Intelligent Healthcare Service Provisioning Using Ontology with Low-Level Sensory Data

Abstract

Ubiquitous Healthcare (u-Healthcare) is the intelligent delivery of healthcare services to users anytime and anywhere. To provide robust healthcare services, recognition of patient daily life activities is required. Context information in combination with user real-time daily life activities can help in the provision of more personalized services, service suggestions, and changes in system behavior based on user profile for better healthcare services. In this paper, we focus on the intelligent manipulation of activities using the Context-aware Activity Manipulation Engine (CAME) core of the Human Activity Recognition Engine (HARE). The activities are recognized using video-based, wearable sensor-based, and location-based activity recognition engines. An ontology-based activity fusion with subject profile information for personalized system response is achieved. CAME receives real-time low level activities and infers higher level activities, situation analysis, personalized service suggestions, and makes appropriate decisions. A two-phase filtering technique is applied for intelligent processing of information (represented in ontology) and making appropriate decisions based on rules (incorporating expert knowledge). The experimental results for intelligent processing of activity information showed relatively better accuracy. Moreover, CAME is extended with activity filters and T-Box inference that resulted in better accuracy and response time in comparison to initial results of CAME.

DDSS: Dynamic decision support system for elderly

“…DDSS is tested on the data set of [10] with an increasing set of activities. The results found are encouraging.…”

“…Work presented in [1] details an ontology based reminder system; incorporates rules for manipulating the recognized activities of the elderly. In [10], realtime activities are recognized using diverse sensors are used for situation analysis. Research in [5] focused on the social interaction of patients.…”

Context Representation and Fusion: Advancements and Opportunities

“…The research and development efforts for context-aware systems involve the process of context sensing, acquisition, representation, distribution, manipulation, development support and its implications on human user [2,3,5]. The use of context-aware systems is increasing in variety of different domains, such as location based system [9], context-aware file system [10], context-aware security [11], context-aware activity recognition [6], context based searching [12,13], and intelligent healthcare systems [7,14–16]. Due to their acceptability, the context-aware systems are currently used in many aspects of our everyday life.…”

“…Due to their acceptability, the context-aware systems are currently used in many aspects of our everyday life. Various transparent sensing and computing devices are integrated into the user’s environment that acquire user context and process it to provide services to the users based on their context [7,14,17]. Regardless of the context dimensions, i.e.…”

“…, internal or external [18], the general working of such systems is to sense context, acquire it and then make reasoning based on the acquired context [2,17]. This process has pragmatic advantages due to the mature nature of sensing technology used for capturing the environmental context the user is involved in [2,7,14,17]. …”