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Interact."],"published-print":{"date-parts":[[2023,6,30]]},"abstract":"<jats:p>\n            Gestural interaction with freehands and while grasping an everyday object enables\n            <jats:italic>always-available input<\/jats:italic>\n            . To sense such gestures, minimal instrumentation of the user\u2019s hand is desirable. However, the choice of an effective but minimal IMU layout remains challenging, due to the complexity of the multi-factorial space that comprises diverse finger gestures, objects, and grasps. We present\n            <jats:italic>SparseIMU<\/jats:italic>\n            , a rapid method for selecting minimal inertial sensor-based layouts for effective gesture recognition. Furthermore, we contribute a computational tool to guide designers with optimal sensor placement. Our approach builds on an extensive microgestures dataset that we collected with a dense network of 17 inertial measurement units (IMUs). We performed a series of analyses, including an evaluation of the entire combinatorial space for freehand and grasping microgestures (393 K layouts), and quantified the performance across different layout choices, revealing new gesture detection opportunities with IMUs. Finally, we demonstrate the versatility of our method with four scenarios.\n          <\/jats:p>","DOI":"10.1145\/3569894","type":"journal-article","created":{"date-parts":[[2022,10,29]],"date-time":"2022-10-29T11:06:55Z","timestamp":1667041615000},"page":"1-40","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":22,"title":["SparseIMU: Computational Design of Sparse IMU Layouts for Sensing Fine-grained Finger Microgestures"],"prefix":"10.1145","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5676-3136","authenticated-orcid":false,"given":"Adwait","family":"Sharma","sequence":"first","affiliation":[{"name":"Saarland University, Saarland Informatics Campus, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5527-9895","authenticated-orcid":false,"given":"Christina","family":"Salchow-H\u00f6mmen","sequence":"additional","affiliation":[{"name":"Department of Neurology, Charit\u00e9-Universit\u00e4tsmedizin Berlin and Control Systems Group, Technische Universit\u00e4t Berlin, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9085-8830","authenticated-orcid":false,"given":"Vimal Suresh","family":"Mollyn","sequence":"additional","affiliation":[{"name":"Saarland University, Saarland Informatics Campus, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3698-9733","authenticated-orcid":false,"given":"Aditya Shekhar","family":"Nittala","sequence":"additional","affiliation":[{"name":"Saarland University, Saarland Informatics Campus, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6858-0791","authenticated-orcid":false,"given":"Michael A.","family":"Hedderich","sequence":"additional","affiliation":[{"name":"Saarland University, Saarland Informatics Campus, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5931-3218","authenticated-orcid":false,"given":"Marion","family":"Koelle","sequence":"additional","affiliation":[{"name":"Saarland University, Saarland Informatics Campus, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6920-1690","authenticated-orcid":false,"given":"Thomas","family":"Seel","sequence":"additional","affiliation":[{"name":"Control Systems Group, Technische Universit\u00e4t Berlin and Department of AI in Biomedical Engineering, FAU Erlangen-N\u00fcrnberg, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3493-8745","authenticated-orcid":false,"given":"J\u00fcrgen","family":"Steimle","sequence":"additional","affiliation":[{"name":"Saarland University, Saarland Informatics Campus, Germany"}]}],"member":"320","published-online":{"date-parts":[[2023,6,10]]},"reference":[{"key":"e_1_3_1_2_2","first-page":"10","volume-title":"Proceedings of the 13th European Conference on Visual Media Production","author":"Andrews Sheldon","year":"2016","unstructured":"Sheldon Andrews, Ivan Huerta, Taku Komura, Leonid Sigal, and Kenny Mitchell. 2016. 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