Ambient and Wearable Sensor Fusion for Abnormal Behaviour Detection in Activities of Daily Living

Matias Garcia-Constantino, Alexandros Konios, Mustafa Mustafa, Chris Nugent, Gareth Morrison

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

Abstract

Abnormal behaviour in the performance of Activities of Daily Living (ADLs) can be an indicator of a progressive health problem or the occurrence of a hazardous incident. This paper presents an initial fusion approach of data collected from ambient (contact and thermal) and wearable (accelerometer) sensors in a smart environment to improve the recognition of the main steps of ADLs. An accurate recognition of these steps can support detecting abnormal behaviour in the form of deviations from the expected steps. The smart environment used is a smart kitchen and the ADLs considered are (i) prepare and drink tea, and (ii) prepare and drink coffee. These ADLs are deemed to have many occurrences during a typical day of a (elderly) person. The fusion approach presented considers the extraction of the most relevant features of the data collected from the two types of sensors (ambient and wearable) and the subsequent data analysis to recognise the main steps involved in the ADLs. Results show that this initial approach slightly improves the recognition of the main steps involved in the ADLs compared to the results obtained with just using data from the wearable sensors.
Original languageEnglish
Title of host publication2020 IEEE International Conference on Pervasive Computing and Communications
PublisherIEEE
Pages(In-Press)
Publication statusAccepted/In press - 6 Jan 2020
EventIEEE International Conference on Pervasive Computing and Communications 2020 - Austin, United States
Duration: 23 Mar 202027 Mar 2020

Conference

ConferenceIEEE International Conference on Pervasive Computing and Communications 2020
Abbreviated titlePerCom
CountryUnited States
CityAustin
Period23/03/2027/03/20

Fingerprint

Fusion reactions
Coffee
Kitchens
Sensors
Medical problems
Accelerometers
Wearable sensors
Hot Temperature
Tea

Cite this

Garcia-Constantino, M., Konios, A., Mustafa, M., Nugent, C., & Morrison, G. (Accepted/In press). Ambient and Wearable Sensor Fusion for Abnormal Behaviour Detection in Activities of Daily Living. In 2020 IEEE International Conference on Pervasive Computing and Communications (pp. (In-Press)). IEEE.

Ambient and Wearable Sensor Fusion for Abnormal Behaviour Detection in Activities of Daily Living. / Garcia-Constantino, Matias; Konios, Alexandros; Mustafa, Mustafa; Nugent, Chris; Morrison, Gareth.

2020 IEEE International Conference on Pervasive Computing and Communications. IEEE, 2020. p. (In-Press).

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

Garcia-Constantino, M, Konios, A, Mustafa, M, Nugent, C & Morrison, G 2020, Ambient and Wearable Sensor Fusion for Abnormal Behaviour Detection in Activities of Daily Living. in 2020 IEEE International Conference on Pervasive Computing and Communications. IEEE, pp. (In-Press), IEEE International Conference on Pervasive Computing and Communications 2020, Austin, United States, 23/03/20.
Garcia-Constantino M, Konios A, Mustafa M, Nugent C, Morrison G. Ambient and Wearable Sensor Fusion for Abnormal Behaviour Detection in Activities of Daily Living. In 2020 IEEE International Conference on Pervasive Computing and Communications. IEEE. 2020. p. (In-Press)
Garcia-Constantino, Matias ; Konios, Alexandros ; Mustafa, Mustafa ; Nugent, Chris ; Morrison, Gareth. / Ambient and Wearable Sensor Fusion for Abnormal Behaviour Detection in Activities of Daily Living. 2020 IEEE International Conference on Pervasive Computing and Communications. IEEE, 2020. pp. (In-Press)
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