Analysis of Accelerometer Data for Personalised Mood Detection in Activities of Daily Living

Yulith V. Altamirano-Flores, Alexandros Konios, Irvin Hussein Lopez-Nava, Matias Garcia-Constantino, Idongesit Ekerete, Mustafa Mustafa

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Abstract

This paper proposes a novel approach to identify moods in Activities of Daily Living (ADLs) using accelerometer sensor data from 15 participants over 7 sessions each. Monitoring ADLs and detecting moods are of particular importance due to the potential life-changing consequences. The ADLs considered relate to preparing and drinking a hot beverage, and they were segmented into four sub-activities: (i) entering kitchen, (ii) preparing beverage, (iii) drinking beverage, and (iv) exiting kitchen. The accelerometer was attached to the participants' wrists, and prior to collecting the data, they were asked about their current mood. Two approaches were considered in the analysis according to the moods reported by the participants (happy, calm, tired, stressed, excited, sad, and bored), firstly using all trials, and secondly using a balanced sample of data. A set of statistical, temporal, and spectral features were extracted from acceleration data, and personalised classification models were built and evaluated using the Random Forest algorithm. The experimental results showed that the average F -measure for all personalized classifiers was 0.75 (\sigma\ 0.20) considering all data, and 0.76 (\sigma\ 0.22) using balanced data. The best classification results were obtained with the 'preparing' and 'drinking' activities, and with the 'happy','calm', and 'stressed' moods. This suggests that the use of accelerometers, such as those incorporated into smartwatches or activity trackers, may be useful in detecting moods in ADLs.

Original languageEnglish
Title of host publication2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2023
Subtitle of host publication2023 IEEE International Conference on Pervasive Computing and Communications (PerCom2023)
PublisherIEEE Xplore
Pages200-205
Number of pages6
ISBN (Electronic)978-1-6654-5381-3
ISBN (Print)978-1-6654-5382-0
DOIs
Publication statusPublished online - 21 Jun 2023
Event7th Workshop on Emotion Awareness for Pervasive Computing Beyond Traditional Approaches (EmotionAware): 21st IEEE International Conference on Pervasive Computing and Communications (PerCom2023) - Atlanta, USA, Atlanta, United States
Duration: 13 Mar 202317 Mar 2023
Conference number: 21
https://www.percom.org/

Publication series

Name2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)
PublisherIEEE Xplore
ISSN (Print)2836-5348
ISSN (Electronic)2766-8576

Workshop

Workshop7th Workshop on Emotion Awareness for Pervasive Computing Beyond Traditional Approaches (EmotionAware)
Abbreviated titlePerCom2023
Country/TerritoryUnited States
CityAtlanta
Period13/03/2317/03/23
Internet address

Bibliographical note

Funding Information:
Invest Northern Ireland is acknowledged for partially supporting this project under the Competence Centre Programs Grant RD0513853 – Connected Health Innovation Centre.

Publisher Copyright:
© 2023 IEEE.

Keywords

  • Activities of Daily Living
  • ADLs
  • Activity Recognition
  • Accelerometer
  • Mood
  • Sensors

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