Clinical studies had demonstrated that slow breathing could lower blood pressure significantly. Based on this knowledge, a portable blood pressure depressor was designed in this study. The device used a miniature variable distance capacitive sensor to collect respiratory signal, an STM32 as the main control chip, a WT588D voice chip to generate voice and music and guide slow breathing, and a 3.5-inch color screen to display breathing state and provide guidance. For patients with difficulty in adapting themselves to the slow breathing training, an intelligent guiding breathing algorithm based on feedback regulation mechanism was proposed to train patients to breathe slowly. Ten volunteers with hypertension were recruited and then trained to breathe slowly, accumulating up to 100 times using this device. The results showed that breath rate of the volunteers decreased from 15.16±0.92 times per minute to 9.40±0.29 times per minute, and meanwhile, time length of breath rate less than 8 times per minute in the proportion of total treatment time increased from 0.079±0.017 to 0.392±0.019 as the training times increased. In a conclusion, the proposed blood pressure depressor worked effectively in guiding slow breathing training.
Real-time continuous glucose monitoring can help diabetics to control blood sugar levels within the normal range. However, in the process of practical monitoring, the output of real-time continuous glucose monitoring system is susceptible to glucose sensor and environment noise, which will influence the measurement accuracy of the system. Aiming at this problem, a dual-calibration algorithm for the moving-window double-layer filtering algorithm combined with real-time self-compensation calibration algorithm is proposed in this paper, which can realize the signal drift compensation for current data. And a real-time continuous glucose monitoring instrument based on this study was designed. This real-time continuous glucose monitoring instrument consisted of an adjustable excitation voltage module, a current-voltage converter module, a microprocessor and a wireless transceiver module. For portability, the size of the device was only 40 mm × 30 mm × 5 mm and its weight was only 30 g. In addition, a communication command code algorithm was designed to ensure the security and integrity of data transmission in this study. Results of experiments in vitro showed that current detection of the device worked effectively. A 5-hour monitoring of blood glucose level in vivo showed that the device could continuously monitor blood glucose in real time. The relative error of monitoring results of the designed device ranged from 2.22% to 7.17% when comparing to a portable blood meter.
Objective To explore the solutions of problems with the ROC analysis for different types data. Method Two kinds of ROC analyses of three cardiac infarction markers, cTNT, CK-MB mass and MYO, were performed with the ROC program developed by Yunnan Provincial Clinical Laboratory Center. Results The distribution of prime data had a large range, which produced a bad analysis result. After logarithmic transformation, the prime data that had smaller range now can be analyzed with full-span method. The results were similar to the ROC analyzed with the overlapped data. Conclusions We should choose different statistical method depend on the distribution of data when we performed ROC analyses.