Auswahl der wissenschaftlichen Literatur zum Thema „Motor abilities rehabilitation“
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Zeitschriftenartikel zum Thema "Motor abilities rehabilitation"
D’Imperio, Daniela, Zaira Romeo, Lorenza Maistrello, Eugenia Durgoni, Camilla Della Pietà, Michele De Filippo De Grazia, Francesca Meneghello, Andrea Turolla und Marco Zorzi. „Sensorimotor, Attentional, and Neuroanatomical Predictors of Upper Limb Motor Deficits and Rehabilitation Outcome after Stroke“. Neural Plasticity 2021 (01.04.2021): 1–12. http://dx.doi.org/10.1155/2021/8845685.
Der volle Inhalt der QuelleReid, Denise. „A Neo-Piagetian Analysis of Infants' Visual-Motor Abilities“. Occupational Therapy Journal of Research 9, Nr. 5 (September 1989): 287–304. http://dx.doi.org/10.1177/153944928900900503.
Der volle Inhalt der QuelleBeretta, Elena, Ambra Cesareo, Cristina Maghini, Anna C. Turconi, Gianluigi Reni, Sandra Strazzer und Emilia Biffi. „An Immersive Virtual Reality Platform to Enhance Walking Ability of Children with Acquired Brain Injuries“. Methods of Information in Medicine 56, Nr. 02 (2017): 119–26. http://dx.doi.org/10.3414/me16-02-0020.
Der volle Inhalt der QuelleFasoli, Susan E., Hermano I. Krebs, Mark Ferraro, Neville Hogan und Bruce T. Volpe. „Does Shorter Rehabilitation Limit Potential Recovery Poststroke?“ Neurorehabilitation and Neural Repair 18, Nr. 2 (Juni 2004): 88–94. http://dx.doi.org/10.1177/0888439004267434.
Der volle Inhalt der QuelleCorallo, Francesco, Carmela Rifici und Viviana Lo Buono. „Rehabilitation in atypical neurological disease: a case report“. Journal of International Medical Research 50, Nr. 6 (Juni 2022): 030006052211020. http://dx.doi.org/10.1177/03000605221102083.
Der volle Inhalt der QuelleYoung, Susanne Yvette, Martin Kidd und Soraya Seedat. „Motor Timing Outcome Differences between Patients with Alcohol- and/or Cocaine Use Disorder in a Rehabilitation Program“. Timing & Time Perception 7, Nr. 1 (11.01.2019): 48–70. http://dx.doi.org/10.1163/22134468-20181137.
Der volle Inhalt der QuelleChen, Jianan, Yunjia Xia, Xinkai Zhou, Ernesto Vidal Rosas, Alexander Thomas, Rui Loureiro, Robert J. Cooper, Tom Carlson und Hubin Zhao. „fNIRS-EEG BCIs for Motor Rehabilitation: A Review“. Bioengineering 10, Nr. 12 (06.12.2023): 1393. http://dx.doi.org/10.3390/bioengineering10121393.
Der volle Inhalt der QuelleBannink, Femke, Johnny R. J. Fontaine, Richard Idro und Geert Van Hove. „Cognitive Abilities of Pre- and Primary School Children with Spina Bifida in Uganda“. International Journal of Educational Psychology 5, Nr. 3 (24.10.2016): 249. http://dx.doi.org/10.17583/ijep.2016.2075.
Der volle Inhalt der QuelleKnežević, Dora. „Motor abilities of children with childhood apraxia of speech“. Hrvatska revija za rehabilitacijska istraživanja 58, Nr. 2 (22.12.2022): 81–91. http://dx.doi.org/10.31299/hrri.58.2.5.
Der volle Inhalt der QuellePanasenko, Karina E., Ludmila V. Shinkareva, Tatiana A. Altukhova, Elena A. Nikolaeva und Elena V. Shatalova. „Study and Assessment of Motor Abilities of Older Children of Pre-school Age With Speech Disorders“. Iranian Rehabilitation Journal 21, Nr. 1 (01.03.2023): 97–106. http://dx.doi.org/10.32598/irj.21.1.1695.1.
Der volle Inhalt der QuelleDissertationen zum Thema "Motor abilities rehabilitation"
Meziani, Yeser. „A Kinematic Framework for Upper Extremity Rehabilitation Assessment : Expectation- Maximization as a Motor Learning Model“. Electronic Thesis or Diss., Université de Lorraine, 2022. http://www.theses.fr/2022LORR0096.
Der volle Inhalt der QuelleMotor learning as a recovery mechanism is assumed to be a framework that drived and guided physical therapy and now since the advent of robotics doing the same to the rehabilitation devices. The rehabilitation process presents the intersection of many different interconnected facets that co-interact to produce recovered movements. The use of the technology introduces many benefits while contributing to the complexity of the phenomena at hand. We interest our research to the passive exosquelette training of the upper limb. We propose an adaptive intra patient assessment scale that is capable of detecting intra-patient performance changes during robotic training. Motor learning, the process of our brain's acquiring newer motor skills or relearning those he lost due to neurological or traumatic incident is our portal to investigating this phenomenon. The interaction of the system that is composed of the device, the incentive in form of exercise games and the patients with all its level of existence, physiological, psycho-logical, and cognitive is the system of study. The components present heterogeneous qualities and dynamically driven changes. The system output in the form of the trajectories executed is our gauging instrument to investigate the interactions within the system. We formulate the trajectory model as a Markov Chain and use the Kalman Filter to estimate the smoothed states. While dynamics are variant in time we model the assumptions about the movement into a dynamical formulation and estimate its parameters from data. To account for the time variability we introduce parallel noise source to the dynamics and estimate it using an Expectation-Maximization algorithm. The temporal nature being only a single facet of the kinematic phenomena, we assume a variable temporal alignment and estimate it using Expectation-Maximization iteration to increase the likelyhood of the estimated model compared to the observed trajectories. Once learned the model dependent and extracted parameters are used to compare between differences in performance. The properties of the clinical assessment tools are investigated and results are formulated to answer the commonly reported needs. Stemming from the same fundamentals of motor learning, we aimed to define a new visual assessment instrument that is intended to fulfill the need of patient-first easily communicated feedback form. We present and assess clinical properties of the tools while providing validating results on clinical data attesting the longitudinal sensitivity of the tool. The underlying assumption of the visualization was then assessed using an objective measure of maximum probability value derived using a probabilistic model of the trajectories and expected on a highly likely trajectory model learned using a Kernel-Near-Neighbors Regressor
Patel, Avani Rajnikant. „Cognitive Rehab Solutions: A computer-assisted cognitive training program“. CSUSB ScholarWorks, 2002. https://scholarworks.lib.csusb.edu/etd-project/2321.
Der volle Inhalt der QuelleBücher zum Thema "Motor abilities rehabilitation"
Vasil'ev, Oleg, Evgeniy Achkasov und Sergey Levushkin. Damage to the musculoskeletal system from overload in ballet and sports medicine. ru: INFRA-M Academic Publishing LLC., 2023. http://dx.doi.org/10.12737/1938064.
Der volle Inhalt der QuelleBuchteile zum Thema "Motor abilities rehabilitation"
Chen, Weiqin, Martin Bang, Daria Krivonos, Hanna Schimek und Arnau Naval. „An Immersive Virtual Reality Exergame for People with Parkinson’s Disease“. In Lecture Notes in Computer Science, 138–45. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58796-3_18.
Der volle Inhalt der QuelleLederman, Eyal. „Motor abilities“. In Neuromuscular Rehabilitation in Manual and Physical Therapy, 19–39. Elsevier, 2010. http://dx.doi.org/10.1016/b978-0-443-06969-7.00003-6.
Der volle Inhalt der QuelleLederman, Eyal. „Motor abilities, assessment to challenge“. In Neuromuscular Rehabilitation in Manual and Physical Therapy, 129–61. Elsevier, 2010. http://dx.doi.org/10.1016/b978-0-443-06969-7.00012-7.
Der volle Inhalt der QuelleNap, Henk Herman, und Unai Diaz-Orueta. „Rehabilitation Gaming“. In Gamification for Human Factors Integration, 122–47. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-5071-8.ch008.
Der volle Inhalt der QuelleFrancisco, Gerard E. „Pharmacologic Management of Spastic Hypertonia“. In Rehabilitation for Traumatic Brain Injury, 271–304. Oxford University PressNew York, NY, 2005. http://dx.doi.org/10.1093/oso/9780195173550.003.0014.
Der volle Inhalt der QuelleMarques, António José Pereira Silva, Helena Maria Martins Caldas, Mariana Castro Barbosa, Luís Miguel Brazão Soares, Maria Inês Dias Ribeiro und Vítor Simões-Silva. „Gamification in Stroke Rehabilitation“. In Advances in Psychology, Mental Health, and Behavioral Studies, 187–99. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-7998-8634-1.ch009.
Der volle Inhalt der QuelleI. San Martín Valenzuela, Constanza. „Dementia and Physical Therapy“. In Dementia in Parkinson's Disease [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.98773.
Der volle Inhalt der QuelleScano, Alessandro, Marco Caimmi, Andrea Chiavenna, Matteo Malosio und Lorenzo Molinari Tosatti. „A Kinect-Based Biomechanical Assessment of Neurological Patients' Motor Performances for Domestic Rehabilitation“. In Advances in Medical Technologies and Clinical Practice, 252–79. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9740-9.ch013.
Der volle Inhalt der QuelleScano, Alessandro, Marco Caimmi, Andrea Chiavenna, Matteo Malosio und Lorenzo Molinari Tosatti. „A Kinect-Based Biomechanical Assessment of Neurological Patients' Motor Performances for Domestic Rehabilitation“. In Robotic Systems, 811–37. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1754-3.ch042.
Der volle Inhalt der QuelleNambiar, Amrutha, Sivakumar Rajagopal und Shamala Subramaniam. „Detection of Four Class Motor Imagery from EEG Signal for Brain-Computer Interface Applications“. In Advances in Transdisciplinary Engineering. IOS Press, 2023. http://dx.doi.org/10.3233/atde231028.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Motor abilities rehabilitation"
Eremushkin, M. A., und E. M. Styazhkina. „Optimization of motor abilities in programs of medical rehabilitation“. In ARBAT READING. Знание-М, 2020. http://dx.doi.org/10.38006/907345-21-8.2020.33.40.
Der volle Inhalt der QuellePacheco, Kevin, Kevin Acuna, Erick Carranza, David Achanccaray und Javier Andreu-Perez. „Performance predictors of motor imagery brain-computer interface based on spatial abilities for upper limb rehabilitation“. In 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2017. http://dx.doi.org/10.1109/embc.2017.8036998.
Der volle Inhalt der QuelleWei, Liyan, Wenxuan Cheng, Zhengzheng Luo, Mo Kit Yu, Chan Hiu Tung, Zhengtao Ma, Yaqi Zhang und Stephen Jia Wang. „Designing A Rehabilitation-Purposed No-Direct-Contact Collaborative Robotic System For Stroke Patients“. In 5th International Conference on Human Systems Engineering and Design: Future Trends and Applications (IHSED 2023). AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1004116.
Der volle Inhalt der QuellePtak-Wojciechowska, Agnieszka, Magda Matuszewska und Agata Gawlak. „Senior-friendly apartments in the context of professional activation of the elderly“. In 14th International Conference on Applied Human Factors and Ergonomics (AHFE 2023). AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1003337.
Der volle Inhalt der QuelleBerichte der Organisationen zum Thema "Motor abilities rehabilitation"
WU, Jingyi, Jiaqi LI, Ananda Sidarta und Patrick Wai Hang Kwong. Neural mechanisms of bimanual coordination in humans and application of neuromodulation therapy: a scoping review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, Mai 2023. http://dx.doi.org/10.37766/inplasy2023.5.0080.
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