A new approach for the recognition of human activities
by Salima Sabri; Abdelouhab Aloui
International Journal of Ad Hoc and Ubiquitous Computing (IJAHUC), Vol. 32, No. 4, 2019

Abstract: The evaluation of a patient's functional ability to perform daily living activities is an essential part of nursing and a powerful predictor of a patient's morbidity, especially for the elderly. In this article, we describe the use of a machine learning approach to address the task of recognising activity in a smart home. We evaluate our approach by comparing it to a Markov statistical approach and using several performance measures over three datasets. We show how our model achieves significantly better recognition performance on certain data sets and with different representations and discretisation methods with an accuracy measurement that exceeds 92% and accuracy of 68%. The experiments also show a significant improvement in the learning time which does not exceed one second in the totality of the experiments reducing the complexity of the approach.

Online publication date: Mon, 21-Oct-2019

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Ad Hoc and Ubiquitous Computing (IJAHUC):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com