Preª²processing and spectral analysis of arterial blood pressure signals in conscious rats

    LIU Xin1, CHENG Jiuª²Hua2, LU Hongª²Bing1, ZHANG Liª²Fan2, DONG Xiuª²Zhen1

    1Department of Computer Application, School of Biomedical Engineering, 2Department of Aerospace Physiology, School of Aerospace Medicine, Fourth Military Medical University, Xi¬ðan 710033, China

    ¡¾Abstract¡¿ AIM: To apply preª²processing and spectral analysis of systolic blood pressure and heart rate signals in conscious rats to evaluate changes in cardiovascular regulatory function induced by simulated weightlessness. METHODS: The tailª²suspended, hindlimbª²unloaded (HU) rat model was used to simulate the cardiovascular effect of microgravity. A pressure transducer connected to a PEª²50-PEª²10 catheter was inserted via the right femoral artery into the posterior abdominal aorta in conscious rats. We applied first derivative and template match algorithm to obtain systolic blood pressure variability (SBPV) data form original blood pressure data. PP time series extracted form the SBP time series were used to substitute the data of RR time series. SBPV data were analyzed by periodogram. RESULTS: An algorithm of first derivative and template match was suitable for effectively identifying SBP time series. The PP time series could replace RR time series. Power spectrum of SBPV, estimated by periodogram could be divided into 3 different frequency bands, very low frequency, low frequency, and high frequency. CONCLUSION: Periodogram is a useful method for blood pressure data processing, which is effective in detecting cardiovascular dysfunction in conscious rats after a 14ª²d simulated microgravity, and may be helpful for cardiovascular signal analysis in conscious rats. ......