Abstract
In this paper, the authors investigate the role that smart devices, including smartphones and smartwatches, can play in identifying activities of daily living. A feasibility study involving N = 10 participants was carried out to evaluate the devices' ability to differentiate between nine everyday activities. The activities examined include walking, running, cycling, standing, sitting, elevator ascents, elevator descents, stair ascents and stair descents. The authors also evaluated the ability of these devices to differentiate indoors from outdoors, with the aim of enhancing contextual awareness. Data from this study was used to train and test five well known machine learning algorithms: C4.5, CART, Naïve Bayes, Multi-Layer Perceptrons and finally Support Vector Machines. Both single and multi-sensor approaches were examined to better understand the role each sensor in the device can play in unobtrusive activity recognition. The authors found overall results to be promising, with some models correctly classifying up to 100% of all instances.
Highlights
Pervasive, ubiquitous computing is coming ever closer, and the implications for user driven preventative healthcare are immense
A smart device, such as a mobile phone can either act as gateway for one or more dedicated devices located in a Personal Area Network (PAN), e.g., [22], or the sensors built into the smartphone can be used, e.g., [23]
We examine the potential role smartphones and smartwatches can play in the inference of everyday human ambulation using both single and fused sensor approaches
Summary
Ubiquitous computing is coming ever closer, and the implications for user driven preventative healthcare are immense. Eradicating physical inactivity would increase life expectancy of the world’s population by an average of 0.68 years This sentiment is echoed in publications by the U.S Department of Health and Human Services, which found a strong correlation between increased physical activity and a lower risk of heart disease, stroke, high blood pressure, type II diabetes and even particular forms of cancer. The use of multiple sensors has come to the fore, e.g., [20,21] In this scenario, a smart device, such as a mobile phone can either act as gateway for one or more dedicated devices located in a Personal Area Network (PAN), e.g., [22], or the sensors built into the smartphone can be used, e.g., [23].
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