Time course of the SPLF on human RR-interval series with1-min increment (red solid line) and 5-min increment (green dotted line).

<p>M and N labelled on the signal represent Meditation and Non-meditation state, respectively. It can be seen that 1-min-increment-based HRV analysis measure gives an earlier responses to the changes of meditation states than 5-min-increment-based measure.</p

Time course of the SPLF on human RR-interval series with1-min increment (red solid line) and 5-min increment (green dotted line).

<p>M and N labelled on the signal represent Meditation and Non-meditation state, respectively. It can be seen that 1-min-increment-based HRV analysis measure gives an earlier responses to the changes of meditation states than 5-min-increment-based measure.</p

Results obtained from protein 1P9H.

<p>(A). The cartoon structure, with the two symmetric substructures shown in red and green respectively. (B). The profile of local codon usage bias: the region with major decreases in <i>CAI</i> value is shown with dashed square lines. (C). The comparison between the profile of the natural gene sequence and the averaged profile of the same codon sequence randomized by 10 times. The blue line is for natural gene sequence and the red line is for the average of the random sequences. (D) and (E). The profile of local folding free energy and the comparison between the natural gene sequence and the random sequences, respectively. The blue line is for natural gene sequence and the red line is for the average of the random sequences.</p

Time course of SPLF components derived from signal segments created by sliding window with six time increments.

<p>With the time increment increasing, the time courses of the measure become smoother, resulting in losing the dynamical information. When increasing the time increment to 5 min, the measure could not provide any useful information about the temporal dynamics in the representative synthetic signal.</p

Recurrence plots for 8 proteins.

<p>The first and third horizontal panel: the recurrence plot of the nucleotide sequence; the second and the fourth horizontal panel: the recurrence plot for codon usage bias in the codon sequence of the corresponding proteins. The PDB id of the protein is given in each of the plot.</p

Results obtained from protein 1YP2.

<p>(A). The cartoon structure: the two symmetric substructures are shown in red and green; the extended irregular structure in the middle of the helix is shown in blue. (B). The profile of local codon usage bias: the decreased region in the middle of the codon sequence is shown with dashed square lines. (C). The comparison between the profile of the natural gene sequence and the averaged profile of the same codon sequence randomized by 10 times. The blue line is for natural gene sequence and the red line is for the average of the random sequences. (D). The profile of local folding free energy, and the dashed square lines shows the region with decreased local folding free energy. (F). The comparison between the natural gene sequence and the random sequences. The blue line is for natural gene sequence and the red line is for the average of the random sequences.</p

The profile for local mRNA folding free energy and the comparison of natural gene sequences to the random sequences.

<p>The x-axis is the nucleotide sequence and the y-axis is the local folding free energy. The region with major decrease of local mRNA folding free energy is shown with dashed square lines. The blue line is for natural gene sequence and the red line is for the average of the random sequences.</p

Time courses of measures of HRV analysis on ECG data from a dog with1-min increment (red solid line) and 5-min increment (green dotted line).

<p>Four rows from top to bottom correspond to the SDNN (standard deviation of the normal-to-normal intervals), RMSSD (square root of the mean squared differences of successive intervals), SPLF (power spectrum in low frequency), and SPHF (power spectrum in high frequency) components. Following the application of atropine, all the four measures of HRV analysis with 1-min increment instantly decreased and reached their minimum values within about seven minutes, and then gradually increased. With a 5-min increment, the four measures began to decrease about three minutes later after giving atropine.</p

Toward Capturing Momentary Changes of Heart Rate Variability by a Dynamic Analysis Method

<div><p>The analysis of heart rate variability (HRV) has been performed on long-term electrocardiography (ECG) recordings (12~24 hours) and short-term recordings (2~5 minutes), which may not capture momentary change of HRV. In this study, we present a new method to analyze the momentary HRV (mHRV). The ECG recordings were segmented into a series of overlapped HRV analysis windows with a window length of 5 minutes and different time increments. The performance of the proposed method in delineating the dynamics of momentary HRV measurement was evaluated with four commonly used time courses of HRV measures on both synthetic time series and real ECG recordings from human subjects and dogs. Our results showed that a smaller time increment could capture more dynamical information on transient changes. Considering a too short increment such as 10 s would cause the indented time courses of the four measures, a 1-min time increment (4-min overlapping) was suggested in the analysis of mHRV in the study. ECG recordings from human subjects and dogs were used to further assess the effectiveness of the proposed method. The pilot study demonstrated that the proposed analysis of mHRV could provide more accurate assessment of the dynamical changes in cardiac activity than the conventional measures of HRV (without time overlapping). The proposed method may provide an efficient means in delineating the dynamics of momentary HRV and it would be worthy performing more investigations.</p></div

Time course of the SPLF on human RR-interval series with1-min increment (red solid line) and 5-min increment (green dotted line).

<p>M and N labelled on the signal represent Meditation and Non-meditation state, respectively. It can be seen that a 5-min-increment-based measure was hardly to capture the happenings of 2-min non-meditation state among the meditation states, 1-min-increment-based measure could clearly catch the short-time changes of meditation state.</p