{"type":"ScholarlyArticle","title":"DeepVentilation: Learning to Predict Physical Effort from Breathing","authors":[{"name":"Sagar Sen","slug":"sagar-sen","given":"Sagar","family":"Sen","affiliation":"Simula Research Laboratory , Pb 135 , 1325 Lysaker , Norway"},{"name":"Pierre Bernabé","slug":"pierre-bernabe","given":"Pierre","family":"Bernabé","affiliation":"Simula Research Laboratory , Pb 135 , 1325 Lysaker , Norway"},{"name":"Erik Johannes B.L.G. Husom","slug":"erik-johannes-b-l-g-husom","given":"Erik  Johannes B.L.G.","family":"Husom","affiliation":"Department of Physics , University of Oslo , Norway"}],"abstract":"Tracking physical effort from physiological signals has enabled people to manage required activity levels in our increasingly sedentary and automated world.  Breathing is a physiological process that is a reactive representation of our physical effort. In this demo, we present DeepVentilation, a deep learning system to predict minute ventilation in litres of air a person moves in one minute uniquely from real-time measurement of rib-cage breathing forces. DeepVentilation has been trained on input signals of expansion and contraction of the rib-cage obtained using a non-invasive  respiratory inductance plethysmography  sensor to predict minute ventilation as observed from a face/head mounted exercise spirometer. The system is used to track physical effort closely matching our perception of actual exercise intensity.  The source code for the demo is available here: https://github.com/simula-vias/DeepVentilation","doi":"10.24963/ijcai.2020/753","url":"https://ijcai.org/proceedings/2020/753","pdf":"https://ijcai.org/proceedings/2020/0753.pdf","markdown":"https://ijcai.org/proceedings/2020/753.md","bibtex":"https://ijcai.org/proceedings/2020/bibtex/753","volume":{"slug":"2020","title":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2020","url":"https://ijcai.org/proceedings/2020/","year":2020,"location":"Yokohama","dates":"January 2021 (postponed from 11-17 July 2020)","editors":"Christian Bessiere","isbn":"978-0-9992411-6-5","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2020"},"section":"Demos","track":"Demos","number":753,"pages":{"first":5231,"last":5233},"keywords":["Machine Learning: general","Uncertainty in AI: general","Human-Computer Interactive Systems: general"],"videos":[],"references":[{"position":1,"raw":"[Adams, 2019] Mary Louise Adams. 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