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1.
Journal of Biomedical Engineering ; (6): 451-455, 2011.
Article in Chinese | WPRIM | ID: wpr-306540

ABSTRACT

The occurrence of acute hypotensive episodes (AHE) in intensive care units (ICU) seriously endangers the lives of patients, and the treatment is mainly depended on the expert experience of doctors. In this paper, a model for predicting the occurrence of AHE in ICU has been developed using the theory of medical Informatics. We analyzed the trend and characteristics of the mean arterial blood pressure (MAP) between the patients who were suffering AHE and those who were not, and extracted the median, mean and other statistical parameters for learning and training based on support vector machine (SVM), then developed a predicting model. On this basis, we also compared different models consisted of different kernel functions. Experiments demonstrated that this approach performed well on classification and prediction, which would contribute to forecast the occurrence of AHE.


Subject(s)
Humans , Acute Disease , Diagnosis, Computer-Assisted , Methods , Forecasting , Hypotension , Diagnosis , Intensive Care Units , Models, Cardiovascular , Support Vector Machine
2.
Chinese Journal of Medical Physics ; (6): 1683-1686, 2010.
Article in Chinese | WPRIM | ID: wpr-500249

ABSTRACT

Graduation project is key link in the cultivation of innovative talents for college teaching work,which is the need of the era.Thus,this paper introduced the current development of biomedical engineering at home and abroad,and the achievement of the graduation project of our university at present.Then,the necessity of the teaching reform and innovation of graduation project are analyzed.The methods for the teaching reform and innovation of graduation project are introduced including the choice of projects,the adjustment of the project schedule,reinforcing the practice of projects and improving the ability to apply knowledge,the assessment criteria of grades for the project,etc.

3.
Journal of Biomedical Engineering ; (6): 529-543, 2010.
Article in Chinese | WPRIM | ID: wpr-230837

ABSTRACT

Motion artifact is a significant source of noise in ambulatory physiologic signals and can affect the diagnoses seriously. To cope with this problem, we adopted certain methods for removing motion artifact from ECG signals via synchronous acquisition of the elector/skin impedance as the reference signal of adaptive filter. The results demonstrated that 3rd order RLS adaptive filter can remove the baseline shift effectively with an exciting current of 120 Hz and 50 microA. Such system was implemented to investigate the utility of ambulatory heart rate monitoring, which provides convenient and reliable monitoring services for patients.


Subject(s)
Humans , Algorithms , Artifacts , Electric Impedance , Electrocardiography , Methods , Signal Processing, Computer-Assisted
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