• PNF and Movement
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• v.13 no.2
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• pp.55-72
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• 2015

Purpose: The purpose of this study was to propose a new therapy algorithm that combines motor imagery and physiotherapy as a physiotherapeutic clinical intervention technique that can stimulate the recovery of damaged physical function for patients with stroke. Methods: A variety of scientific research results related to motor imagery were reviewed and analyzed to investigate their applicability to physiotherapy in clinics. Results: As a new therapy algorithm for the therapeutic approach of motor imagery in stroke rehabilitation, a therapy algorithm that combines motor imagery with physiotherapy is proposed, which consists of three stages or steps: STEP 1 motor imagery familiarization, STEP 2 explicit learning stage, and STEP 3 implicit learning. Conclusion: The new therapy algorithm proposed in this study is expected to be a very useful clinical therapeutic approach for stimulating the recovery of damaged physical function in patients with stroke. It is believed that it will be necessary to confirm and standardize the effects of the therapeutic algorithm proposed in this study in the future by conducting diverse clinical studies.

• Journal of the Korean Society of Physical Medicine
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• v.5 no.4
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• pp.517-525
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• 2010

Purpose : This study aimed to compare the effect of two conditions (visual and kinesthetic) of motor imagery training on static and dynamic balance. Methods : Fifteen patients with post-stroke hemiparesis volunteered to participate in this study. Two motor imagery training conditions, for 10minute trials, employed with audiotape instructions. Measurements were performed at pretest, posttest and 1-hour follow up in both static and dynamic balance. Results : Measures were significantly different both static and dynamic balance tests between treatment conditions (kinesthetic imagery more than visual imagery) at the pretest, post test, and 1-hour follow-up (p<.05). Measures of both static and dynamic balance tests, for both conditions, improved significantly from pretest to posttest (p<.05), and was maintained at 1-hour follow up. Conclusion : This study showed that both imagery training applications were effective treatment strategies for both static and dynamic balance. When comparing the two treatment conditions, kinesthetic motor imagery training was more effective than the visual motor imagery training in static and dynamic balance.

• Journal of International Academy of Physical Therapy Research
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• v.11 no.1
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• pp.1999-2004
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• 2020

Background: Although studies on physical motor learning through motor imagery training have been conducted in various fields, studies on its effectiveness are still considered insufficient. Objective: To investigate the effect of motor imagery training and balance training on static balance of asymptomatic adults in their 20s. Design: A quasi-experimental study. Methods: Thirty-six adults in their 20s who passed the tandem stance test were randomized to the motor imagery training group (MIG, n=12), motor imagery with balance training group (MIBG, n=12), and balance training group (BG, n=12). Each group underwent their respective interventions three times a week for four weeks, and changes in static balance were analyzed using multivariate analysis of variance. Results: Trace length was significantly lower in the MIBG than in the MIG and BG (P<.05), and a significant reduction in trace length in the MIBG was observed after the intervention as compared to the baseline (P<.05). Furthermore, a significantly lower velocity was observed in the MIBG than in the MIG and BG (P<.05), and a significant reduction of velocity in the MIBG was more observed after the intervention compared to the baseline (P<.05). Conclusion: These results suggest that motor imagery training enhance static balance in healthy college students.

• The Journal of Korean Physical Therapy
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• v.24 no.1
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• pp.7-14
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• 2012

Purpose: The purpose of this study was to investigate the effect of motor imagery on the onset time of the leg muscle and ankle injury score of patients with functional ankle instability. Methods: The study included 16 patients with ankle instability after their ankle sprains. Motor imagery was performed 3 times a week for 4 weeks. The onset time of leg muscles was measured by using the surface EMG in one leg standing position on tibialis anterior, peroneous longus and medial, lateral gastrocnemius. The pre- and post-intervention was measured by using the ankle injury score. Data was analyzed by a paired t-test. Results: The onset time was reduced but there was no significant difference (p>0.05). The order of muscle recruitment was changed. Anke injury score increased significantly after motor imagery (p<0.05). Conclusion: The results suggest that motor imagery was effective by showing delayed onset time of peroneal muscle in patients with functional ankle instability. In future studies, various conditions and disorders should all be considered for the effective analysis of motor imagery.

• Physical Therapy Rehabilitation Science
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• v.8 no.1
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• pp.52-59
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• 2019

Objective: The purpose of this review was to investigate whether motor imagery training has an effect on the recovery of upper extremity function in individuals with hemiparetic stroke or not. Design: A systematic review and meta-analysis. Methods: PubMed and three other databases were searched up to December 18th, 2018 and randomized controlled trials (RCTs) evaluating motor imagery training on upper extremity function in persons with a diagnosis of hemiparetic stroke were included. This review selected the following information from each study: surname of the first author, published year, nation, population, intervention, therapeutic intensity of intervention, therapeutic comparison, outcome measures, additional therapy, summary of results, and descriptive statistics of outcome measures. Results: This review selected seventeen RCTs with 487 stroke survivors and the following intervention methods: six motor imagery training with additional therapeutic technology, two motor imagery training with additional modified constraint-induced therapy, four mirror therapy, and five motor imagery training. Ten RCTs were eligible for meta-analysis after systematic review. The motor imagery group were more effective than the control group based on the Fugl-Meyer assessment (3.43; 95% confidence interval [CI], 1.65 to 5.22; heterogeneity [$chi^2=8.03$, df=8, $I^2=0%$], test of overall effect Z=3.76; test for subgroup differences [$chi^2=2.56$, df=2, $I^2=21.8%$]) and the Action Research Arm Test (1.32; 95% CI, -8.12 to 10.76; heterogeneity [$Tau^2=70.74$, $chi^2=15.22$, df=3, $I^2=80%$], test of overall effect Z=3.76). Conclusions: The results of this review suggests that motor imagery shows positive effectiveness on improving upper extremity function in persons with hemiparetic stroke.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06b
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• pp.34-36
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• 2006

In this paper we present a method of feature extraction for motor imagery single trial EEG classification, where we exploit nonnegative matrix factorization (NMF) to select discriminative features in the time-frequency representation of EEG. Experimental results with motor Imagery EEG data in BCI competition 2003. show that the method indeed finds meaningful EEG features automatically, while some existing methods should undergo cross-validation to find them.

• Journal of International Academy of Physical Therapy Research
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• v.11 no.1
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• pp.2005-2011
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• 2020

Background: Motor imagery is the mental representation of an action without overt movement or muscle activation. However, few previous studies have demonstrated motor imagery training effects as an objective assessment tool in patients with early stroke. Objective: To investigate the effect of motor imagery training on Somatosensory Evoked Potentials (SSEP) and upper limb function of stroke patients. Design: A quasi-experimental study. Methods: Twenty-four patients with stroke were enrolled in this study. All subjects were assigned to the experimental or control group. All participants received traditional occupational therapy for 30 minutes, 5 times a week. The experimental group performed an additional task of motor imagery training (MIT) 20 minutes per day, 5 days a week, for 4 weeks. Both groups were assessed using the SSEP amplitude, Fugl-Meyer assessment of upper extremity (FMA UE) and Wolf motor function test. Results: After the intervention, the experimental group showed significant improvement in SSEP amplitude and FMA UE than did the control group. Conclusion: These findings suggest that the MIT effectively improve the SSEP and upper limb function of stroke patients.

• 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 Electrical Engineering and Technology
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• v.11 no.6
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• pp.1812-1824
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• 2016

The neural dynamics underlying the causal network during motor planning or imagery in the human brain are not well understood. The lack of signal processing tools suitable for the analysis of nonlinear and nonstationary electroencephalographic (EEG) hinders such analyses. In this study, noise-assisted multivariate empirical mode decomposition (NA-MEMD) is used to estimate the causal inference in the frequency domain, i.e., partial directed coherence (PDC). Natural and intrinsic oscillations corresponding to the motor imagery tasks can be extracted due to the data-driven approach of NA-MEMD, which does not employ predefined basis functions. Simulations based on synthetic data with a time delay between two signals demonstrated that NA-MEMD was the optimal method for estimating the delay between two signals. Furthermore, classification analysis of the motor imagery responses of 29 subjects revealed that NA-MEMD is a prerequisite process for estimating the causal network across multichannel EEG data during mental tasks.

• The Journal of Korean Physical Therapy
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• v.32 no.2
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• pp.70-74
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• 2020

Purpose: This study examined whether 1) the motor inhibition response as cognitive-behavioral component is learning though a stop signal task using stop-signal paradigm, and 2) whether there is a difference in the learning degree according to imagery training and actual practice training. Methods: Twenty young adults (males: 9, females: 11) volunteered to participate in this study, and were divided randomly into motor imagery training (IT, n=10) and practice training (PT, n=10) groups. The PT group performed an actual practice stop-signal task, while the IT group performed imagery training, which showed a stop-signal task on a monitor of a personal computer. The non-signal reaction time and stop-signal reaction time of both groups were assessed during the stop-signal task. Results: In the non-signal reaction time, there were no significant intra-group and inter-group differences between pre- and post-intervention in both groups (p>0.05). The stop-signal reaction time showed a significant difference in the PT group in the intra-group analysis (p<0.05). On the other hand, there was no significant intra-group difference in the IT group and inter-group difference between pre- and post-intervention (p>0.05). Conclusion: These results showed that the motor inhibition response could be learned through a stop-signal task. Moreover, these findings suggest that actual practice is a more effective method for learning the motor inhibition response.