A multi-sensor dataset with annotated activities of daily living recorded in a residential setting

Emma L. Tonkin*, Michael H Holmes, Hao Song, Niall J Twomey, Tom R Diethe, Meelis Kull, Miquel Perello Nieto, Massimo Camplani, Sion L Hannuna, Xenofon Fafoutis, Ni Zhu, Przemyslaw R Woznowski, Gregory J. L. Tourte, Raul Santos-Rodriguez, Peter A Flach, Ian J Craddock

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

1 Citation (Scopus)

Abstract

SPHERE is a large multidisciplinary project to research and develop a sensor network to facilitate home healthcare by activity monitoring, specifically towards activities of daily living. It aims to use the latest technologies in low powered sensors, internet of things, machine learning and automated decision making to provide benefits to patients and clinicians. This dataset comprises data collected from a SPHERE sensor network deployment during a set of experiments conducted in the ‘SPHERE House’ in Bristol, UK, during 2016, including video tracking, accelerometer and environmental sensor data obtained by volunteers undertaking both scripted and non-scripted activities of daily living in a domestic residence. Trained annotators provided ground-truth labels annotating posture, ambulation, activity and location. This dataset is a valuable resource both within and outside the machine learning community, particularly in developing and evaluating algorithms for identifying activities of daily living from multi-modal sensor data in real-world environments. A subset of this dataset was released as a machine learning competition in association with the European Conference on Machine Learning (ECML-PKDD 2016).
Original languageEnglish
Article number162
Pages (from-to)1-15
Number of pages15
JournalScientific Data
Volume10
Issue number1
DOIs
Publication statusPublished - 23 Mar 2023

Bibliographical note

Funding Information:
This work was performed under the SPHERE IRC funded by the UK Engineering and Physical Sciences Research Council (EPSRC), Grant EP/K031910/1. NT is currently supported by ‘Continuous Behavioural Biomarkers of Cognitive Impairment’ project funded by the UK Medical Research Council Momentum Awards under Grant MC/PC/16029.

Publisher Copyright:
© 2023, The Author(s).

Keywords

  • Electrical and electronic engineering
  • Quality of life
  • Scientific data

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