HIGHLIGHTS
- who: Yantao Xing et al. from the School of Instrument Science and Engineering, Southeast University, Nanjing, China have published the paper: An Artifact-Resistant Feature SKNAER for Quantifying the Burst of Skin Sympathetic Nerve Activity Signal, in the Journal: Biosensors 2022, 355 of 18/05/2022
- what: This paper proposed an SNA evaluation method based on SKNA burst area detection.
- how: The results showed that SKNAER correlated well with HRV features (r = 0.60 with the standard deviation of NN intervals 0.67 with low frequency/high frequency 0.47 with very low . . .
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