{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T09:51:00Z","timestamp":1766137860923,"version":"3.37.3"},"reference-count":24,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,11,1]],"date-time":"2021-11-01T00:00:00Z","timestamp":1635724800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,11,1]],"date-time":"2021-11-01T00:00:00Z","timestamp":1635724800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,11,1]],"date-time":"2021-11-01T00:00:00Z","timestamp":1635724800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100003693","name":"Korea Institute of Science and Technology","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003693","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,11,1]]},"DOI":"10.1109\/embc46164.2021.9630431","type":"proceedings-article","created":{"date-parts":[[2021,12,9]],"date-time":"2021-12-09T21:24:16Z","timestamp":1639085056000},"page":"1936-1941","source":"Crossref","is-referenced-by-count":3,"title":["Vision-Based Gait Events Detection Using Deep Convolutional Neural Networks"],"prefix":"10.1109","author":[{"given":"Ankhzaya","family":"Jamsrandorj","sequence":"first","affiliation":[]},{"given":"Mau Dung","family":"Nguyen","sequence":"additional","affiliation":[]},{"given":"Mina","family":"Park","sequence":"additional","affiliation":[]},{"given":"Konki Sravan","family":"Kumar","sequence":"additional","affiliation":[]},{"given":"Kyung-Ryoul","family":"Mun","sequence":"additional","affiliation":[]},{"given":"Jinwook","family":"Kim","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1080\/01691864.2020.1803126"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2016.08.003"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1049\/iet-bmt.2016.0118"},{"journal-title":"Pose-Based Temporal-Spatial Network (PTSN) for Gait Recognition with Carrying and Clothing Variations","year":"2017","author":"liao","key":"ref13"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33018126"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2879896"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICB.2016.7550060"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.3390\/e21040329"},{"journal-title":"Vision Based Extraction of Dynamic Gait Features Focused on Feet Movement Using RGB Camera","year":"2015","author":"nieto-hidalgo","key":"ref18"},{"journal-title":"Vision Based Gait Analysis for Frontal View Gait Sequences Using RGB Camera","year":"2016","author":"nieto-hidalgo","key":"ref19"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.3390\/s20030656"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2015.2472560"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2020.3011627"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.3390\/s20185272"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2020.2980863"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbiomech.2019.109490"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC.2019.8857872"},{"key":"ref1","doi-asserted-by":"crossref","first-page":"9879","DOI":"10.1038\/s41598-018-28222-2","article-title":"Gait Estimation from Anatomical Foot Parameters Measured by a Foot Feature Measurement System using a Deep Neural Network Model","volume":"8","author":"mun","year":"2018","journal-title":"Scientific Reports"},{"key":"ref9","doi-asserted-by":"crossref","DOI":"10.3390\/s19071483","article-title":"Automated Accelerometer-Based Gait Event Detection During Multiple Running Conditions","author":"benson","year":"2019"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1155\/2016\/5036857"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0201728"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2019.04.002"},{"key":"ref24","article-title":"Accuracy of the Microsoft KinectTM for measuring gait parameters during treadmill walking","volume":"34","author":"xu","year":"2015","journal-title":"Gait & Posture"},{"journal-title":"TTNet Real-time temporal and spatial video analysis of table tennis","year":"2020","author":"voeikov","key":"ref23"}],"event":{"name":"2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","start":{"date-parts":[[2021,11,1]]},"location":"Mexico","end":{"date-parts":[[2021,11,5]]}},"container-title":["2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9629355\/9629471\/09630431.pdf?arnumber=9630431","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T16:54:22Z","timestamp":1652201662000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9630431\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,1]]},"references-count":24,"URL":"https:\/\/doi.org\/10.1109\/embc46164.2021.9630431","relation":{},"subject":[],"published":{"date-parts":[[2021,11,1]]}}}