Activities of Daily Living Ontology for Ubiquitous Systems

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 paper 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. Furthermore, these studies are reflected upon from the machine learning perspective, and the use of this ontology in clinical studies is discussed.