Tharoeun Thap

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We proposed new electrodes that are applicable for electrocardiogram (ECG) monitoring under freshwater- and saltwater-immersion conditions. Our proposed electrodes are made of graphite pencil lead (GPL), a general-purpose writing pencil. We have fabricated two types of electrode: a pencil lead solid type (PLS) electrode and a pencil lead powder type (PLP)(More)
We introduce a cardiac rehabilitation program (CRP) that utilizes only a smartphone, with no external devices. As an efficient guide for cardiac rehabilitation exercise, we developed an application to automatically indicate the exercise intensity by comparing the estimated heart rate (HR) with the target heart rate zone (THZ). The HR is estimated using(More)
In this study, we obtained a pulsatile photoplethysmogram (PPG) signal from a fingertip using the built-in camera of an iPhone 6 s and displayed a real-time heart activity images with holographic projection on a smartphone screen. Our proposed heart activity hologram is simple and can be easily realized with only a smartphone and overhead projector (OHP)(More)
In this paper, a smartphone-based lung function test, developed to estimate lung function parameters using a high-resolution time-frequency spectrum from a smartphone built-in microphone is presented. A method of estimation of the forced expiratory volume in 1 s divided by forced vital capacity (FEV₁/FVC) based on the variable frequency complex demodulation(More)
We proposed a technique to eliminate motion artifacts by subtracting the two green signals with different light intensity from single green LED. We used green LED light source with a photodetector to obtain the PPG signals from the wrist. We showed that the signal subtraction with different light intensity from the same light source reduced motion(More)
In this paper, we used smartphone to obtained pulsatile signal from a fingertip by illuminating the skin tissue using flashlight and with an on-board camera to record the change of the light intensity reflected from the tissue. The pulsatile signal is produced by analyzing average green component values of the frames taken by the camera and the heart rate(More)
In this study, we analyzed three statistical methods for automatic detection of Atrial Fibrillation (AF) and Congestive Heart Failure (CHF) based on the randomness, variability and complexity of the heart beat interval, which is RRI time series. Specifically, we used short RRI time series with 16 beats and employed the normalized Root Mean Square of(More)
In this paper, we use smartphone's built-in camera with flash light to obtain the pulsatile signal from fingertip and then apply the peak detection algorithm to detect the pulse's peaks and after that calculate the R-R interval (RRI) in real time. We design the animated heart images that beat according to each RRI of the pulsatile signal. At the same time,(More)
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