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Figure 5: Bland–Altman Plots Showing Agreement Between the rPPG- And Reference-Derived pNN50 From (A) the Average of All 30 S Recordings and (B) the 60 S Recordings.
doi 10.7717/peerj.8342/fig-5
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Figure 4: Bland–Altman (BA) Plots Showing Agreements Between the RMSSD Values Derived From rPPG and Those Derived From the Reference (PPG) Signals. (A)–(C) Show the BA Plots for RMSSD Derived From (A) the Average of All 10 S Recordings, (B) the Average of All 30 S Recordings, and (C) the 60 S Recordings.
Figure 3: Bland–Altman (BA) Plots Showing Levels of Agreement Between the SDNN/lnSDNN Values Derived From rPPG and Those Derived From the Reference (PPG) Signals.
Table 7: Correlation and Effect Size Metrics Measuring the Agreement Between the SDNN, lnSDNN, RMSSD, and pNN50 Values Derived From rPPG Recordings of Different Lengths and the Metrics Derived From the 60 S Reference (PPG) Recordings.
Figure 5: The Bland-Altman Plot Showing the Difference Between the AI BA and the Reference Standard.
Figure 5: Bland–Altman Plots for Off-Speed Arm Speed Comparisons.
Figure 3: Bland–Altman Plots Showing Differences in Sedentary, Light, Moderate and Vigorous Activity Time Between ACC and EMG.
Figure 3: Bland-Altman Plots of the Inter-Rater Agreements in Measuring Total Lean Volume (A) and Total Fat Volume (B).
Figure 6: Bland–Altman Plots for Force Plate and WIMU in CMJ.
Classification of 5-S Epileptic EEG Recordings Using Distribution Entropy and Sample Entropy
Frontiers in Physiology
Physiology
