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Physical activity of first graders in Norwegian after-school programs: A relevant contribution to the development of motor competencies and learning of movements? Investigated utilizing a mixed methods approach.

PloS one

Løndal K, Haugen ALH, Lund S, Riiser K.
PMID: 32353056
PLoS One. 2020 Apr 30;15(4):e0232486. doi: 10.1371/journal.pone.0232486. eCollection 2020.

BACKGROUND: Development of motor competencies and learning of movements in children is dependent on varied physical activity (PA). After-school programs (ASP) might provide opportunities for young schoolchildren to participate in PA. The aim of the current study was to...

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Løndal K, Haugen ALH, Lund S, et al. Physical activity of first graders in Norwegian after-school programs: A relevant contribution to the development of motor competencies and learning of movements? Investigated utilizing a mixed methods approach. PLoS One. 2020;15(4):e0232486doi: 10.1371/journal.pone.0232486.
Løndal, K., Haugen, A. L. H., Lund, S., & Riiser, K. (2020). Physical activity of first graders in Norwegian after-school programs: A relevant contribution to the development of motor competencies and learning of movements? Investigated utilizing a mixed methods approach. PloS one, 15(4), e0232486. https://doi.org/10.1371/journal.pone.0232486
Løndal, Knut, et al. "Physical activity of first graders in Norwegian after-school programs: A relevant contribution to the development of motor competencies and learning of movements? Investigated utilizing a mixed methods approach." PloS one vol. 15,4 (2020): e0232486. doi: https://doi.org/10.1371/journal.pone.0232486
Løndal K, Haugen ALH, Lund S, Riiser K. Physical activity of first graders in Norwegian after-school programs: A relevant contribution to the development of motor competencies and learning of movements? Investigated utilizing a mixed methods approach. PLoS One. 2020 Apr 30;15(4):e0232486. doi: 10.1371/journal.pone.0232486. eCollection 2020. PMID: 32353056; PMCID: PMC7192409.
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Weighted sparse representation for classification of motor imagery EEG signals.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

Sreeja SR, Himanshu, Samanta D, Sarma M.
PMID: 31947254
Annu Int Conf IEEE Eng Med Biol Soc. 2019 Jul;2019:6180-6183. doi: 10.1109/EMBC.2019.8857496.

Motor imagery (MI) based brain-computer interface systems (BCIs) are highly in demand for many real-time applications such as hands and touch-free text entry, prosthetic arms, virtual reality, movement of wheelchairs, etc. Traditional sparse representation based classification (SRC) is a...

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Sreeja SR, Himanshu, Samanta D, et al. Weighted sparse representation for classification of motor imagery EEG signals. Annu Int Conf IEEE Eng Med Biol Soc. 2019;2019:6180-6183doi: 10.1109/EMBC.2019.8857496.
Sreeja, S. R., Himanshu, Samanta, D., & Sarma, M. (2019). Weighted sparse representation for classification of motor imagery EEG signals. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 20196180-6183. https://doi.org/10.1109/EMBC.2019.8857496
Sreeja, S R, et al. "Weighted sparse representation for classification of motor imagery EEG signals." Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference vol. 2019 (2019): 6180-6183. doi: https://doi.org/10.1109/EMBC.2019.8857496
Sreeja SR, Himanshu, Samanta D, Sarma M. Weighted sparse representation for classification of motor imagery EEG signals. Annu Int Conf IEEE Eng Med Biol Soc. 2019 Jul;2019:6180-6183. doi: 10.1109/EMBC.2019.8857496. PMID: 31947254.
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Classification and Transfer Learning of EEG during a Kinesthetic Motor Imagery Task using Deep Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

Craik A, Kilicarslan A, Contreras-Vidal JL.
PMID: 31946530
Annu Int Conf IEEE Eng Med Biol Soc. 2019 Jul;2019:3046-3049. doi: 10.1109/EMBC.2019.8857575.

The reliable classification of Electroencephalography (EEG) signals is a crucial step towards making EEG-controlled non-invasive neuro-exoskeleton rehabilitation a practical reality. EEG signals collected during motor imagery tasks have been proposed to act as a control signal for exoskeleton applications....

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Craik A, Kilicarslan A, Contreras-Vidal JL. Classification and Transfer Learning of EEG during a Kinesthetic Motor Imagery Task using Deep Convolutional Neural Networks. Annu Int Conf IEEE Eng Med Biol Soc. 2019;2019:3046-3049doi: 10.1109/EMBC.2019.8857575.
Craik, A., Kilicarslan, A., & Contreras-Vidal, J. L. (2019). Classification and Transfer Learning of EEG during a Kinesthetic Motor Imagery Task using Deep Convolutional Neural Networks. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 20193046-3049. https://doi.org/10.1109/EMBC.2019.8857575
Craik, Alexander, et al. "Classification and Transfer Learning of EEG during a Kinesthetic Motor Imagery Task using Deep Convolutional Neural Networks." Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference vol. 2019 (2019): 3046-3049. doi: https://doi.org/10.1109/EMBC.2019.8857575
Craik A, Kilicarslan A, Contreras-Vidal JL. Classification and Transfer Learning of EEG during a Kinesthetic Motor Imagery Task using Deep Convolutional Neural Networks. Annu Int Conf IEEE Eng Med Biol Soc. 2019 Jul;2019:3046-3049. doi: 10.1109/EMBC.2019.8857575. PMID: 31946530.
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Inner Workings: Self-powered biomedical devices tap into the body's movements.

Proceedings of the National Academy of Sciences of the United States of America

Madhusoodanan J.
PMID: 31481627
Proc Natl Acad Sci U S A. 2019 Sep 03;116(36):17605-17607. doi: 10.1073/pnas.1912885116.

No abstract available.

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Madhusoodanan J. Inner Workings: Self-powered biomedical devices tap into the body's movements. Proc Natl Acad Sci U S A. 2019;116(36):17605-17607doi: 10.1073/pnas.1912885116.
Madhusoodanan, J. (2019). Inner Workings: Self-powered biomedical devices tap into the body's movements. Proceedings of the National Academy of Sciences of the United States of America, 116(36), 17605-17607. https://doi.org/10.1073/pnas.1912885116
Madhusoodanan, Jyoti. "Inner Workings: Self-powered biomedical devices tap into the body's movements." Proceedings of the National Academy of Sciences of the United States of America vol. 116,36 (2019): 17605-17607. doi: https://doi.org/10.1073/pnas.1912885116
Madhusoodanan J. Inner Workings: Self-powered biomedical devices tap into the body's movements. Proc Natl Acad Sci U S A. 2019 Sep 03;116(36):17605-17607. doi: 10.1073/pnas.1912885116. PMID: 31481627; PMCID: PMC6731626.
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A Curvilinear Effect of Mental Workload on Mental Effort and Behavioral Adaptability: An Approach With the Pre-Ejection Period.

Human factors

Mallat C, Cegarra J, Calmettes C, Capa RL.
PMID: 31260326
Hum Factors. 2020 Sep;62(6):928-939. doi: 10.1177/0018720819855919. Epub 2019 Jul 01.

OBJECTIVE: We tested Hancock and Szalma's mental workload model, which has never been experimentally validated at a global level with the measure of the pre-ejection period (PEP), an index of beta-adrenergic sympathetic impact.BACKGROUND: Operators adapt to mental workload. When...

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Mallat C, Cegarra J, Calmettes C, et al. A Curvilinear Effect of Mental Workload on Mental Effort and Behavioral Adaptability: An Approach With the Pre-Ejection Period. Hum Factors. 2019;62(6):928-939doi: 10.1177/0018720819855919.
Mallat, C., Cegarra, J., Calmettes, C., & Capa, R. L. (2020). A Curvilinear Effect of Mental Workload on Mental Effort and Behavioral Adaptability: An Approach With the Pre-Ejection Period. Human factors, 62(6), 928-939. https://doi.org/10.1177/0018720819855919
Mallat, Charlotte, et al. "A Curvilinear Effect of Mental Workload on Mental Effort and Behavioral Adaptability: An Approach With the Pre-Ejection Period." Human factors vol. 62,6 (2020): 928-939. doi: https://doi.org/10.1177/0018720819855919
Mallat C, Cegarra J, Calmettes C, Capa RL. A Curvilinear Effect of Mental Workload on Mental Effort and Behavioral Adaptability: An Approach With the Pre-Ejection Period. Hum Factors. 2020 Sep;62(6):928-939. doi: 10.1177/0018720819855919. Epub 2019 Jul 01. PMID: 31260326.
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A Novel Method to Understand Neural Oscillations During Full-Body Reaching: A Combined EEG and 3D Virtual Reality Study.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society

Wang WE, Ho RLM, Gatto B, Der Veen SMV, Underation MK, Thomas JS, Antony AB, Coombes SA.
PMID: 33232238
IEEE Trans Neural Syst Rehabil Eng. 2020 Dec;28(12):3074-3082. doi: 10.1109/TNSRE.2020.3039829. Epub 2021 Jan 28.

Virtual reality (VR) can be used to create environments that are not possible in the real-world. Producing movements in VR holds enormous promise for rehabilitation and offers a platform from which to understand the neural control of movement. However,...

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Wang WE, Ho RLM, Gatto B, et al. A Novel Method to Understand Neural Oscillations During Full-Body Reaching: A Combined EEG and 3D Virtual Reality Study. IEEE Trans Neural Syst Rehabil Eng. 2021;28(12):3074-3082doi: 10.1109/TNSRE.2020.3039829.
Wang, W. E., Ho, R. L. M., Gatto, B., Der Veen, S. M. V., Underation, M. K., Thomas, J. S., Antony, A. B., & Coombes, S. A. (2020). A Novel Method to Understand Neural Oscillations During Full-Body Reaching: A Combined EEG and 3D Virtual Reality Study. IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society, 28(12), 3074-3082. https://doi.org/10.1109/TNSRE.2020.3039829
Wang, Wei-En, et al. "A Novel Method to Understand Neural Oscillations During Full-Body Reaching: A Combined EEG and 3D Virtual Reality Study." IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society vol. 28,12 (2020): 3074-3082. doi: https://doi.org/10.1109/TNSRE.2020.3039829
Wang WE, Ho RLM, Gatto B, Der Veen SMV, Underation MK, Thomas JS, Antony AB, Coombes SA. A Novel Method to Understand Neural Oscillations During Full-Body Reaching: A Combined EEG and 3D Virtual Reality Study. IEEE Trans Neural Syst Rehabil Eng. 2020 Dec;28(12):3074-3082. doi: 10.1109/TNSRE.2020.3039829. Epub 2021 Jan 28. PMID: 33232238.
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Showing 49 to 54 of 54 entries