{"year":"2022","file_date_updated":"2022-04-04T10:07:48Z","file":[{"date_updated":"2022-04-04T10:07:48Z","date_created":"2022-04-04T10:07:48Z","access_level":"open_access","file_id":"1800","content_type":"application/pdf","relation":"main_file","file_size":2869767,"file_name":"sensors-22-02481-v3.pdf","success":1,"creator":"kvandevoorde"}],"tmp":{"short":"CC BY (4.0)","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"citation":{"ieee":"K. Vandevoorde, L. Vollenkemper, C. Schwan, M. Kohlhase, and W. Schenck, “Using Artificial Intelligence for Assistance Systems to Bring Motor Learning Principles into Real World Motor Tasks,” <i>Sensors</i>, vol. 22, no. 7, 2022.","chicago":"Vandevoorde, Koenraad, Lukas Vollenkemper, Constanze Schwan, Martin Kohlhase, and Wolfram Schenck. “Using Artificial Intelligence for Assistance Systems to Bring Motor Learning Principles into Real World Motor Tasks.” <i>Sensors</i> 22, no. 7 (2022). <a href=\"https://doi.org/10.3390/s22072481\">https://doi.org/10.3390/s22072481</a>.","apa":"Vandevoorde, K., Vollenkemper, L., Schwan, C., Kohlhase, M., &#38; Schenck, W. (2022). Using Artificial Intelligence for Assistance Systems to Bring Motor Learning Principles into Real World Motor Tasks. <i>Sensors</i>, <i>22</i>(7). <a href=\"https://doi.org/10.3390/s22072481\">https://doi.org/10.3390/s22072481</a>","short":"K. Vandevoorde, L. Vollenkemper, C. Schwan, M. Kohlhase, W. Schenck, Sensors 22 (2022).","alphadin":"<span style=\"font-variant:small-caps;\">Vandevoorde, Koenraad</span> ; <span style=\"font-variant:small-caps;\">Vollenkemper, Lukas</span> ; <span style=\"font-variant:small-caps;\">Schwan, Constanze</span> ; <span style=\"font-variant:small-caps;\">Kohlhase, Martin</span> ; <span style=\"font-variant:small-caps;\">Schenck, Wolfram</span>: Using Artificial Intelligence for Assistance Systems to Bring Motor Learning Principles into Real World Motor Tasks. In: <i>Sensors</i> Bd. 22, MDPI AG (2022), Nr. 7","bibtex":"@article{Vandevoorde_Vollenkemper_Schwan_Kohlhase_Schenck_2022, title={Using Artificial Intelligence for Assistance Systems to Bring Motor Learning Principles into Real World Motor Tasks}, volume={22}, DOI={<a href=\"https://doi.org/10.3390/s22072481\">10.3390/s22072481</a>}, number={72481}, journal={Sensors}, publisher={MDPI AG}, author={Vandevoorde, Koenraad and Vollenkemper, Lukas and Schwan, Constanze and Kohlhase, Martin and Schenck, Wolfram}, year={2022} }","mla":"Vandevoorde, Koenraad, et al. “Using Artificial Intelligence for Assistance Systems to Bring Motor Learning Principles into Real World Motor Tasks.” <i>Sensors</i>, vol. 22, no. 7, 2481, MDPI AG, 2022, doi:<a href=\"https://doi.org/10.3390/s22072481\">10.3390/s22072481</a>.","ama":"Vandevoorde K, Vollenkemper L, Schwan C, Kohlhase M, Schenck W. Using Artificial Intelligence for Assistance Systems to Bring Motor Learning Principles into Real World Motor Tasks. <i>Sensors</i>. 2022;22(7). doi:<a href=\"https://doi.org/10.3390/s22072481\">10.3390/s22072481</a>"},"date_created":"2022-04-04T10:08:43Z","issue":"7","oa":"1","quality_controlled":"1","keyword":["motor learning","motor skill learning","assistance system","artificial intelligence","machine learning","pose estimation","action recognition","human motion analysis"],"doi":"10.3390/s22072481","type":"journal_article","main_file_link":[{"open_access":"1","url":"https://www.mdpi.com/1424-8220/22/7/2481"}],"language":[{"iso":"eng"}],"intvolume":"        22","article_number":"2481","date_updated":"2024-03-27T14:01:14Z","has_accepted_license":"1","publication_status":"published","user_id":"245590","title":"Using Artificial Intelligence for Assistance Systems to Bring Motor Learning Principles into Real World Motor Tasks","publication":"Sensors","status":"public","_id":"1799","author":[{"last_name":"Vandevoorde","full_name":"Vandevoorde, Koenraad","id":"242844","first_name":"Koenraad"},{"full_name":"Vollenkemper, Lukas","last_name":"Vollenkemper","first_name":"Lukas","id":"245570"},{"first_name":"Constanze","last_name":"Schwan","full_name":"Schwan, Constanze"},{"last_name":"Kohlhase","full_name":"Kohlhase, Martin","id":"226669","first_name":"Martin","orcid":"0009-0002-9374-0720"},{"last_name":"Schenck","full_name":"Schenck, Wolfram","id":"224375","first_name":"Wolfram","orcid":"0000-0003-3300-2048"}],"publisher":"MDPI AG","urn":"urn:nbn:de:hbz:bi10-17992","volume":22,"publication_identifier":{"eissn":["1424-8220"]},"abstract":[{"lang":"eng","text":"                  Humans learn movements naturally, but it takes a lot of time and training to achieve expert performance in motor skills. In this review, we show how modern technologies can support people in learning new motor skills. First, we introduce important concepts in motor control, motor learning and motor skill learning. We also give an overview about the rapid expansion of machine learning algorithms and sensor technologies for human motion analysis. The integration between motor learning principles, machine learning algorithms and recent sensor technologies has the potential to develop AI-guided assistance systems for motor skill training. We give our perspective on this integration of different fields to transition from motor learning research in laboratory settings to real world environments and real world motor tasks and propose a stepwise approach to facilitate this transition.\r\n                "}]}