Chaturvedi, Iti, Seow, Wei Liang, Hogarth, Amber, Adornetto, Luca, and Cambria, Erik (2025) Continuous Time Markov Chain for Smartwatch Sensors. Expert Systems, 42 (11). e70144.

Preview

PDF (Published Version) - Published Version Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (671kB) | Preview

Abstract

Time-series forecasting is essential for predicting events in the future and for tracking objects. The conventional recurrent neural network model needs to pad the target with zeros when handling long inputs, resulting in a loss in accuracy. Recently, it was proposed to divide a time series input into patches and merge the learned weights. However, such a model is difficult to interpret. In this article, we consider a mixture of continuous and discrete Markov states to model long-range time dependencies. For example, in a vehicle, each gear level can be a discrete state and the throttle input is continuously controlled to maximise the efficiency of the engine. Data collected from the sensor is prone to noise due to component faults or external disturbances. Hence, we apply a stability constraint to select samples for training. We validate our algorithm on three datasets: (1) Apple Watch, (2) Car engine and (3) Election tweets. On all datasets, we achieve an improvement in the range of 5%–20% in the F-measure. Furthermore, the features learned are easy to explain in terms of real-world scenarios.

Item ID:	88920
Item Type:	Article (Research - C1)
ISSN:	1468-0394
Copyright Information:	© 2025 The Author(s). Expert Systems published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
Date Deposited:	25 Sep 2025 03:41
FoR Codes:	46 INFORMATION AND COMPUTING SCIENCES > 4602 Artificial intelligence > 460206 Knowledge representation and reasoning @ 60% 46 INFORMATION AND COMPUTING SCIENCES > 4602 Artificial intelligence > 460208 Natural language processing @ 40%
SEO Codes:	20 HEALTH > 2004 Public health (excl. specific population health) > 200408 Injury prevention and control @ 40% 28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280121 Expanding knowledge in psychology @ 60%
Downloads:	Total: 1 Last 12 Months: 1
	More Statistics