Literatura científica selecionada sobre o tema "Kinesthetic motor imagery"
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Artigos de revistas sobre o assunto "Kinesthetic motor imagery"
Sadato, Norihiro, e Eiichi Naito. "Emulation of kinesthesia during motor imagery". Behavioral and Brain Sciences 27, n.º 3 (junho de 2004): 412–13. http://dx.doi.org/10.1017/s0140525x0438009x.
Texto completo da fonteRyo, K. "Kinestheitc motor imagery internally generate kinesthetic sensations". Neuroscience Research 38 (2000): S153. http://dx.doi.org/10.1016/s0168-0102(00)81764-2.
Texto completo da fonteKwon, Sechang, Jingu Kim e Teri Kim. "Neuropsychological Activations and Networks While Performing Visual and Kinesthetic Motor Imagery". Brain Sciences 13, n.º 7 (22 de junho de 2023): 983. http://dx.doi.org/10.3390/brainsci13070983.
Texto completo da fonteZhang, Lanlan, Yanling Pi, Hua Zhu, Cheng Shen, Jian Zhang e Yin Wu. "Motor experience with a sport-specific implement affects motor imagery". PeerJ 6 (27 de abril de 2018): e4687. http://dx.doi.org/10.7717/peerj.4687.
Texto completo da fonteCoker Girón, Elizabeth, Tara Mclsaac e Dawn Nilsen. "Effects of Kinesthetic versus Visual Imagery Practice on Two Technical Dance Movements". Journal of Dance Medicine & Science 16, n.º 1 (março de 2012): 36–38. http://dx.doi.org/10.1177/1089313x1201600105.
Texto completo da fonteStepp, C. E., N. Oyunerdene e Y. Matsuoka. "Kinesthetic Motor Imagery Modulates Intermuscular Coherence". IEEE Transactions on Neural Systems and Rehabilitation Engineering 19, n.º 6 (dezembro de 2011): 638–43. http://dx.doi.org/10.1109/tnsre.2011.2168982.
Texto completo da fonteRodrigues, E. C., T. Lemos, B. Gouvea, E. Volchan, L. A. Imbiriba e C. D. Vargas. "Kinesthetic motor imagery modulates body sway". Neuroscience 169, n.º 2 (agosto de 2010): 743–50. http://dx.doi.org/10.1016/j.neuroscience.2010.04.081.
Texto completo da fonteOldrati, Viola, Alessandra Finisguerra, Alessio Avenanti, Salvatore Maria Aglioti e Cosimo Urgesi. "Differential Influence of the Dorsal Premotor and Primary Somatosensory Cortex on Corticospinal Excitability during Kinesthetic and Visual Motor Imagery: A Low-Frequency Repetitive Transcranial Magnetic Stimulation Study". Brain Sciences 11, n.º 9 (10 de setembro de 2021): 1196. http://dx.doi.org/10.3390/brainsci11091196.
Texto completo da fonteOzlem, Ozcan, e Kul Hayriye. "Kinesthetic and visual imagery in young adults with chronic neck pain". Sanamed, n.º 00 (2022): 4. http://dx.doi.org/10.5937/sanamed17-37885.
Texto completo da fonteRamezanzade, Hesam, Georgian Badicu, Stefania Cataldi, Fateme Parimi, Sahar Mohammadzadeh, Mahya Mohamadtaghi, Seyed Hojjat Zamani Zamani Sani e Gianpiero Greco. "Sonification of Motor Imagery in the Basketball Jump Shot: Effect on Muscle Activity Amplitude". Applied Sciences 13, n.º 3 (23 de janeiro de 2023): 1495. http://dx.doi.org/10.3390/app13031495.
Texto completo da fonteTeses / dissertações sobre o assunto "Kinesthetic motor imagery"
Herrera, Altamira Gabriela. "Vibrotactile feedback to support kinesthetic motor imagery in a brain-computer interface for post-stroke motor rehabilitation". Electronic Thesis or Diss., Université de Lorraine, 2024. https://docnum.univ-lorraine.fr/ulprive/DDOC_T_2024_0002_HERRERA_ALTAMIRA.pdf.
Texto completo da fonteMotor imagery-based brain-computer interfaces (BCI) offer promising solutions for post-stroke motor rehabilitation. Kinesthetic motor imagery (KMI) consists of imagining the sensations of a movement (such as temperature, pressure, roughness, muscular contraction, and nerve activation) rather than visualizing the movement. However, KMI lacks sensory or kinesthetic feedback, making this task challenging to understand, learn, and perform. This absence of feedback hinders performance evaluation and therapeutic guidance for post-stroke patients. To address this issue, feedback is provided to both patients and therapists, based on the patient's performance. Various feedback modalities, including visual, functional electrical stimulation, exoskeletons, and robotic assistance, have been explored to bridge this gap. Vibrotactile feedback is an underexplored alternative, that offers skin stimulation, targeting patients with limited mobility. Combining different feedback modalities has emerged as a promising approach to provide more effective feedback and enhance the rehabilitation process. The development of BCI feedback has often prioritized technological advancement over patient-centric considerations, resulting in limited clinical adoption. This thesis adopts a novel design-based research (DBR) approach, placing the user at the core of feedback system development. The objective is to design and evaluate vibrotactile feedback, complemented with visual feedback and integrated it with a KMI-based BCI to improve post-stroke motor rehabilitation. We start by identifying the needs and objectives of patients undergoing BCI training, leading to the hypothesis that bimodal feedback (combining vibrotactile and visual modalities) can enhance KMI within the BCI context. We tailor the vibrotactile stimulation to provide precise sensory feedback during grasping KMI. The vibrotactile device is then built considering the anatomical and physical limitations of post-stroke patients. Then, the vibrotactile stimulation is built in two phases: establishing vibration sensory thresholds for age-dependent groups and synchronizing a visual environment with vibrotactile stimulation. Different vibration patterns are compared to determine the one that better corresponds to the graphic animation. The stimulation was designed, drawing inspiration from the natural muscle activation of the muscles during grasping. Following the validation of the stimulation, the BCI is assessed with a group of neurotypical participants to measure its efficacy in improving KMI and evaluate its acceptability, usability, and reliability. Three feedback modalities (vibrotactile, visual and bimodal - vibrotactile and visual) are compared to determine their effectiveness. This research highlights the potential of a user-centered approach for developing feedback solutions that enhance motor imagery and rehabilitation outcomes. Furthermore, an experimental protocol is presented for future studies with post-stroke patients to assess the acceptability and usability of the meticulously designed BCI with bimodal feedback. The findings of this work lay the foundation for translating the resulting BCI into practical clinical applications, ultimately benefiting post-stroke patients
Jackson, Elizabeth Helene. "An exploratory examination of the electroencephalographic correlates of aural imagery, kinesthetic imagery, music listening, and motor movement by novice and expert conductors". The Ohio State University, 1994. http://rave.ohiolink.edu/etdc/view?acc_num=osu1345482654.
Texto completo da fonteRabahi, Tahar. "Étude des relations entre stimuli cognitifs et la motricité relative à un geste complexe". Thesis, Lyon 1, 2014. http://www.theses.fr/2014LYO10023/document.
Texto completo da fonteSeveral studies have shown that cortical motor areas, located in the frontal cortex and responsible for voluntary movement, might be involved in the process of understanding action words. From this point of view, it has been reported that the performance of a simple motor act (e.g.: catching an object) might be improved by the pronunciation, reading or listening to words referring to the action. We approached the relationship between speech and action through the study of the effect of action verbs and other cognitive stimuli, kinesthetic imagery (KI) and mental subtraction (MS), upon the performance of a complex motor act, the Squat vertical jump (SVJ). We measured the height of SVJ in young naive men (7 experiments, n = 114) and women (2 experiments, n = 41) using an Optojump® and a Myotest® apparatuses. The results showed that the silent and loud pronunciation of specific action verb to SVJ (jump), the KI and the MS improved significantly the performance of the movement, in men (up to 2.7 cm) but less in women (up to + 1 cm in the 2 experiments). The results of other experiments obtained with men indicated that pronunciation of the action verb nonspecific to the jump (pinch) increased also the SVJ performance, while the pronunciation or listening to other verbs unrelated to the jump (Jick, move) had no significant effect on the SVJ. A meaningless verb for the French subjects (tiao = jump in Chinese) showed, in turn, no effect as did dream, faJJ and stop. The verb win improved significantly the SVJ height as much as its antonym Jose, thus suggesting a possible influence of affects in the subjects' performance. It appears that the effects of the specific action verb jump did seem effective but not totally exclusive for the enhancement of the SVJ performance, since non-linguistic stimuli (IK) or unrelated to action (MS) may have had a positive effect on the improvement in motor performance. Moreover verbs referring to emotion, unrelated to action, increased the height of SVJ similarly to the specific action verb jump. The results led us to consider the hypothesis that improving the performance of a complex gesture is dependent, a minima, upon the individual's intention, attention, emotions and also, and perhaps most importantly, concepts (we call concepts, the mental representations) as they may be induced by the cerebral processing of words
Capítulos de livros sobre o assunto "Kinesthetic motor imagery"
Anema, Helen A., e H. Chris Dijkerman. "Motor and Kinesthetic Imagery". In Multisensory Imagery, 93–113. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-5879-1_6.
Texto completo da fonteStecklow, M. V., M. Cagy e A. F. C. Infantosi. "Investigating the EEG Alpha Band during Kinesthetic and Visual Motor Imagery of the Spike Volleyball Movement". In XII Mediterranean Conference on Medical and Biological Engineering and Computing 2010, 41–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13039-7_11.
Texto completo da fonteBunno, Yoshibumi, Chieko Onigata e Toshiaki Suzuki. "Motor imagery in evidence-based physical therapy". In Physical Therapy - Towards Evidence-Based Practice [Working Title]. IntechOpen, 2023. http://dx.doi.org/10.5772/intechopen.1003041.
Texto completo da fonteShah, Rakshit, Sohail Daulat, Vadivelan Ramu, Viashen Moodley, Puja Sengupta, Deepa Madathil, Yifei Yao e Kishor Lakshminarayanan. "Applications of Brain-Computer Interface in Action Observation and Motor Imagery". In New Insights in Brain-Computer Interface Systems [Working Title]. IntechOpen, 2023. http://dx.doi.org/10.5772/intechopen.114042.
Texto completo da fonteSvard, Lois. "Imagery—Music in the Mind’s Eye, Ear, Body". In The Musical Brain, 149—C8P71. Oxford University PressNew York, 2023. http://dx.doi.org/10.1093/oso/9780197584170.003.0008.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Kinesthetic motor imagery"
Igasaki, Tomohiko, Junya Takemoto e Katsuya Sakamoto. "Relationship Between Kinesthetic/Visual Motor Imagery Difficulty and Event-Related Desynchronization/Synchronization". In 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2018. http://dx.doi.org/10.1109/embc.2018.8512673.
Texto completo da fonteRimbert, Sebastien, Cecilia Lindig-Leon e Laurent Bougrain. "Profiling BCI users based on contralateral activity to improve kinesthetic motor imagery detection". In 2017 8th International IEEE/EMBS Conference on Neural Engineering (NER). IEEE, 2017. http://dx.doi.org/10.1109/ner.2017.8008383.
Texto completo da fonteArfaras, G., A. Athanasiou, N. Pandria, K. R. Kavazidi, P. Kartsidis, A. Astaras e P. D. Bamidis. "Visual Versus Kinesthetic Motor Imagery for BCI Control of Robotic Arms (Mercury 2.0)". In 2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS). IEEE, 2017. http://dx.doi.org/10.1109/cbms.2017.34.
Texto completo da fonteSakamoto, Katsuya, Junya Takemoto e Tomohiko Igasaki. "Investigation of kinesthetic and visual motor imagery differences during movement tasks using electroencephalograms". In 2017 10th Biomedical Engineering International Conference (BMEiCON). IEEE, 2017. http://dx.doi.org/10.1109/bmeicon.2017.8229139.
Texto completo da fonteCraik, Alexander, Atilla Kilicarslan e Jose L. Contreras-Vidal. "Classification and Transfer Learning of EEG during a Kinesthetic Motor Imagery Task using Deep Convolutional Neural Networks". In 2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). IEEE, 2019. http://dx.doi.org/10.1109/embc.2019.8857575.
Texto completo da fonteStecklow, M. V., M. Cagy e A. F. C. Infantosi. "Event-related synchronization/desynchronization to assess changes in alpha peak frequency along time during kinesthetic motor imagery". In 2011 Pan American Health Care Exchanges (PAHCE 2011). IEEE, 2011. http://dx.doi.org/10.1109/pahce.2011.5871909.
Texto completo da fonteIgasaki, Tomohiko, Arata Shibuta e Katsuya Sakamoto. "Evaluation of Kinesthetic/Visual Motor Imagery of Dorsiflexion of the Right Ankle Joint via Event-Related Desynchronization/Synchronization". In 2019 International Biomedical Instrumentation and Technology Conference (IBITeC). IEEE, 2019. http://dx.doi.org/10.1109/ibitec46597.2019.9091709.
Texto completo da fonteMosqueda-Herrera, A., D. Martinez-Peon, L. Gomez-Sanchez, Marco I. Ramirez-Sosa, S. Delfin-Prieto e F. G. Benavides-Bravo. "Characterization of Kinesthetic Motor Imagery paradigm for wrist and forearm using an algorithm based on the Hurst Exponent and Variogram". In 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, 2020. http://dx.doi.org/10.1109/smc42975.2020.9282888.
Texto completo da fonteGuerrero-Mendez, Cristian D., Cristian F. Blanco-Diaz, Denis Delisle-Rodriguez, Andrés F. Ruiz-Olaya, Sebastián Jaramillo-Isaza e Teodiano F. Bastos-Filho. "Analysis of EEG Rhythms During Four-Direction First-Person Reach-to-Grasp Kinesthetic Motor Imagery Tasks from the Same Limb". In 2023 IEEE 3rd Colombian BioCAS Workshop. IEEE, 2023. http://dx.doi.org/10.1109/colbiocas59270.2023.10280841.
Texto completo da fonteRimbert, Sebastien, Laurent Bougrain e Stephanie Fleck. "Learning How to Generate Kinesthetic Motor Imagery Using a BCI-based Learning Environment: a Comparative Study Based on Guided or Trial-and-Error Approaches". In 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, 2020. http://dx.doi.org/10.1109/smc42975.2020.9283225.
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