A computerized resolution visual acuity test in preschool and school age children.

AIM: To develop a novel approach called the Autoacuity Tester, and to evaluate its validity, especially the sensitivity and specificity for detecting amblyopia. METHODS: Children aged from 3 to 12y (n=552) were enrolled in the study. The validity of the Autoacuity Tester was evaluated by comparing it to the Tumbling E Early Treatment Diabetic Retinopathy Study (ETDRS) acuity chart for school age children, and Lea Symbols and Teller acuity card (TAC) for preschool children. The repeatability was assessed by coefficient of repeatability (COR). The sensitivity and specificity for detecting amblyopia were calculated. RESULTS: The mean difference (95% limits of agreement) between the Autoacuity Tester and the ETDRS tests were -0.03 (-0.24, 0.19) logMAR for the school age group. In preschool children, the mean difference was 0.04 (-0.14, 0.21) logMAR between the Autoacuity Tester and the TAC and 0.00 (-0.17, 0.18) logMAR between the Autoacuity Tester and the Lea Symbols. For the school age group, the COR was 0.20 logMAR for the Autoacuity Tester and 0.18 logMAR for the ETDRS. For the preschool group, the COR was 0.13 logMAR for the Autoacuity Tester and 0.21 logMAR for TAC. The Autoacuity Tester (88%) is more sensitive than TAC (72%) in detecting amblyopia (P=0.04), while had similar specificity (92% vs 90%, P=0.20). CONCLUSION: The Autoacuity Tester provides a reliable alternative for assessing visual acuity, and offers advantage of higher testability and repeatability for preschool children.

[Concept and Implementation of ECG Monitoring for Whole-course of Pre-hospital Emergency].

In pre-hospital emergency, it's essential to immediate recognize cardiac arrest, and use real-time ECG monitoring for patients. We propose a concept of whole-course ECG monitoring and implementation in pre-hospital emergency, and design a portable pre-hospital ECG monitor (Pre-ECG). There are two working modes in Pre-ECG, i.e., rapid detection and continuous monitoring modes. In rapid detection mode, ECG waves and heart rate of patients can be displayed in a few seconds by using metal electrodes, which helps to understand the status of patients' cardiac electrical activity. After connecting lead wire to the Pre-ECG, it can automatically switch to working in continous monitoring mode. At this time, ECG waves and heart rate can be displayed in real time, and give an alarm for abnormalities of heart rate, which can well meet the requirement from transfer process of patients. Moreover, all ECG data derived from the two modes can be stored permanently in TranFlash card, which can be printed via bluetooth printer, be used for remote medical consultation through the internet, or be reserved as legal evidence and academic research materials.

[Comparison Study of Heart Rate Variability at Resting and Real-time Motional States].

This study aims to discover the characteristics of heart rate variability of resting and real-time motional states in healthy population. The ECG data of 16 healthy young subjects during 5-minute resting and motion periods were recorded respectively. After that, the R wave was extracted through Hilbert transformation and the RR interval time series was computed. The calculations for HRV parameters in time and frequency domains, Poincaré scatter plots and the detrended fluctuation analysis were conducted. Our study finds that, the measures of real-time motion in time domain (Mean RR, SDNN and RMSSD), the measures in frequency domain (VLF, LF, HF, TP), and the measures of Poincaré scatter plots are significantly less than those of resting state (P <0.001). The measure of long-term fractal exponent (α2) in real-time motion state is significantly higher than resting state (P <0.05). Between the two states, there are no statistically significant differences in other parameters of frequency domain (LF norm, HF norm, LF/HF) and short-term fractal exponent (α1), P>0.05. This study suggests that, the results can provide new characteristic signatures and statistical evidence for sport medicine or rehabilitation medicine.

[Time-frequency Research of Pulse Rate Variability Based on the EEMD].

In this paper, based on the feature of ensemble empirical mode decomposition(EEMD) which is very suitable for analyzing non-stationary and nonlinear signals, the pulse rate variability (PRV) signal is decomposed into multiple intrinsic mode function (IMF) components by EEMD, to calculate the energy of each IMF component respectively, and high-frequency energy(EHF), low-frequency energy(ELF) and very low-frequency energy(EVLF) of PRV were reconstructed from the energy of the IMF components according to the characteristics of each IMF component spectrum. This method is compared with the traditional AR power spectrum estimation method through the experiment. The results show that the correlation coefficient of each frequency domain parameter corresponding to PRV obtained by the two methods is higher than 0.96, which indicates that the method can truly reflect the sympathetic nerve and vagus nerve activity.

[Wireless Passive Body Sensor for Temperature Monitoring Using Near Field Communication Technology].

In this study, we designed a wireless body temperature sensor (WBTS) based on near field communication (NFC) technology. Just attaching the WBTS to a mobile phone with NFC function, the real-time body temperature of human subjects can be acquired by an application program without seperate power supply. The WBTS is mainly composed of a digital body temperature probe (d-BTP), a NFC unit and an antenna. The d-BTP acquires and processes body temperature data through a micro control er, and the NFC unit and antenna are used for wireless energy transmission and data communication between the mobile phone and WBTS. UART communication protocol is used in the communication between the d-BTP and NFC unit, and data compression technique is adopted for improving transmission efficiency and decreasing power loss. In tests, the error of WBTS is ±0.1 oC, in range of 32 oC to 42 oC. The WBTS has advantages of high accuracy, low power loss, strong anti-interference ability, dispensation with independent power supply etc., and it can be integrated into wearable apparatuses for temperature monitoring and health management.

[A Wearable Wireless Body Sensor for Epileptic Seizure Prediction].

In this study, we designed a wearable patch-type ECG sensor (WPES), which is mainly composed of the electrodes, an ECG acquisition unit, a Bluetooth unit, and a power supplies module. By using BMD101 chip as the core of ECG acquisition, the WPES can communicate with smart phones through Bluetooth low energy (BLE). The WEPS can be well used in monitoring epileptic seizure prediction, based on the advantages of simplification of circuits, miniaturization, low-power consumption, light-weight, convenience of wearing, high-comfort etc.

[A Heart Rate Variability Analysis System for Short-term Applications].

In this paper, a heart rate variability analysis system is presented for short-term (5 min) applications, which is composed of an electrocardiogram signal acquisition unit and a heart rate variability analysis unit. The electrocardiogram signal acquisition unit adopts various digital technologies, including the low-gain amplifier, the high-resolution analog-digital converter, the real-time digital filter and wireless transmission etc. Meanwhile, it has the advantages of strong anti-interference capacity, small size, light weight, and good portability. The heart rate variability analysis unit is used to complete the R-wave detection and the analyses of time domain, frequency domain and nonlinear indexes, based on the Matlab Toolbox. The preliminary experiments demonstrated that the system was reliable, and could be applied to the heart rate variability analysis at resting, motion states etc.

[Analysis of Pulse Rate Variability and Its Application to Wearable Smart Devices].

In this paper, a reflection type photoelectric pulse wave sensor was designed for short-term pulse rate variability analysis. Photoplethysmography (PPG) signals and ECG signals (obtained with the Dimetek MicroECG recorder Dicare-m1CP) were recorded synchronously from 20 healthy subjects. The analytical results show a significant correlation (correlation coefficient r > 0.99) between the PPG-derived peak-to-peak (PP) intervals and the ECG-derived RR intervals. Besides, there are no significant differences (P > 0.05) between the HRV measured by ECG and the PRV quantified by the PPG whether in time domain, frequency domain, or the Poincaré plot parameters. The experimental results suggest that the PPG-based short-term PRV analysis can be consistent with the ECG-based HRV measurement in wearable smart devices.

[Continuous ECG recording for freely moving patients].

As more and more people are becoming aged in China and many of them tend to suffer from chronic cardiac problems, the long-term dynamic cardiac monitoring for freely moving patients becomes essential. A new design for continuous ECG recording on the freely moving patients at home and/or at work is proposed here. It is miniature in size, using digital technologies of the low gain amplifier, the high resolution analog to digital converter and the real-time digital filter that features > 100dB input signal dynamic range (ISDR), > 100dB common-mode rejection ratio (CMRR), and < 5microV (RMS) internal noise. The device works continuously more than 24 hours with a pair of AAA batteries, and is capable of storing the recorded data into a storage card. The preliminary tests showed that the P-QRS-T waveforms were captured and displayed smoothly in resting, walking, and activities, making the device useful in monitoring and analyzing for the patients on the move.

[The design of handheld fast ECG detector].

A new handheld fast ECG detector based on low gain amplifier, the high resolution analog to digital converter, the real-time digital filter, fast P-QRS-T wave detection and abstraction algorithm was designed. The results showed that the ECG detector can meet the requirements of fast detecting heart rate and ECG P-QRS-T waveforms.