Objectives

The photoplethysmographic (PPG) signal has the potential to aid in the acquisition and analysis of heart rate variability (HRV) signal: a non-invasive quantitative marker of the autonomic nervous system that could be used to assess cardiac health and other physiologic conditions. A low-power wireless PPG device was custom-developed to monitor, acquire and analyze the arterial pulse in the finger. The system consisted of an optical sensor to detect arterial pulse as variations in reflected light intensity, signal conditioning circuitry to process the reflected light signal, a microcontroller to control PPG signal acquisition, digitization and wireless transmission, a receiver to collect the transmitted digital data and convert them back to their analog representations. A personal computer was used to further process the captured PPG signals and display them. A MATLAB program was then developed to capture the PPG data, detect the RR peaks, perform spectral analysis of the PPG data, and extract the HRV signal. A user-friendly graphical user interface (GUI) was developed in LabView to display the PPG data and their spectra. The performance of each module (sensing unit, signal conditioning, wireless transmission/reception units, and graphical user interface) was assessed individually and the device was then tested as a whole. Consequently, PPG data were obtained from five healthy individuals to test the utility of the wireless system. The device was able to reliably acquire the PPG signals from the volunteers. To validate the accuracy of the MATLAB codes, RR peak information from each subject was fed into Kubios software as a text file. Kubios was able to generate a report sheet with the time domain and frequency domain parameters of the acquired data. These features were then compared against those calculated by MATLAB. The preliminary results demonstrate that the prototype wireless device could be used to perform HRV signal acquisition and analysis.

BackgroundThe increase in overall rates of cesarean sections (CS) in Brazil causes concern and it appears that multiple factors are involved in this fact. In 2009, undergraduate students in the first and final years of medical school at the University of Santa Catarina answered questionnaires regarding their choice of mode of delivery. The aim of the study was to evaluate whether the education process affects decision-making regarding the waay of childbirth preferred by medical students.MethodsA cross-sectional, quantitative study was conducted based on data obtained from questionnaires applied to medical students. The questions addressed four different scenarios in childbirth, as follows: under an uneventful pregnancy; the mode of delivery for a pregnant woman under their care; the best choice as a healthcare manager and lastly, choosing the birth of their own child. For each circumstance, there was an open question to explain their choice.ResultsA total of 189 students answered the questionnaires. For any uneventful pregnancy and for a pregnant woman under their care, 8.46% of the students would opt for CS. As a healthcare manager, only 2.64% of the students would recommend CS. For these three scenarios, the answers of the students in the first year did not differ from those given by students in the sixth year. In the case of the student’s own or a partner’s pregnancy, 41.4% of those in the sixth year and 16.8% of those in the first year would choose a CS. A positive association was found between being a sixth year student and a personal preference for CS according to logistic regression (OR = 2.91; 95%CI: 1.03–8.30). Pain associated with vaginal delivery was usually the reason for choosing a CS.ConclusionsA higher number of sixth year students preferred a CS for their own pregnancy (or their partner’s) compared to first year students. Pain associated with vaginal delivery was the most common reason given for haven chosen a CS. The students’ preference for childbirth changed over time during their graduation in favor of cesarean sections. This finding deserves considerable attention when structuring medical education in Obstetrics.

The analysis of time duration between consecutive R waves of electrocardiogram (ECG) is a standard method to evaluate the variations in heart rate. The physiological literature reveals that blood glucose levels modulate the autonomic nervous system (ANS) activity and heart rate variability (HRV) is representative of the cardiovascular autonomic function. In the research described here, a pilot investigation was carried out to investigate the relationship between HRV signal measures derived from ECG and arterial blood glucose changes in a female subject with type 1 diabetes mellitus (T1DM) subject during normoglycemic and mildly hyperglycemic conditions. A CleveLabs BioCapture wireless device was used to acquire ECG signals from a 160 Kg, 59.6 year old female volunteer with type 1 diabetes. The PhysioToolkit Software was used to extract the HRV signal and the Kubios software package was deployed to perform comprehensive HRV signal analysis. This software has an easy-to-use graphical user interface that displays the HRV signal and provides three options to calculate: Time-domain, Frequency-domain and Nonlinear Dynamics parameters from raw HRV signals. In its Frequency-domain analysis section, it provides frequency bands such as VLF (Hz), LF (Hz), and HF (Hz), with LF/HF as an index that reflects the sympathovagal balance of the ANS. ECG data were acquired for 30 minutes during normoglycemic condition and for another 30 minutes during mildly hyperglycemic conditions, while blood glucose levels were measured manually by the subject using a glucometer every 5 minutes. ECG signal segments of 5 minute durations were then processed to extract HRV signals and these in turn were analyzed to provide frequency-domain measures. The results indicated that blood glucose changes were inversely related to LF/HF. For this dataset, it was observed that mean ± std of the LF/HF decreased from 6.0 ± 1.04 to 0.91 ± 0.17 when blood glucose levels increased from 156 ± 22 mg/dl to 202 ± 29 mg/dl. Further investigation is underway to recruit more diabetic subjects to acquire a large dataset and explore the relationships between different HRV signal parameters and blood glucose changes under different gylcemic conditions in a comprehensive way.

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