IC-SMART: IoTCloud enabled Seamless Monitoring for Alzheimer Diagnosis and Rehabilitation SysTem

Abstract

Alzheimer disease (AD), a progressive neurodegenerative disease is related with the gradual loss of structure or disturbance of neuronal functions and deterioration in cognitive functions. Timely diagnosis of this disease countenances prompt treatment and headways to patient’s quality of life. This paper proposes IC-SMART, a novel IoTCloud based Seamless Monitoring for Alzheimer Diagnosis and Rehabilitation SysTem (SMART) that leverages semantic modeling, specifically, ontology modeling for structuring and representing pertinent knowledge explicit to AD. Patient’s data collected from the “things” such as sensory devices and the inputs provided by the general practitioners and specialists in the AD realm has been integrated in the knowledge base for construction of a Bayesian Network decision model to ascertain the possibility of patient being diagnosed with AD. Furthermore, IC-SMART offers users with the intelligent capabilities of accomplishing multiple control functions such as patient diagnosis, messaging and communication, real time and historical alarm generation, and navigation based assistance to rehabilitation centers. To verify the feasibility of the proposed IC-SMART, an android based mobile cloud software service has been designed and deployed on Amazon EC2 cloud. The classification accuracy of Alzheimer diagnosis using ontology based Bayesian network model has been validated by obtaining the classification results from well-known classifiers such as Naïve Bayes, J48 decision tree and decision stump. Further, sensitivity analysis has been carried out to verify the robustness of IC-SMART. The evaluation results attained for the prototype implementation prove to be very promising.

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Correspondence to Pankaj Deep Kaur.

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Kaur, P.D., Sharma, P. IC-SMART: IoTCloud enabled Seamless Monitoring for Alzheimer Diagnosis and Rehabilitation SysTem. J Ambient Intell Human Comput 11, 3387–3403 (2020). https://doi.org/10.1007/s12652-019-01534-5

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Keywords

  • Neurological disorder
  • Alzheimer’s disease (AD) diagnosis
  • Ontology
  • Bayesian network (BN)
  • IoTCloud based healthcare