tailieunhanh - Biomedical Engineering Trends in Electronics Communications and Software Part 15

Tham khảo tài liệu 'biomedical engineering trends in electronics communications and software part 15', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 550 Biomedical Engineering Trends in Electronics Communications and Software 2. Problem definition and related works In this section the importance of human-machine collaboration in causal analysis is discussed from a viewpoint of requirements for practical biomedical sensing. And problem definitions are discussed. Requirements for biomedical sensing from a viewpoint of practical use Considering practical usage biomedical sensing has to be easy to use. In addition it should be non-invasive low-intrusive and unconscious regarding consumers home usage. For instance X-ray CT is not available at home because of its X-ray exposure. In addition biomedical sensing is required to have not only measurement accuracy but also transparent measurement theory because it provides users with feeling of security besides informed consent Marutschke et al. 2010 . However measurement accuracy becomes worse while measurement theory becomes too simplified. Thus the satisfaction of accuracy and transparency should be considered while experts design certain biomedical sensing equipments. Regarding the above-mentioned problem a new designing process of biomedical sensing is proposed which employs causal analysis based on human-machine collaboration. In the next section the human-machine collaboration is discussed and its importance described. Human-machine collaboration As means for representing causality many theories have been proposed that is Bayesian networks graphical modeling neural networks fuzzy logic and so forth. Additionally as means for modeling cause-effect structure lots of learning theories have been studied considering the characteristics of each theory Bishop 2006 Zadeh 1996 . Particularly Bayesian network and graphical modeling are utilized for a variety of applications in the broad domain due to transparency of the causality Pearl 2001 . These previous works show two primary approaches to causality analysis one for generating causality based on experts knowledge