Brain to Movement: Motion Intention Prediction (Journal-25mins)
Citation: Tang, C., Xu, Z., Occhipinti, E., Yi, W., Xu, M., Kumar, S., Virk, G. S., Gao, S., & Occhipinti, L. G. (2023). From brain to movement: Wearables-based motion intention prediction across the human nervous system. Nano Energy, 115, 108712. https://doi.org/10.1016/j.nanoen.2023.108712
Abstract: This article examines non-invasive techniques, including Electroencephalogram (EEG) and near-infrared spectroscopy (NIRS), for the application of wearable technology in predicting motion intention.
License: This is an open-access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Motor Practice on Position Control, Force Control and Corticomusculoar Coherence (Journal - 25-30mins)
Citation: Norup, Malene; Nielsen, August Lomholt; Bjorndal, Jonas Rud; Wiegel, Patrick; Spedden, Meaghan Elizabeth; Lundbye-Jensen, Jesper; (2023) Effects of dynamic and isometric motor practice on position control, force control and corticomuscular coherence in preadolescent children. Human Movement Science , 90 , Article 103114. 10.1016/j.humov.2023.103114.
Abstract: The study examined the impact of motor practice when focusing on either position or force control on motor performance, accuracy, and variability among preadolescent children. Additionally, corticomuscular coherence was assessed to identify potential changes resulting from motor skills development. Notably, findings indicate that children demonstrate improved performance when provided with augmented feedback (information that is given to the learner, that does not come from their own sensory feedback), suggesting that this additional information is used to guide their movements and/or that enhanced feedback increases their motivation, which leads to improvement of overall performance.
License: Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).