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| An Online Heart Rate Variability Analysis Method Based on Sliding Window Hurst Series |
| Taizhi Lv, Yangquan Chen, Marwin Ko |
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Abstract Heart Rate Variability (HRV) analysis is based on variability
between each heartbeat which is used as a diagnosis method for
assessing the cardiovascular modulation of autonomic nerve system.
Up to now, most HRV analysis has been done offline. However, in many
relevant applications, HRV should be analyzed online such as the
analysis of stress level and the detection of the drowsiness while
driving. This paper proposes an online analysis method which can be
used in platforms for human robot cooperation. This online analysis
method based on a sliding Hurst window can be applied to estimate
the heart status. By the sliding Hurst series, the two indices,
cumulative mean of Hurst series (CMHurst) and cumulative standard
deviation of Hurst series (CStdHurst) are introduced as indicators
to distinguish heart health status. Using this method, the hardware
requirement is significantly low, and the execution time is short.
Some databases from the PhysioBank are used for test these indices.
The results show this method can distinguish between the groups who
have normal rhythm and abnormal rhythm.
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| Cite this article: |
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Taizhi Lv,Yangquan Chen,Marwin Ko. An Online Heart Rate Variability Analysis Method Based on Sliding Window Hurst Series[J]. Journal of Fiber Bioengineering and Informatics, 2015, 8(2): 391-400.
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2015, Vol. 8 
