AI Article Synopsis
- Ubiquitous eHealth systems leveraging sensor technologies are essential for addressing the financial challenges of an ageing population.
- Activity recognition algorithms are central to these systems, relying on both high-quality sensor data and a reliable ground truth for effective training and validation.
- The development of a hierarchical ontology for activities of daily living (ADL) is proposed to facilitate data sharing and reuse, along with two practical applications demonstrating its effectiveness, while also discussing requirements for future improvements.
Article Abstract
Ubiquitous eHealth systems based on sensor technologies are seen as key enablers in the effort to reduce the financial impact of an ageing society. At the heart of such systems sit activity recognition algorithms, which need sensor data to reason over, and a ground truth of adequate quality used for training and validation purposes. The large set up costs of such research projects and their complexity limit rapid developments in this area. Therefore, information sharing and reuse, especially in the context of collected datasets, is key in overcoming these barriers. One approach which facilitates this process by reducing ambiguity is the use of ontologies. This article presents a hierarchical ontology for activities of daily living (ADL), together with two use cases of ground truth acquisition in which this ontology has been successfully utilised. Requirements placed on the ontology by ongoing work are discussed.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6068475 | PMC |
| http://dx.doi.org/10.3390/s18072361 | DOI Listing |
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