• Journal of Biomedical Engineering Research
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• v.43 no.6
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• pp.375-381
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• 2022

Brain-computer interface (BCI) is a technology that allows users with motor disturbance to control machines by brainwaves without a physical controller. Motor imagery (MI)-BCI is one of the popular BCI techniques, but it needs a long calibration time for users to perform a mental task that causes high fatigue to the users. MI is reported as showing a similar neural mechanism as motor execution (ME) and motor observation (MO). However, integrative investigations of these three tasks are rarely conducted. In this study, we propose a new paradigm that incorporates three tasks (MI, ME, and MO) and conducted a comparative analysis. For this study, we collected Electroencephalograms (EEG) of motor imagery/execution/observation from 28 healthy subjects and investigated alpha event-related (de)synchronization (ERD/ERS) and classification accuracy (left vs. right motor tasks). As result, we observed ERD and ERS in MI, MO and ME although the timing is different across tasks. In addition, the MI showed strong ERD on the contralateral hemisphere, while the MO showed strong ERD on the ipsilateral side. In the classification analysis using a Riemannian geometry-based classifier, we obtained classification accuracies as MO (66.34%), MI (60.06%) and ME (58.57%). We conclude that there are similarities and differences in fundamental neural mechanisms across the three motor tasks and that these results could be used to advance the current MI-BCI further by incorporating data from ME and MO.

• Journal of Magnetics
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• v.19 no.2
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• pp.181-184
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• 2014

The aim of the present study was to examine whether motor imagery (MI) practice in conjunction with repetitive transcranial magnetic stimulation (rTMS) applied to stroke patients could improve theirgait ability. This study was conducted with 29 subjects diagnosed with hemiparesis due to stroke.The experimental group consisted of 15 members who were performed MI practice in conjunction with repetitive transcranial magnetic stimulation, while the control group consisted of 14 members who were performed MI practice and sham therapy. Both groups received traditional physical therapy for 30 minutes a day, 5 days a week, for 6 weeks; additionally, they received mental practice for 15 minutes. The experimental group was instructed to perform rTMS and the control group was instructed to apply sham stimulation for 15 minutes. Gait analysis was performed using a three-dimensional motion capture system, which is a real-time tracking device that delivers data via infrared reflective markers using six cameras. Results showed that the velocity, step length, and cadence of both groups were significantly improved after the practice (p<0.05). Significant differences were found between the groups in velocity and cadence (p<0.05) as well as with respect to the change rate (p<0.05) after practice. The results showed that MI practice in conjunction with rTMS is more effective in improving gait ability than MI practice alone.

• Journal of Sensor Science and Technology
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• v.25 no.4
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• pp.257-263
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• 2016

Among several technologies related to human brain, Brain Computer Interface (BCI) system is one of the most notable technologies recently. Conventional BCI for direct communication between human brain and machine are discomfort because normally electroencephalograghy(EEG) signal is measured by using multichannel EEG sensor. In this study, we propose 2-channel EEG sensor-based application control system which is more convenience and low complexity to wear to get EEG signal. EEG sensor module and system algorithm used in this study are developed and designed and one of the BCI methods, Motor Imagery (MI) is implemented in the system. Experiments are consisted of accuracy measurement of MI classification and driving control test. The results show that our simple wearable system has comparable performance with studies using multi-channel EEG sensor-based system, even better performance than other studies.

• Journal of the Korean Society of Physical Medicine
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• v.5 no.3
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• pp.395-404
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• 2010

Purpose : The object of this study was to examine the effect of motor learning on brain activation depending on the method of motor learning. Methods : The brain activation was measured in 9 men by fMRI. The subjects were divided into the following groups depending on the method of motor learning: actually practice (AP, n=3) group, action observation (AO, n=3) group and motor imagery (MI, n=3) group. In order to examine the effect of motor learning depending on the method of motor learning, the brain activation data were measured during learning. For the investigation of brain activation, fMRI was conducted. Results : The results of brain activation measured before and during learning were as follows; (1) During learning, the AP group showed the activation in the following areas: primary motor area located in precentral gyrus, somatosensory area located in postcentral gyrus, supplemental motor area and prefrontal association area located in precentral gyrus, middle frontal gyrus and superior frontal gyrus, speech area located in superior temporal gyrus and middle temporal gyrus, Broca's area located in inferior parietal lobe and somatosensory association area of precuneus; (2) During learning, the AD groups showed the activation in the following areas: primary motor area located in precentral gyrus, prefrontal association area located in middle frontal gyrus and superior frontal gyrus, speech area and supplemental motor area located in superior temporal gyrus and middle temporal gyrus, Broca's area located in inferior parietal lobe, somatosensory area and primary motor area located in precentral gyrus of right cerebrum and left cerebrum, and somatosensory association area located in precuneus; and (3) During learning, the MI group showed activation in the following areas: speech area located in superior temporal gyrus, supplemental area, and somatosensory association area located in precuneus. Conclusion : Given the results above, in this study, the action observation was suggested as an alternative to motor learning through actual practice in serial reaction time task of motor learning. It showed the similar results to the actual practice in brain activation which were obtained using activation of mirror neuron. This result suggests that the brain activation occurred by the activation of mirror neuron, which was observed during action observation. The mirror neurons are located in primary motor area, somatosensory area, premotor area, supplemental motor area and somatosensory association area. In sum, when we plan a training program through physiotherapy to increase the effect during reeducation of movement, the action observation as well as best resting is necessary in increasing the effect of motor learning with the patients who cannot be engaged in actual practice.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.1
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• pp.7-13
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• 2018

In the current study, we proposed an optimized brain-computer interface (BCI) which employed blind source separation (BBS) approach to remove noises. Thus motor imagery (MI) signal and steady state visual evoked potential (SSVEP) signal were easily to be detected due to enhancement in signal-to-noise ratio (SNR). Moreover, a combination between MI and SSVEP which is typically can increase the number of commands being generated in the current BCI. To reduce the computational time as well as to bring the BCI closer to real-world applications, the current system utilizes a single-channel EEG signal. In addition, a convolutional neural network (CNN) was used as the multi-class classification model. We evaluated the performance in term of accuracy between a non-BBS+BCI and BBS+BCI. Results show that the accuracy of the BBS+BCI is achieved $16.15{\pm}5.12%$ higher than that in the non-BBS+BCI by using BBS than non-used on. Overall, the proposed BCI system demonstrate a feasibility to be applied for multi-dimensional control applications with a comparable accuracy.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1661-1664
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• 2013

본 연구는 만성 뇌졸중 환자 5 명을 대상으로 상지 운동(Affected hand의 주먹 쥐기/펴기운동)시 참가자의 운동의지와 운동 수행의 유무에 따라 차이가 있을 것을 가정하고, 운동 수행 및 운동의지가 존재하는 Active movement와 운동 수행을 하지만 운동의지가 없는 Passive movement, 운동 수행은 없지만 운동의지가 있는 Motor Imagery(MI)의 세가지 task에 따른 뇌파의 연결성을 비교하고자 한다. 이 때 EEG 영역 간의 연결성을 보기 위한 분석 방식 중 하나인 Phase locking value(PLV)를 통해 각 task 간의 차이를 비교 및 분석했다. 운동 수행은 동일하지만 운동의지 유무에 따른 차이는 Passive movement가 전반적으로 뇌 영역간 연결이 감소하고 Active movement가 motor task 시작 후 375ms를 기점으로 급격히 증가함을 보이는 데에서 발견할 수 있었으며, 운동 수행 유무에 따른 차이는 687.5ms 이후 Active movement에 비해 MI에서 뇌 영역 간 연결 수가 확연히 감소하는 데에서 큰 차이를 나타내었다. 이에 따라 본 연구에서는 만성 뇌졸중 환자의 상지운동 시의 motor task에 따른 EEG 영역간의 연결성을 토대로 운동의지 검출이 가능성이 있음을 밝혔다.