ObjectiveTo evaluate the incidence of osteoporosis and relevant factors in the elderly male patients with chronic obstructive pulmonary disease(COPD).Methods Forty elderly male patients with COPD were enrolled and thirty age-matched healthy subjectss were enrolled.The BMD of lumbar vertebrae and proximal end of the femur were measured by dual energy X-ray absorptiometry.Serum levels of osteocalcin （BGP）and lung function were measured while blood-gas analysis of arterial blood was conducted.Results The BMD of lumbar vertebrae and proximal end of the femur(including lumbar 1 to 4，femoral neck，wards triangle，trochanter and shaft) in the COPD group were significantly lower than those in the control subjects(all Plt;0.01).Serum BGP level in the COPD group was higher than that in the control group[(5.67±1.59)ng/mL vs (4.37±1.47)ng/mL，Plt;0.01).The prevalence of osteoporosis among the COPD patients was significantly higher than that among the control subjects（65% vs 40%，50% vs 20%，both Plt;0.05）.BMD in the COPD patients who had a history of smoking was significantly lower than those who did not smoke cigarettes（Plt;0.01 or Plt;0.05）.BMD in the COPD patients treated with glucocorticoid were significantly lower than those who were not receiving glucocorticoid therapy(Plt;0.01 or Plt;0.05).BMD was positively correlated with PaO2，BMI，FEV1%pred and FEV1/FVC(Plt;0.01 or Plt;0.05).Conclusions Compared with age-matched normal controls，BMD in elderly male COPD patients are significantly lower with increased osteoporosis risk.Osteoporosis induced by COPD is high change-over pattern. BMD in patients with COPD may be correlated with hypoxia，lung function，smoking，low body mass index and glucocorticoids therapy.
As an important medical electronic equipment for the cardioversion of malignant arrhythmia such as ventricular fibrillation and ventricular tachycardia, cardiac external defibrillators have been widely used in the clinics. However, the resuscitation success rate for these patients is still unsatisfied. In this paper, the recent advances of cardiac external defibrillation technologies is reviewed. The potential mechanism of defibrillation, the development of novel defibrillation waveform, the factors that may affect defibrillation outcome, the interaction between defibrillation waveform and ventricular fibrillation waveform, and the individualized patient-specific external defibrillation protocol are analyzed and summarized. We hope that this review can provide helpful reference for the optimization of external defibrillator design and the individualization of clinical application.
The dynamic electrocardiogram (ECG) collected by wearable devices is often corrupted by motion interference due to human activities. The frequency of the interference and the frequency of the ECG signal overlap with each other, which distorts and deforms the ECG signal, and then affects the accuracy of heart rate detection. In this paper, a heart rate detection method that using coarse graining technique was proposed. First, the ECG signal was preprocessed to remove the baseline drift and the high-frequency interference. Second, the motion-related high amplitude interference exceeding the preset threshold was suppressed by signal compression method. Third, the signal was coarse-grained by adaptive peak dilation and waveform reconstruction. Heart rate was calculated based on the frequency spectrum obtained from fast Fourier transformation. The performance of the method was compared with a wavelet transform based QRS feature extraction algorithm using ECG collected from 30 volunteers at rest and in different motion states. The results showed that the correlation coefficient between the calculated heart rate and the standard heart rate was 0.999, which was higher than the result of the wavelet transform method (r = 0.971). The accuracy of the proposed method was significantly higher than the wavelet transform method in all states, including resting (99.95% vs. 99.14%, P < 0.01), walking (100% vs. 97.26%, P < 0.01) and running (100% vs. 90.89%, P < 0.01). The absolute error [0 (0, 1) vs. 1 (0, 1), P < 0.05] and relative error [0 (0, 0.59) vs. 0.52 (0, 0.72), P < 0.05] of the proposed method were significantly lower than the wavelet transform method during running state. The method presented in this paper shows high accuracy and strong anti-interference ability, and is potentially used in wearable devices to realize real-time continuous heart rate monitoring in daily activities and exercise conditions.