1.Application of empowerment theory-based health education for the major caregivers of patient with leukemia
Mandi LI ; Min NI ; Lili HU ; Minjie LIU
Modern Clinical Nursing 2015;14(9):72-77
Objective To evaluate the effect of the empowerment theory-based health education on anxiety, depression and self-efficacy in the major caregivers for patient with leukemia. Methods Eighty patients with leukemia and their caregivers were enrolled during November 2013 to November 2014 and were divided into the intervention group (n=40) and the control group (n=40). The caregivers of the intervention group received empowerment theory-based education , while those of the control group received general health education. The two groups were compared in terms of anxiety, depression and self-efficacy. Results Before intervention, there were no significant differences in the three items between the groups (P>0.05). After intervention, the level of self efficacy in the intervention group was better than that in the control group (P<0.05) and the scores in the intervention group were significantly lower than those of the control group. Conclusion The empowerment theory-based education can relieve anxiety and depression and improve the self efficacy of the caregivers of patients with leukemia.
2.Single trial classification of motor imagery electroencephalogram based on Fisher criterion.
Rongrong FU ; Peiguo HOU ; Mandi LI
Journal of Biomedical Engineering 2018;35(5):774-778
In order to realize brain-computer interface (BCI), optimal features of single trail motor imagery electroencephalogram (EEG) were extracted and classified. Mu rhythm of EEG was obtained by preprocessing, and the features were optimized by spatial filtering, which are estimated from a set of data by method of common spatial pattern. Classification decision can be made by Fisher criterion, and classification performance can be evaluated by cross validation and receiver operating characteristic (ROC) curve. Optimal feature dimension determination projected by spatial filter was discussed deeply in cross-validation way. The experimental results show that the high discriminate accuracy can be guaranteed, meanwhile the program running speed is improved. Motor imagery intention classification based on optimized EEG feature provides difference of states and simplifies the recognition processing, which offers a new method for the research of intention recognition.