{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T16:47:55Z","timestamp":1774630075726,"version":"3.50.1"},"reference-count":32,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2023,5,1]],"date-time":"2023-05-01T00:00:00Z","timestamp":1682899200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"NSERC Discovery","award":["RGPIN-2018-04850"],"award-info":[{"award-number":["RGPIN-2018-04850"]}]},{"name":"NSERC Discovery","award":["NFRFE2018-01698"],"award-info":[{"award-number":["NFRFE2018-01698"]}]},{"name":"John R. Evans Leaders Fund Canadian Foundation for Innovation, Ontario Research Fund (ORF)","award":["RGPIN-2018-04850"],"award-info":[{"award-number":["RGPIN-2018-04850"]}]},{"name":"John R. Evans Leaders Fund Canadian Foundation for Innovation, Ontario Research Fund (ORF)","award":["NFRFE2018-01698"],"award-info":[{"award-number":["NFRFE2018-01698"]}]},{"name":"New Frontiers in Research Fund","award":["RGPIN-2018-04850"],"award-info":[{"award-number":["RGPIN-2018-04850"]}]},{"name":"New Frontiers in Research Fund","award":["NFRFE2018-01698"],"award-info":[{"award-number":["NFRFE2018-01698"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Robotics"],"abstract":"<jats:p>Accurate interaction force estimation can play an important role in optimizing human\u2013robot interaction in an exoskeleton. In this work, we propose a novel approach for the system identification of exoskeleton dynamics in the presence of interaction forces as a whole multibody system without imposing any constraints on the exoskeleton dynamics. We hung the exoskeleton through a linear spring and excited the exoskeleton joints with chirp commands while measuring the exoskeleton\u2013environment interaction force. Several structures of neural networks were trained to model the exoskeleton passive dynamics and estimate the interaction force. Our testing results indicated that a deep neural network with 250 neurons and 10 time\u2013delays could obtain a sufficiently accurate estimation of the interaction force, resulting in an RMSE of 1.23 on Z\u2013normalized applied torques and an adjusted R2 of 0.89.<\/jats:p>","DOI":"10.3390\/robotics12030066","type":"journal-article","created":{"date-parts":[[2023,5,1]],"date-time":"2023-05-01T12:14:08Z","timestamp":1682943248000},"page":"66","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Human\u2013Exoskeleton Interaction Force Estimation in Indego Exoskeleton"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2956-2272","authenticated-orcid":false,"given":"Mohammad","family":"Shushtari","sequence":"first","affiliation":[{"name":"Department of Mechanical and Mechatronics Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7609-6553","authenticated-orcid":false,"given":"Arash","family":"Arami","sequence":"additional","affiliation":[{"name":"Department of Mechanical and Mechatronics Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada"},{"name":"Toronto Rehabilitation Institute (KITE), University Health Network, Toronto, ON M5G 2A2, Canada"}]}],"member":"1968","published-online":{"date-parts":[[2023,5,1]]},"reference":[{"key":"ref_1","first-page":"38","article-title":"Path control: A method for patient-cooperative robot-aided gait rehabilitation","volume":"18","author":"Caprez","year":"2009","journal-title":"IEEE Trans. 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