A correlation study of beat-to-beat R-R intervals and pulse arrival time under natural state and cold stimulation.

Beat-to-beat R-R intervals (RRI) and pulse arrival time (PAT) provide pivotal information to evaluate cardiac autonomic functions for predicting arrhythmias and cardiovascular morbidity. However, their relationship has not been clearly understood. In this study, we simultaneously recorded electrocardiograms and photoplethysmograms on 34 subjects in the natural state, and on 55 subjects under the cold stimulation. The RRI and the PAT were calculated and then analyzed using Pearson correlation coefficient. The results showed that the RRI and the PAT were strongly correlated (r = 0.562) and the RRI series were 2.18 ± 0.40 beats advanced to the PAT series. After smoothing, the RRI and the PAT were more correlated in the low frequency than in the high frequency. Furthermore, when involving RRI with the phase effect, the proposed PAT based model showed better performance for blood pressure estimation. We think these results are helpful to understand the underlying regulatory mechanisms of the two cardiovascular factors, and would provide useful suggestions for non-invasive cuffless blood pressure estimation.

Cuffless and Continuous Blood Pressure Estimation from the Heart Sound Signals.

Cardiovascular disease, like hypertension, is one of the top killers of human life and early detection of cardiovascular disease is of great importance. However, traditional medical devices are often bulky and expensive, and unsuitable for home healthcare. In this paper, we proposed an easy and inexpensive technique to estimate continuous blood pressure from the heart sound signals acquired by the microphone of a smartphone. A cold-pressor experiment was performed in 32 healthy subjects, with a smartphone to acquire heart sound signals and with a commercial device to measure continuous blood pressure. The Fourier spectrum of the second heart sound and the blood pressure were regressed using a support vector machine, and the accuracy of the regression was evaluated using 10-fold cross-validation. Statistical analysis showed that the mean correlation coefficients between the predicted values from the regression model and the measured values from the commercial device were 0.707, 0.712, and 0.748 for systolic, diastolic, and mean blood pressure, respectively, and that the mean errors were less than 5 mmHg, with standard deviations less than 8 mmHg. These results suggest that this technique is of potential use for cuffless and continuous blood pressure monitoring and it has promising application in home healthcare services.

Time-frequency analysis of heart rate variability during the cold pressor test using a time-varying autoregressive model.

Heart rate variability is a useful clinical tool for autonomic function assessment and cardiovascular disease diagnosis. To investigate the dynamic changes of sympathetic and parasympathetic activities during the cold pressor test, we used a time-varying autoregressive model for the time-frequency analysis of heart rate variability in 101 healthy subjects. We found that there were two sympathetic peaks (or two parasympathetic valleys) when the abrupt changes of temperature (ACT) occurred at the beginning and the end of the cold stimulus and that the sympathetic and parasympathetic activities returned to normal in about the last 2 min of the cold stimulus. These findings suggested that the ACT rather than the low temperature was the major cause of the sympathetic excitation and parasympathetic withdrawal. We also found that the onsets of the sympathetic peaks were 4-26 s prior to the ACT and the returns to normal were 54-57 s after the ACT, which could be interpreted as the feedforward and adaptation of the autonomic regulation process in the human body, respectively. These results might be helpful for understanding the regulatory mechanisms of the autonomic system and its effects on the cardiovascular system.

[Identification and analysis of genuine and false Flos Rosae Rugosae by FTIR and 2D correlation IR spectroscopy].

The genuine and false Flos Rosae Rugosae (Flos Rosae Chinensis and Flos Rosa multiflora) were examined in terms of their differences by using Fourier transform infrared spectroscopy (FTIR) combined with two-dimensional (2D) correlation IR spectroscopy. The three species were shown very similar in FTIR spectra. The peak of 1318 cm(-1) of genuine Flos Rosae Rugosae is not obvious but this peak could be found sharp in Flos Rosae Chinensis and Flos Rosa multiflora. Generally, the second derivative IR spectrum can clearly enhance the spectral resolution. Flos Rosae Rugosae and Flos rosae Chinensis have aromatic compounds distinct fingerprint characteristics at 1 617 and 1 618 cm(-1), respectively. Nevertheless, FlosRosa multiflora has the peak at 1612 cm(-1). There is a discrepancy of 5 to 6 cm(-1). FlosRosa multiflora has glucide's distinct fingerprint characteristics at 1 044 cm(-1), but Flos Rosae Rugosae and Flos Rosae Chinensis don't. The second derivative infrared spectra indicated different fingerprint characteristics. Three of them showed aromatic compounds with autopeaks at 1620, 1560 and 1460 cm(-1). Flos Rosae Chinensis and Flos Rosa multiflora have the shoulder peak at 1660 cm(-1). In the range of 850-1250 cm(-1), three of them are distinct different, Flos Rosae Rugosae has the strongest autopeak, Flos Rosae Chinensis has the feeble autopeak and Flos Rosa multiflora has no autopeak at 1050 cm(-1). In third-step identification, the different contents of aromatic compounds and glucide in Flos Rosae Rugosae, Flos Rosae Chinensis and Flos Rosa multiflora were revealed. It is proved that the method is fast and effective for distinguishing and analyzing genuine Flos Rosae Rugosae and false Flos Rosae Rugosae (Flos Rosae Chinensis and Flos Rosa multiflora).