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Novel Ensemble Algorithm for Multiple Activity Recognition in Elderly People Exploiting Ubiquitous Sensing Devices

Liaqat, Sidrah; Dashtipour, Kia; Shah, Syed Aziz; Rizwan, Ali; Alotaibi, Abdullah Alhumaidi; Althobaiti, Turke; Arshad, Kamran; Assaleh, Khaled; Ramzan, Naeem

Authors

Sidrah Liaqat

Syed Aziz Shah

Ali Rizwan

Abdullah Alhumaidi Alotaibi

Turke Althobaiti

Kamran Arshad

Khaled Assaleh

Naeem Ramzan



Abstract

Ambient assisted living is good way to look after ageing population that enables us to detect human’s activities of daily living (ADLs) and postures, as number of older adults are increasing at rapid pace. Posture detection is used to provide the assessment for monitoring the activity of elderly people. Most of the existing approaches exploit dedicated sensing devices as cameras, thermal sensors, accelerometer, gyroscope, magnetometer and so on. Traditional methods such as recording data using these sensors, training and testing machine learning classifiers to identify various human postures. This paper exploits data recorded using ubiquitous devices such as smart phones we use on daily basis and classify different human activities such as standing, sitting, laying, walking, walking downstairs and walking upstairs. Moreover, we have used machine learning and deep learning classifiers including random forest, KNN, logistic regression, multilayer perceptron, decision tree, QDA and SVM, convolutional neural network and long short-term memory as ground truth and proposed a novel ensemble classification algorithm to classify each human activity. The proposed algorithm demonstrate classification accuracy of 98% that outperforms other algorithms.

Citation

Liaqat, S., Dashtipour, K., Shah, S. A., Rizwan, A., Alotaibi, A. A., Althobaiti, T., Arshad, K., Assaleh, K., & Ramzan, N. (2021). Novel Ensemble Algorithm for Multiple Activity Recognition in Elderly People Exploiting Ubiquitous Sensing Devices. IEEE Sensors Journal, 21(16), 18214-18221. https://doi.org/10.1109/jsen.2021.3085362

Journal Article Type Article
Acceptance Date May 26, 2021
Online Publication Date Jun 2, 2021
Publication Date Aug 15, 2021
Deposit Date Aug 26, 2021
Journal IEEE Sensors Journal
Print ISSN 1530-437X
Electronic ISSN 1558-1748
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 21
Issue 16
Pages 18214-18221
DOI https://doi.org/10.1109/jsen.2021.3085362
Keywords Posture detection, ensemble algorithm, deep learning, machine learning, ubiquitous devices
Public URL http://researchrepository.napier.ac.uk/Output/2796737