TY - JOUR
T1 - Do-Care
T2 - A dynamic ontology reasoning based healthcare monitoring system
AU - Elhadj, Hadda Ben
AU - Sallabi, Farag
AU - Henaien, Amira
AU - Chaari, Lamia
AU - Shuaib, Khaled
AU - Al Thawadi, Maryam
N1 - Funding Information:
This research is funded by the United Arab Emirates University research grant number 31T078 .
Publisher Copyright:
© 2021
PY - 2021/5
Y1 - 2021/5
N2 - Healthcare remote monitoring applications dominate the market of new technologies due to their valuable aid to patients, families, and medical staff. They provide ubiquitous remote health services for patients with chronic diseases or specific conditions and can provide ubiquitous communication between patients and caregiver(s). This paper presents an ontology reasoning-based healthcare monitoring system called Do-Care. The proposed system supports the supervision and follow-up of outdoor and indoor patients suffering from chronic diseases. Collected data, from wearable1, nearable2 or usable3 devices forms the instances for entities from the proposed Do-Care ontology used by the reasoner when applying a set of SWRL4 rules to determinate the health situation of a patient as Normal, Abnormal or Wrong. The main contribution in this paper is a modular and dynamic ontology composed of FOAF5, SSN6/SOSA7 and ICNP8 ontologies with a scalable set of inference rules. The proposed rule based methodology is dynamic and adjustable to meet possible changes in the medication market, medical discoveries, and personal users’ profiles. The presented experimental results show the efficiency of the proposed DO-Care system.
AB - Healthcare remote monitoring applications dominate the market of new technologies due to their valuable aid to patients, families, and medical staff. They provide ubiquitous remote health services for patients with chronic diseases or specific conditions and can provide ubiquitous communication between patients and caregiver(s). This paper presents an ontology reasoning-based healthcare monitoring system called Do-Care. The proposed system supports the supervision and follow-up of outdoor and indoor patients suffering from chronic diseases. Collected data, from wearable1, nearable2 or usable3 devices forms the instances for entities from the proposed Do-Care ontology used by the reasoner when applying a set of SWRL4 rules to determinate the health situation of a patient as Normal, Abnormal or Wrong. The main contribution in this paper is a modular and dynamic ontology composed of FOAF5, SSN6/SOSA7 and ICNP8 ontologies with a scalable set of inference rules. The proposed rule based methodology is dynamic and adjustable to meet possible changes in the medication market, medical discoveries, and personal users’ profiles. The presented experimental results show the efficiency of the proposed DO-Care system.
KW - Decision support system
KW - Dynamic ontology
KW - Healthcare
KW - IoT
KW - Reasoning
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U2 - 10.1016/j.future.2021.01.001
DO - 10.1016/j.future.2021.01.001
M3 - Article
AN - SCOPUS:85100098197
SN - 0167-739X
VL - 118
SP - 417
EP - 431
JO - Future Generation Computer Systems
JF - Future Generation Computer Systems
ER -