The purpose of this study is to determine an individual physiological signal and based on the information; develop equipment that will encourage the efficiency of exercise. To evaluate the practical use of equipment an experiment is carried out. The signal of twenty adult male is determined under condition of Exercise Stress Test. Measured physiological signals are ECG from ears, chest (Lead I), PPG from earlap, activity from ear and arm, and the body skin temperature of arm. For ECG data, there are two signals: one is ear-arm signal, and the other is chest (Lead I) signal. When compare those two, ear-arm detection rate shows 92.08% detection, and 93.13% at chest. The error rate occurred average 0.035(+/-0.014) seconds and 0.026(+/-0.017) seconds. For PPG, we can reduce the influence of motion artifact by Autocorrelation method, and as a result, peak detection rate increased from 94.3% to 98.4%, decreased the error rate with 0.058+/-0.076 to 0.023+/-0.031, Also, we certified that if the speed and elevation of the treadmill increase, physical activity increase, and the body temperature gets decreased. Upon this consequence, we developed a physiological data acquisition system that is convenient to user while they are exercising.
Purpose Wearable electrocardiogram (ECG) systems are exposed to more noises than the general ECG systems, because of the high impedance between electrodes and the skin and the need to acquire ECG data during exercise or in daily life. The purpose of this study was to enhance heart rate detection by optimizing electrode and signal processing in a wearable system during high-intensity exercise. Methods To create an optimal electrode condition, we quantitatively measured the change in noise according to a change in pattern of textile electrodes by using 3 textile electrodes with the same material quality but different patterns. We also measured the degree of skin hydration by using an MPA5 (CK Electronics, Germany) to obtain the optimal condition between electrodes and skin. To accurately detect the QRS complex, use of an improved algorithm based on a wavelet, which has strong noise tolerance, was suggested. Results We obtained root-mean-square (RMS) values that were expected to be similar to those measured with the AgAgCl electrode at the point of >120% of skin hydration. The QRS complex detection rate of the wavelet method that was suggested in this study was compared to that of an adaptive filter and mathematical morphology operator. We used the data collected during actual exercise performed at 15 km/h. The QRS complex detection rate of the proposed algorithm was 99.9%. Conclusions Through optimization of the wearable system that was suggested in this study, collection of a more accurate heart rate value is expected. In addition, the influence of noise could be minimized in the wearable system.
Message delivery mechanism based on distributed hash table (DHT) can cause performance improvement over conventional P2P (Peer-to-Peer) system by increased delivery efficiency. However, the DHT, which is based on hash function, shows a few but important shortcomings: discovery of any resource without the same key value is not possible, and also repetitive discovery steps are required to discover resources with similar names. Therefore, in this research, we propose a simple but effective method which allows us to overcome those limitations of DHT method and to achieve performance enhancement. A virtual resource is not an actual resource, but a resource that acts like a wrapper to the original resources; it represents many similar resources and makes them discovered by a single discovery query. By using a virtual resource, users can obtain a significant improvement not only on performance but also on usability. Also experiment results show that using virtual resources can bring around 30% decrease in overall bandwidth usage and around 70% decrease in discovery time depending on given environment.
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