ABSTRACT
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 (
Subject(s)
Humans , Electrocardiography , Heart Rate , Signal Processing, Computer-Assisted , Wavelet Analysis , Wearable Electronic DevicesABSTRACT
Based on the requirements of military professional education reform and in view of the problems existing in the operation and maintenance of first-aid medical equipment in grass-roots forces. We put forward a construction scheme of online course which named operation and maintenance of first-aid medical equipment in grass-roots forces, and then expound the scheme from teaching content construction and teaching mode construction. The teaching content construction consists of two parts: the management theory of conventional medical equipments and the operation and maintenance teaching of specific first-aid medical equipments. In the construction of teaching mode, we elaborate on the organization forms of teaching, answering questions, training and examination units in detail. The design scheme of the online course is in line with the learning characteristics and meets the demand of learning the knowledge of the operation and maintenance of first-aid medical equipment systematically, so as to improve the post competency of the grass-roots forces.
ABSTRACT
To overcome the problems of current electrocardiogram (ECG) tele-monitoring devices used for daily life, according to information fusion thought and by means of wearable technology, we developed a new type of wearable ECG monitor with the capability of physical activity recognition in this paper. The ECG monitor synchronously detected electrocardiogram signal and body acceleration signal, and recognized the scene information of physical activity, and finally determined the health status of the heart. With the advantages of accuracy for measurement, easy to use, comfort to wear, private feelings and long-term continuous in monitoring, this ECG monitor is quite fit for the heart-health monitoring in daily life.
Subject(s)
Humans , Electrocardiography, Ambulatory , Equipment Design , Heart , Physiology , Monitoring, Physiologic , Motor Activity , Signal Processing, Computer-Assisted , TelemetryABSTRACT
Object To establish a method for the assay of myricetin in Ampelopsis grossedentata (Hand. Mazz.) W. T. Wang. Methods The determination was carried out with RP HPLC on Nova pak C 18 stainless steel column (150 mm ? 3 9 mm) with methanol∶water (40∶60) as the mobile phase, and detected at a UV wave length of 254 nm. Results The coefficient of variation was 2.763% with average recoveries=97.4%. The minimal detectable limit was 15 ng. Contents of myricetin in different parts of A. grossedentata from Hunan Province varied from 1.57% to 2.17%. Conclusion The method is rapid, simple, accurate and good for the determination of myricetin in A. grossedentata.