ABSTRACT
Designing effective engineering solutions or algorithms to solve biomedical problems in the healthcare monitoring context is a challenging task, to say the least. The initial objectives and specifications are typically vague. In addition to this lack of clarity, the designer has to take into account many factors, including the algorithmic complexity that can be tolerated by the target platform as well as the type and amount of data that are available to calibrate and properly evaluate the algorithm. For example, the physiological condition of a subject might adversely affect the signals, which might have unpredictable consequences on the algorithm used to process them. Therefore, limitations and issues with the algorithm might not be adequately exposed at design time, which could lead to substantial costs and loss of credibility when they are discovered by the client during or after field deployment.
