ECG authentication in post-exercise situation.

Human authentication based on electrocardiogram (ECG) has been a remarkable issue for recent ten years. This paper proposed an authentication technology with the ECG data recorded after the harsh exercise. 55 subjects voluntarily attended to this experiment. A stepper was used as an exercise equipment. The subjects are asked to do stepper for 5 minutes and their ECG signals are acquired before and after the exercise in rest, sitting posture. Linear discriminant analysis (LDA) was used for both feature extraction and classification. Even though, within the first 1 minute recording, the subject recognition accuracy was 59.64%, which is too low to utilize, after one minute the accuracy was higher than 90% and it increased up to 96.22% within 5 minutes, which is plausible to use in authentication circumstances. Therefore, we have concluded that ECG authentication techniques will be able to be used after 1 minute of catching breath.

Heart rate variability in patients with major depressive disorder and healthy controls during non-REM sleep and REM sleep.

The objectives of this study are to investigate heart rate variability (HRV) in major depressive disorder patients (MDD) and healthy controls during different sleep stages, and to examine the association of HRV during sleep and depression severity. Polysomnography was recorded from 15 depressive patients with a higher beck depression inventory index (BDI > 25, H-BDI-D), 15 depressive patients with a lower BDI index (BDI ≤ 25, L-BDI-D) and 15 healthy controls. HRV was calculated during the first three rapid eye movements (REM) periods and non-REM stages (i.e. sleep stage 2 and 3) with time domain, power spectral and fractal analysis. As a result, H-BDI-D patients showed the highest short-term fractal alpha-1 exponent during first REM period and healthy controls had the lowest values. Our results suggest an association between the depression severity and the autonomic nerve function, especially during the first REM sleep. The pathophysiological analysis for this property should be conducted in future prospective studies.

Heart rate estimation from facial photoplethysmography during dynamic illuminance changes.

Camera-based remote photoplethysmography (rPPG) enables low-cost, non-contact cardiovascular activity monitoring. However, applying rPPG to practical use has some limitations caused from the artifacts by illuminance changes. During watching a video in a dark room, for example, watching a TV at night without illuminance, there is a high correlation between the brightness changes of a video and the illuminance variation on the skin of the viewer's face. In this study, we propose an artifact reduction method in rPPG, which is caused by the variation of the illuminance. The method subtracts the artifacts from the raw facial rPPG signal by applying multi-order curve fitting between the illuminance information from the facial rPPG signal and the brightness information from a video. On average, the results showed that signal-to-noise ratio (SNR) increased from -11.74 to -4.19 dB and from -15.27 to 7.99 dB for low-dynamic-brightness and high-dynamic-brightness video, respectively. In addition, the root-mean-square-error (RMSE) of estimated heart rate decreased from 11.00 to 1.82 bpm and from 9.88 to 4.65 bpm for the videos, respectively.

Estimation of body temperature rhythm based on heart activity parameters in daily life.

Body temperature contains valuable health related information such as circadian rhythm and menstruation cycle. Also, it was discovered from previous studies that body temperature rhythm in daily life is related with sleep disorders and cognitive performances. However, monitoring body temperature with existing devices during daily life is not easy because they are invasive, intrusive, or expensive. Therefore, the technology which can accurately and nonintrusively monitor body temperature is required. In this study, we developed body temperature estimation model based on heart rate and heart rate variability parameters. Although this work was inspired by previous research, we originally identified that the model can be applied to body temperature monitoring in daily life. Also, we could find out that normalized Mean heart rate (nMHR) and frequency domain parameters of heart rate variability showed better performance than other parameters. Although we should validate the model with more number of subjects and consider additional algorithms to decrease the accumulated estimation error, we could verify the usefulness of this approach. Through this study, we expect that we would be able to monitor core body temperature and circadian rhythm from simple heart rate monitor. Then, we can obtain various health related information derived from daily body temperature rhythm.

Newly developing endoscopic devices--shadow optics and micromachine

Based on the newly-developed engineering technologies, many kinds of useful equipment have been available for minimally invasive surgery. Recently the time to connect clinical needs and advanced technologies has become faster. In this article, we have summarized the recent technologies for endoscopic surgeries. Shadow optic technologies for better geometric perception using dual illumination in a conventional 2-D monitor and "Overview optics" for a panoramic view with an additional visual system are introduced. Micromachine technology is very close to practical implementation for minimally invasive surgeries. Virtual Biopsy is the one of the hottest topics for the next generation of endoscopy. Stereoscopic and volumetric vision systems are still on the way, which should overcome the irritating goggles and stereo display devices. As well as operational theater that integrates all the required equipment with a computer-based system, including voice recognition, still requires the standard protocols to connect many kinds of devices from different manufacturers.