EISAs (n = 20), showed a significant reduction of BPD (29.0 vs. 70.0%, p = 0.004) and PDA (29.0 vs. 65.0%, p = 0.011). In the subgroup analysis of blood gas, arterial oxygen saturation (SaO 2) value at 1 and 12 h and partial pressure of arterial oxygen (PaO 2) at 12 h were all higher in the EISA group compared to the MISA group. Conclusion : MISA had no clear benefit on the incidence of BPD, but it was related to a reduction in PDA. It is an appropriate therapy for spontaneous breathing in infants with extremely low birth weight and NRDS.

A badminton training system based on body sensor networks has been proposed. The system may recognize different badminton strokes of badminton players. A two-layer hidden Markov model (HMM) classification algorithm is proposed to recognize 14 types of badminton strokes. In the first layer, we use acceleration magnitude of the right wrist to determine a threshold to detect strokes, and then, the HMM is applied to filter out nonstroke motions. In the second layer, we adopt the HMM to classify all the strokes into 14 categories. Experimental results show that the two-layer HMM can achieve good recognition accuracy. The effectiveness and feasibility of the two-layer HMM classification algorithm have been verified in a comparison. Index Terms-Badminton stroke recognition, body sensor networks (BSN), hidden Markov model (HMM).

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