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On curating multimodal sensory data for health and wellness platforms


Amin, MB and Banos, O and Khan, WA and Bilal, HSM and Gong, J and Bui, D-M and Cho, SH and Hussain, S and Ali, T and Akhtar, U and Chung, TC and Lee, S, On curating multimodal sensory data for health and wellness platforms, Sensors, 16, (7) Article 980. ISSN 1424-8220 (2016) [Refereed Article]

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c 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (

DOI: doi:10.3390/s16070980


In recent years, the focus of healthcare and wellness technologies has shown a significant shift towards personal vital signs devices. The technology has evolved from smartphone-based wellness applications to fitness bands and smartwatches. The novelty of these devices is the accumulation of activity data as their users go about their daily life routine. However, these implementations are device specific and lack the ability to incorporate multimodal data sources. Data accumulated in their usage does not offer rich contextual information that is adequate for providing a holistic view of a userís lifelog. As a result, making decisions and generating recommendations based on this data are single dimensional. In this paper, we present our Data Curation Framework (DCF) which is device independent and accumulates a userís sensory data from multimodal data sources in real time. DCF curates the context of this accumulated data over the userís lifelog. DCF provides rule-based anomaly detection over this context-rich lifelog in real time. To provide computation and persistence over the large volume of sensory data, DCF utilizes the distributed and ubiquitous environment of the cloud platform. DCF has been evaluated for its performance, correctness, ability to detect complex anomalies, and management support for a large volume of sensory data.

Item Details

Item Type:Refereed Article
Keywords:data curation, multimodal sensory data, data acquisition, lifelog, healthcare and wellness platforms
Research Division:Information and Computing Sciences
Research Group:Distributed computing and systems software
Research Field:Cyberphysical systems and internet of things
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Application software packages
UTAS Author:Amin, MB (Dr Muhammad Bilal Amin)
ID Code:143570
Year Published:2016
Web of Science® Times Cited:26
Deposited By:Information and Communication Technology
Deposited On:2021-03-24
Last Modified:2021-05-26
Downloads:9 View Download Statistics

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