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For wearable devices to be practical, they must be responsive, deformable to fit the wearer, and robust to the user's range of motion. Signals produced by the wearable must also be informative enough to infer the precise physical state or activity of the user. Herein, a fully soft, wearable glove is developed, which is capable of real\u2010time hand pose reconstruction, environment sensing, and task classification. The design is easy to fabricate using low cost, commercial off\u2010the\u2010shelf items in a manner that is amenable to automated manufacturing. To realize such capabilities, resisitive and fluidic sensing technologies with machine learning neural architectures are merged. The glove is formed from a conductive knit which is strain sensitive, providing information through a network of resistance measurements. Fluidic sensing captured via pressure changes in fibrous sewn\u2010in flexible tubes, measuring interactions with the environment. The system can reconstruct user hand pose and identify sensory inputs such as holding force, object temperature, conductability, material stiffness, and user heart rate, all with high accuracy. The ability to identify complex environmentally dependent tasks, including held object identification and handwriting recognition is demonstrated.<\/jats:p><\/jats:sec>","DOI":"10.1002\/aisy.202000002","type":"journal-article","created":{"date-parts":[[2020,6,3]],"date-time":"2020-06-03T08:47:37Z","timestamp":1591174057000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":57,"title":["A Simple, Inexpensive, Wearable Glove with Hybrid Resistive\u2010Pressure Sensors for Computational Sensing, Proprioception, and Task Identification"],"prefix":"10.1002","volume":"2","author":[{"given":"Josie","family":"Hughes","sequence":"first","affiliation":[{"name":"Computer Science and Artificial Intelligence Laboratory (CSAIL) Massachusetts Institute of Technology  Cambridge MA 02139 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andrew","family":"Spielberg","sequence":"additional","affiliation":[{"name":"Computer Science and Artificial Intelligence Laboratory (CSAIL) Massachusetts Institute of Technology  Cambridge MA 02139 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mark","family":"Chounlakone","sequence":"additional","affiliation":[{"name":"Computer Science and Artificial Intelligence Laboratory (CSAIL) Massachusetts Institute of Technology  Cambridge MA 02139 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gloria","family":"Chang","sequence":"additional","affiliation":[{"name":"Computer Science and Artificial Intelligence Laboratory (CSAIL) Massachusetts Institute of Technology  Cambridge MA 02139 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wojciech","family":"Matusik","sequence":"additional","affiliation":[{"name":"Computer Science and Artificial Intelligence Laboratory (CSAIL) Massachusetts Institute of Technology  Cambridge MA 02139 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5473-3566","authenticated-orcid":false,"given":"Daniela","family":"Rus","sequence":"additional","affiliation":[{"name":"Computer Science and Artificial Intelligence Laboratory (CSAIL) Massachusetts Institute of Technology  Cambridge MA 02139 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2020,6,3]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/TRO.2009.2033627"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1038\/nature14543"},{"key":"e_1_2_11_4_1","first-page":"05","volume":"29","author":"Schiavullo R.","year":"2019","journal-title":"Virtual Reality"},{"key":"e_1_2_11_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCC.2009.2021255"},{"key":"e_1_2_11_6_1","first-page":"2271","volume-title":"Proc. of the 2005 IEEE Int. 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