Clinical

Towards Guideline Compliant Clinical Decision Support System Integration in Smart and Mobile Environments: Formalizing and Using Clinical Guidelines For Diagnosing Sleep Apnea

Abstract

Assistive technologies in smart environments were developed in order to maintain and improve the quality of life of people with dementia or other health problems. In order to provide adequate support at the opportune moment, it is necessary to deploy ambient services, such as activity recognition and assistance planning. Clinical Decision Support Systems (CDSS) that implement clinical guidelines, allow for the right clinical decisions, such as diagnoses and treatment choices, to be made automatically based on patient data and other health information. While data derived from smart home services can be used in these CDSS, smart homes can be used to provide services related to clinical decisions. Mobile devices can be used in conjunction with the smart home services and a remote CDSS for sending notifications or retrieve data from wearable or built-in sensors. However, in a context where smart homes interacts with a remote CDSS, we must take into account mobility (e.g. outdoors, work), failure tolerance (e.g. connection issues with remote CDSS) and privacy concerns in order to provide minimum quality of service. Thus, CDSS must be locally deployed as a smart home service and on a mobile device. In this paper we investigate a scenario where due to the above mentioned reasons a clinical guideline compliant CDSS needs to be deployed on a mobile device and as a smart home service, where clinical data can come from either the patient (manual input) or the smart home and mobile sensors. In particular we focus on implementing and evaluating a guideline for the diagnosis of sleep apnea. Sleep apnea diagnosis is a well-suited task for this purpose as attributes for the execution of the guideline could be collected both from the patient and sensor data inside or outside the smart home environment. In order to illustrate the feasibility of CDSS as smart home service and on mobile device, the Sleep Apnea CDSS is validated on an Android smartphone and show promising results.

Publication
In The Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI-14), Qu├ębec City, Canada
Date