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Conference Paper/Proceeding/Abstract 365 views 21 downloads

What's cooking and why? Behaviour recognition during unscripted cooking tasks for health monitoring / Adeline, Paiement

IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), 2017, Pages: 18 - 21

Swansea University Author: Adeline, Paiement

DOI (Published version): 10.1109/PERCOMW.2017.7917511

Abstract

Nutrition related health conditions can seriously decrease quality of life; a system able to monitor the kitchen activities and eating behaviour of patients could provide clinicians with important indicators for improving a patient’s condition. To achieve this, the system has to reason about the per...

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Published in: IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), 2017
ISBN: 978-1-5090-4338-5
Published: 2017
Online Access: http://ieeexplore.ieee.org/document/7917511/
URI: https://cronfa.swan.ac.uk/Record/cronfa31590
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first_indexed 2017-01-06T20:58:27Z
last_indexed 2018-02-09T05:18:40Z
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spelling 2017-12-06T17:41:10.3361015 v2 31590 2017-01-06 What's cooking and why? Behaviour recognition during unscripted cooking tasks for health monitoring f50adf4186d930e3a2a0f9a6d643cf53 0000-0001-5114-1514 Adeline Paiement Adeline Paiement true false 2017-01-06 SCS Nutrition related health conditions can seriously decrease quality of life; a system able to monitor the kitchen activities and eating behaviour of patients could provide clinicians with important indicators for improving a patient’s condition. To achieve this, the system has to reason about the person’s actions and goals. To address this challenge, we present a behaviour recognition approach that relies on symbolic behaviour repre- sentation and probabilistic reasoning to recognise the person’s actions, the type of meal being prepared and its potential impact on a patient’s health. We test our approach on a cooking dataset containing unscripted kitchen activities recorded with various sensors in a real kitchen. The results show that the approach is able to recognise the sequence of executed actions and the prepared meal, to determine whether it is healthy, and to reason about the possibility of depression based on the type of meal. Conference Paper/Proceeding/Abstract IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), 2017 18 21 978-1-5090-4338-5 4 5 2017 2017-05-04 10.1109/PERCOMW.2017.7917511 http://ieeexplore.ieee.org/document/7917511/ COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University 2017-12-06T17:41:10.3361015 2017-01-06T15:26:25.0630187 College of Science Computer Science Kristina Yordanova 1 Samuel Whitehouse 2 Adeline Paiement 3 Majid Mirmehdi 4 Thomas Kirste 5 Ian Craddock 6 0031590-06122017174018.pdf WhatsCooking.pdf 2017-12-06T17:40:18.1830000 Output 2328815 application/pdf Accepted Manuscript true 2017-12-06T00:00:00.0000000 true eng
title What's cooking and why? Behaviour recognition during unscripted cooking tasks for health monitoring
spellingShingle What's cooking and why? Behaviour recognition during unscripted cooking tasks for health monitoring
Adeline, Paiement
title_short What's cooking and why? Behaviour recognition during unscripted cooking tasks for health monitoring
title_full What's cooking and why? Behaviour recognition during unscripted cooking tasks for health monitoring
title_fullStr What's cooking and why? Behaviour recognition during unscripted cooking tasks for health monitoring
title_full_unstemmed What's cooking and why? Behaviour recognition during unscripted cooking tasks for health monitoring
title_sort What's cooking and why? Behaviour recognition during unscripted cooking tasks for health monitoring
author_id_str_mv f50adf4186d930e3a2a0f9a6d643cf53
author_id_fullname_str_mv f50adf4186d930e3a2a0f9a6d643cf53_***_Adeline, Paiement
author Adeline, Paiement
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url http://ieeexplore.ieee.org/document/7917511/
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description Nutrition related health conditions can seriously decrease quality of life; a system able to monitor the kitchen activities and eating behaviour of patients could provide clinicians with important indicators for improving a patient’s condition. To achieve this, the system has to reason about the person’s actions and goals. To address this challenge, we present a behaviour recognition approach that relies on symbolic behaviour repre- sentation and probabilistic reasoning to recognise the person’s actions, the type of meal being prepared and its potential impact on a patient’s health. We test our approach on a cooking dataset containing unscripted kitchen activities recorded with various sensors in a real kitchen. The results show that the approach is able to recognise the sequence of executed actions and the prepared meal, to determine whether it is healthy, and to reason about the possibility of depression based on the type of meal.
published_date 2017-05-04T03:56:12Z
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