查看更多>>摘要：In order to realise low-load cuffless and continuous blood pressure measurement in daily life, the authors developed a blood pressure estimation system combining human body communication-based wearable electrocardiograph and reflectance photoplethysmography. The principle is based on a relationship between the pulse arrive time and the systolic blood pressure. The pulse arrive time is the time period between the R-wave in electrocardiograph and peak of pulse wave. The greatest feature is the use of a human body communication-based electrocardiograph which can provide automatic synchronisation in time between the measured electrocardiograph and pulse wave signals to obtain the pulse arrive time so that no additional synchronisation circuit is required. Using this system, the authors measured the pulse arrive time from the electrocardiograph and pulse wave signals in real time, estimated the systolic blood pressure and compared the result with that measured by a cuff sphygmomanometer. The authors found that the root mean square error of the estimated blood pressure and the actual value measured using the cuff sphygmomanometer was 4.5 mmHg or less, and the correlation coefficient was >0.6 with aPvalue much <0.05. These results show the validity of the developed system for cuffless and continuous blood pressure estimation.
查看更多>>摘要：Hypertension is a chronic disease that can harm the health of many people. Though hypertension may be caused by many factors, the diet has been recognised as a factor, which can seriously impact hypertension. In this Letter, the authors explore the relationship between the nutritional ingredients and hypertension with machine learning methods. They design a prediction scheme, which is constructed by nutritional ingredients data conversion, feature selection, classifiers etc. To choose the proper classifier, the performance of several classification algorithms are compared. Based on their experimental results, XGboost is used as the classifier in their scheme as it obtains the highest accuracy (84.9%) and F1_score = 0.841.
查看更多>>摘要：In recent years, with the development of intelligent vehicles, the demand for security will be bigger and bigger. One of the most important solutions is the use of new biometric technology. At present, there are still some areas to be improved on biometric technology. For example, diseases will destroy some biological characteristics, some detection methods are too slow, many detection methods do not need living detection, and so on. Electroencephalogram (EEG) is a new biometric tool for living identification. In this Letter, a kind of identity authentication system based on the EEG signal is presented. The overall goal of this research is to design a new authentication method and develop the corresponding application. Therefore, the authors carried out a series of EEG experiments, and analysed and discussed the experimental results. Based on these results, they build and present an access control system based on the uniqueness of their EEG signals to be capable of authenticating access control to the car. The accuracy of the authentication system is >87.3%.
查看更多>>摘要：A signal-piloted linear phase filtering tactic for removing baseline wander and power-line interference from the electrocardiogram (ECG) signals is suggested. The system is capable of adjusting its parameters by following the incoming signal variations. It renders the processing of lesser samples by inferior order filters. The applicability is demonstrated by using the MIT-BIH ECG database. The precision of the approach is also studied regarding the signal-to-noise ratio (SNR). Results showed that the proposed method achieves a 2.18-fold compression gain and notable computational efficiency over conventional counterpart while securing an analogous output SNR. A comparison of the designed solution is made with the contemporary empirical mode decomposition with Kalman filtering and eigenvalue decomposition based tactics. Results show that the suggested method performs better in terms of output SNR for the studied cases.
NETL
NSTL
Inst Engineering Technology-Iet
Wiley