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Combining blood pressure variability and heart rate variability to analyze the autonomic nervous function of rotenone
Nan Yang1, Tao Tan2, Jiarong Wei2
1School of Medical Engineering of Xinxiang Medical University, Xinxiang, China; Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, People's Republic of China; Henan Engineering Laboratory of Combinatorial Technique for Clinical and Biomedical Big Data, Xinxiang, China; Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China; The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Collaborative Innovation Center of Prevention and treatment of mental disorder, Xinxiang, China.
Background:
Parkinson's patients have significant autonomic dysfunction, early detect the disorder is a major challenge. To assess the autonomic function in the rat model of rotenone induced Parkinson's disease (PD), Blood pressure and ECG signal acquisition are very important.
New Method:
We used telemetry to record the electrocardiogram and blood pressure signals from awake rats, with linear and nonlinear analysis techniques calculate the heart rate variability (HRV) and blood pressure variability (BPV). we applied nonlinear analysis methods like sample entropy and detrended fluctuation analysis to analyze blood pressure signals. Particularly, this is the first attempt to apply nonlinear analysis to the blood pressure evaluate in rotenone induced PD model rat.
Results:
HRV in the time and frequency domains indicated sympathetic-parasympathetic imbalance in PD model rats. Linear BPV analysis didn't reflect changes in vascular function and blood pressure regulation in PD model rats. Nonlinear analysis revealed differences in BPV, with lower sample entropy results and increased detrended fluctuation analysis results in the PD group rats.
Comparison With Existing Methods And Conclusions:
our experiments demonstrate the ability to evaluate autonomic dysfunction in models of Parkinson's disease by combining the analysis of BPV with HRV, consistent with autonomic impairment in PD patients. Nonlinear analysis by blood pressure signal may help in early detection of the PD. It indicates that the fluctuation of blood pressure in the rats in the rotenone model group tends to be regular and predictable, contributes to understand the PD pathophysiological mechanisms and to find strategies for early diagnosis.
