{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T17:46:22Z","timestamp":1771955182877,"version":"3.50.1"},"reference-count":38,"publisher":"IEEE","license":[{"start":{"date-parts":[[2019,9,1]],"date-time":"2019-09-01T00:00:00Z","timestamp":1567296000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,9,1]],"date-time":"2019-09-01T00:00:00Z","timestamp":1567296000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,9,1]],"date-time":"2019-09-01T00:00:00Z","timestamp":1567296000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,9]]},"DOI":"10.1109\/acii.2019.8925520","type":"proceedings-article","created":{"date-parts":[[2019,12,27]],"date-time":"2019-12-27T13:44:34Z","timestamp":1577454274000},"page":"1-7","source":"Crossref","is-referenced-by-count":13,"title":["End-To-End Prediction of Emotion from Heartbeat Data Collected by a Consumer Fitness Tracker"],"prefix":"10.1109","author":[{"given":"Ross","family":"Harper","sequence":"first","affiliation":[]},{"given":"Joshua","family":"Southern","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref38","first-page":"2825","article-title":"Scikit-learn: Machine learning in python","volume":"12","author":"pedregosa","year":"2011","journal-title":"J Mach Learn Res"},{"key":"ref33","first-page":"1050","article-title":"Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning","author":"gal","year":"0","journal-title":"Proceedings of the 33rd International Conference on Machine Learning (ICML-16)"},{"key":"ref32","doi-asserted-by":"crossref","first-page":"452","DOI":"10.1038\/nature14541","article-title":"Probabilistic machine learning and artificial intelligence","volume":"521","author":"ghahramani","year":"2015","journal-title":"Nature"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/BF01745040"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1111\/j.1469-8986.1992.tb02011.x"},{"key":"ref37","article-title":"TensorFlow: Large-scale machine learning on heterogeneous systems","year":"2015","journal-title":"Google research"},{"key":"ref36","article-title":"Adam: A Method for Stochastic Optimization","author":"kingma","year":"0","journal-title":"International Conference on Learning Representations"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.123"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1186\/1475-925X-3-28"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/T-AFFC.2012.4"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.bj.2017.11.001"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1037\/0022-3514.53.4.712"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1177\/0022022101032001009"},{"key":"ref14","author":"harper","year":"2019","journal-title":"A bayesian deep learning framework for end-to-end prediction of emotion from heartbeat"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2017.2688239"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2016.2625250"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICME.2017.8019533"},{"key":"ref18","article-title":"AMIGOS: A Dataset for Affect, Personality and Mood Research on Individuals and Groups","volume":"pp","author":"miranda-correa","year":"2017","journal-title":"IEEE Transactions on Affective Computing"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/BIBE.2016.40"},{"key":"ref28","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1007\/978-3-319-60639-2_2","article-title":"Emotion recognition using physiological signals: Laboratory vs. wearable sensors","author":"ragot","year":"2018","journal-title":"Advances in Human Factors in Wearable Technologies and Game Design"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TASL.2007.911513"},{"key":"ref27","year":"0"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2004.427"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/T-AFFC.2010.8"},{"key":"ref29","first-page":"63","article-title":"SAM: The Self-Assessment Manikin - An efficient cross-cultural measurement of emotional response","volume":"35","author":"morris","year":"1995","journal-title":"Journal of Advertising Research"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2008.52"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.specom.2011.01.011"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.specom.2011.05.002"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2004.840618"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2008.26"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/34.895976"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CIBCB.2016.7758108"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/T-AFFC.2011.28"},{"key":"ref21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/srep04998","article-title":"Revealing real-time emotional responses: A personalized assessment based on heartbeat dynamics","volume":"4","author":"valenza","year":"2014","journal-title":"Scientific Reports"},{"key":"ref24","year":"0","journal-title":"Shimmer discovery in motion All products"},{"key":"ref23","author":"corporation","year":"2018","journal-title":"Idc forecasts sustained double-digit growth for wearable devices led by steady adoption of smartwatches"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/MOBIHEALTH.2014.7015904"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/3132635.3132641"}],"event":{"name":"2019 8th International Conference on Affective Computing and Intelligent Interaction (ACII)","location":"Cambridge, United Kingdom","start":{"date-parts":[[2019,9,3]]},"end":{"date-parts":[[2019,9,6]]}},"container-title":["2019 8th International Conference on Affective Computing and Intelligent Interaction (ACII)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8911251\/8925431\/08925520.pdf?arnumber=8925520","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,24]],"date-time":"2023-09-24T11:54:58Z","timestamp":1695556498000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8925520\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,9]]},"references-count":38,"URL":"https:\/\/doi.org\/10.1109\/acii.2019.8925520","relation":{},"subject":[],"published":{"date-parts":[[2019,9]]}}}