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The concept of activity recognition chain is investigated and used as a reference for the gesture recognition process. A sliding window allows the system to extract relevant features from the incoming data streams: mean values, standard deviations, maximum values, minimum values, energy, and correlations between homologous axes are calculated to identify and differentiate the performed actions. Machine learning algorithms are implemented to handle the recognition phase.<\/jats:p>","DOI":"10.1115\/1.4041704","type":"journal-article","created":{"date-parts":[[2018,10,10]],"date-time":"2018-10-10T15:34:28Z","timestamp":1539185668000},"update-policy":"https:\/\/doi.org\/10.1115\/crossmarkpolicy-asme","source":"Crossref","is-referenced-by-count":16,"title":["A Wearable Device to Detect in Real-Time Bimanual Gestures of Basketball Players During Training Sessions"],"prefix":"10.1115","volume":"19","author":[{"given":"Marco","family":"Mangiarotti","sequence":"first","affiliation":[{"name":"School of Industrial and Information Engineering, Politecnico di Milano, Milano 20133, Italy e-mail:"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Francesco","family":"Ferrise","sequence":"additional","affiliation":[{"name":"Politecnico di Milano, Department of Mechanical Engineering, Via La Masa 1, Milano 20156, Italy e-mail:"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Serena","family":"Graziosi","sequence":"additional","affiliation":[{"name":"Politecnico di Milano, Department of Mechanical Engineering, Via La Masa 1, Milano 20156, Italy e-mail:"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Francesco","family":"Tamburrino","sequence":"additional","affiliation":[{"name":"Politecnico di Milano, Department of Mechanical Engineering, Via La Masa 1, Milano 20156, Italy e-mail:"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Monica","family":"Bordegoni","sequence":"additional","affiliation":[{"name":"Politecnico di Milano, Department of Mechanical Engineering, Via La Masa 1, Milano 20156, Italy e-mail:"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"33","published-online":{"date-parts":[[2018,11,19]]},"reference":[{"key":"2019100316240195900_bib1","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1109\/MSPEC.2016.7420400","article-title":"Silicon Gets Sporty: Next-Gen Sensors Make Golf Clubs, Tennis Rackets, and Baseball Bats Smarter Than Ever","volume":"53","year":"2016","journal-title":"IEEE Spectrum"},{"key":"2019100316240195900_bib2","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1016\/j.procs.2016.09.126","article-title":"A Depth Camera-Based Human Activity Recognition Via Deep Learning Recurrent Neural Network for Health and Social Care Services","volume":"100","year":"2016","journal-title":"Procedia Comput. 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