiences in visuomotor tasks can enhance adaptability.
Article
Neurosciences
Naoko Sakabe, Samirah Altukhaim, Yoshikatsu Hayashi, Takeshi Sakurada, Shiro Yano, Toshiyuki Kondo
Summary: This study utilized IVR-reinforced physical therapy with visual feedback enhancement intervention to successfully increase the use of the affected limb in patients, with the effect being maintained over time. This suggests that positive reinforcement within IVR can influence decision making in hand usage.
FRONTIERS IN HUMAN NEUROSCIENCE
(2021)
Article
Neurosciences
Kosei Nakayashiki, Hajime Tojiki, Yoshikatsu Hayashi, Shiro Yano, Toshiyuki Kondo
Summary: This study aimed to identify the dominant factor for inducing event-related desynchronization (ERD). The results showed that ERD was significantly attenuated in the absence of force feedback, while it was maintained in the presence of force feedback. Additionally, the extent of ERD was found to reflect neural activity involved in the motor planning process for changing virtual equilibrium point.
FRONTIERS IN HUMAN NEUROSCIENCE
(2021)
Article
Computer Science, Artificial Intelligence
Ozge Ozlem Saracbasi, William Harwin, Toshiyuki Kondo, Yoshikatsu Hayashi
Summary: When learning a new skill in an unknown environment, cooperating with other beginners enhances motor learning the most, while practicing individually is more effective than learning under the guidance of an expert. Peer-to-peer interactions also induce higher adaptability to new partners when attempting to achieve a common goal together.
FRONTIERS IN NEUROROBOTICS
(2021)
Article
Robotics
Eiko Matsuda, Daichi Misawa, Shiro Yano, Toshiyuki Kondo
Summary: This study investigated the ability of humans to adapt to a novel environment and found that the presence of lemon odor can reduce retrograde interference and enhance simultaneous motor learning.
JOURNAL OF ROBOTICS AND MECHATRONICS
(2022)
Article
Robotics
Saki Niiyama, Shiro Yano, Toshiyuki Kondo
Summary: Regional cerebral activity related to attention can be a more useful evaluation index for attention levels than conventional task performance score-based methods. In our study, we used near-infrared spectroscopy to quantitatively evaluate cerebral activity during a continuous performance test. The results showed a high correlation between activity in the right-side anterior cingulate cortex and estimated dorsolateral prefrontal cortex, and attention and executive function levels.
JOURNAL OF ROBOTICS AND MECHATRONICS
(2022)
Article
Engineering, Biomedical
Naoya Yamamoto, Takato Matsumoto, Tamami Sudo, Megumi Miyashita, Toshiyuki Kondo
Summary: This study used a ring-shaped wearable device to simultaneously measure upper-limb and finger usage in hemiplegic stroke patients and examined the association between finger usage and general clinical evaluation. The results showed that finger usage of the affected hand was moderately correlated with hand function evaluation (STEF) and moderately to strongly correlated with upper-limb function evaluation (FMA-UE and ARAT). However, there was no correlation between finger usage and other measurements.
JOURNAL OF NEUROENGINEERING AND REHABILITATION
(2023)
Article
Psychology, Multidisciplinary
Shiro Yano, Yoshikatsu Hayashi, Yuki Murata, Hiroshi Imamizu, Takaki Maeda, Toshiyuki Kondo
FRONTIERS IN PSYCHOLOGY
(2020)
Proceedings Paper
Engineering, Biomedical
Phuong Thi Mai Nguyen, Xinzhe Li, Yoshikatsu Hayashi, Shiro Yano, Toshiyuki Kondo
2019 IEEE 19TH INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOENGINEERING (BIBE)
(2019)
Article
Neurosciences
John J. Buchanan, Alberto Cordova
Summary: Research has shown that spontaneous visual coupling supports frequency entrainment, phase attraction, and intermittent interpersonal coordination during the switch from a novision (NV) to vision (V) context among co-actors. The experiments demonstrate that similar self-paced frequencies result from same amplitude movements, while different amplitudes lead to disparate frequencies. In experiment 1, co-actors were instructed to maintain amplitude without explicit instructions for coordination, which limited frequency and phase entrainment in the V context. In experiment 2, co-actors were instructed to maintain amplitude and intentionally coordinate together, resulting in significant frequency modulations and the production of various stable relative phase patterns.
HUMAN MOVEMENT SCIENCE
(2024)
