A Baseline Patient Model to Support Testing of Medical Cyber-Physical Systems.
Medical Cyber-Physical Systems (MCPS) are currently a trending topic of research. The main challenges are related to the integration and interoperability of connected medical devices, patient safety, physiologic closed-loop control, and the verification and validation of these systems. In this paper, we focus on patient safety and MCPS validation. We present a formal patient model to be used in health care systems validation without jeopardizing the patient's health. To determine the basic patient conditions, our model considers the four main vital signs: heart rate, respiratory rate, blood pressure and body temperature. To generate the vital signs we used regression models based on statistical analysis of a clinical database. Our solution should be used as a starting point for a behavioral patient model and adapted to specific clinical scenarios. We present the modeling process of the baseline patient model and show its evaluation. The conception process may be used to build different patient models. The results show the feasibility of the proposed model as an alternative to the immediate need for clinical trials to test these medical systems.
Embedded Systems and Pervasive Comp. Lab, Federal University of Campina Grande, Campina Grande, Brazil.
Lenardo C
LC
Silva
Federal Institute of Paraíba, Monteiro, Brazil.
Mirko
M
Perkusich
Embedded Systems and Pervasive Comp. Lab, Federal University of Campina Grande, Campina Grande, Brazil.
Hyggo O
HO
Almeida
Electrical Engineering Department, Federal University of Campina Grande, Campina Grande, Brazil.
Angelo
A
Perkusich
Electrical Engineering Department, Federal University of Campina Grande, Campina Grande, Brazil.
Mateus A M
MA
Lima
Embedded Systems and Pervasive Comp. Lab, Federal University of Campina Grande, Campina Grande, Brazil.
Kyller C
KC
Gorgônio
D003198:Computer Simulation; D057225:Data Mining / Q000379:methods*; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D006801:Humans; D008954:Models, Biological; D009323:Natural Language Processing; D066230:Patient-Specific Modeling / Q000706:statistics & numerical data*; D055986:Vital Signs