A fundamental study on visual impairment evaluation using N170.

Progressive population aging has created many problems. Many aged people suffers from cataract because prevalence of cataract in advanced age is far higher than younger people. In this study, we have focused on N170 as a visibility-related signal for quantitative evaluation of cataract. In this report, basic evaluation of N170 in presenting numerical images which had different contrasts was performed. Amplitude and latency were extracted from N170, and then relations to the contrasts of the images were checked. The results showed that the experiments had feasibility, reproducibility and universality. It was also shown that there are positive correlation between logarithm of Michelson contrast and N170 amplitude, and negative correlation between log. contrast and latency.

Biometric identification with high frequency electrocardiogram: Unregistered user refusal method and performance evaluation.

As a new modality for biometric identification, electrocardiogram-based identification technique has been developed. We proposed a technique with high frequency component of electrocardiogram (HFECG) in QRS segment. In this report, an unregistered user refusal algorithm was combined with the artificial neural network based waveform classifier. The refusal function was realized by simple thresholding technique. HFECGs from twenty collaborators were used for supervised learning. Twenty HFECGs from the same collaborators were tested and false acceptance rate (FAR) and false rejection rate (FRR) were evaluated. Ten HFECGs from other collaborators were also tested to find unregistered user refusal performance. The results show that FAR and FRR in the registrants can be kept within 1%, however, unregistered user refusal performance was not acceptable under the same condition.

A study on reception electrodes for the vital-sign monitor using near-field intra-body communication enhanced by spread spectrum technique.

As a novel vital sign monitor, we have developed wireless ECG monitoring system with Near-field intra-body communication (NF-IBC) technique. However, it was hard to ensure communication reliability because transmission channel is noisy and unstable. In order to solve the problem, we utilize spread spectrum (SS), which is known as robust communication technique even through poor transmission channel. In previous study, we have already developed an ECG monitor using NF-IBC enhanced by SS. In this paper, we evaluated on structure of the reception electrode for reliable communication. Based on the evaluations with bit error rate, we suggested the reception electrode structure which can keep the communication reliability. As the results we considered that we can expand the reception electrode up to 2.25 m(2). Moreover, we proposed the structure of the reception electrodes that can keep the communication reliability. Finally we suggested how to use the SS NF-IBC vital-sign monitor in room that larger than 2.25 m(2), and we had shown the practicability of the systems.

An implantable neural activity monitor with nonlinear gain-controlled amplifier.

An implantable neural spike monitor with nonlinear amplifier was proposed for robust measurement against noise. In embedded electrophysiological signal processing systems, detection performance depends on signal to noise ratio (SNR), however, it is getting worth after implantation because of neoformation surrounding the electrodes and so on. We proposed a spike enhancer in this study. It has two remarkable function; automatic gain optimization with feedback loop and SNR improvement by nonlinear amplifier. In this report, the system performance was evaluated without feedback loop. A prototype circuit is prepared with small number of parts and tested on input-output characteristics. For the final evaluation, neural spike signal from somatosensory cortex of a rat was applied to the circuit. The test results show that system can expand SNR on neural spike signal from rat. It indicates that the spike enhancer can improve total performance of neural activity processing system.

Application of Near-field intra-body communication and spread spectrum technique to vital-sign monitor.

As a novel vital sign monitor, we have developed wireless ECG monitoring system with Near-field intra-body communication technique. However, communication reliability is not so high because transmission channel is noisy and unstable. In order to improve the problem, we utilize spread spectrum (SS), which is known as robust communication technique even through poor transmission channel. First of all, we evaluated characteristics of human body to SS signal. The results show that SS can be used even through human body. Based on this result, we developed and tested near-field intra-body communication device enhanced by SS. The test result shows that SS can solve the problem mentioned above.

Individual identification with high frequency ECG : preprocessing and classification by neural network.

In this research, we proposed that high frequency component of HFECG was applicable biometric feature for new identification system. We developed identification method by using neural network (NN), and aimed at the improvement of the classification rate. Preprocessing prior to NN is performed by justification on time axis and normalization on amplitude. As a result, an average of 99% classification rate was obtained from 9 subjects. We also made an attempt to identify in shorter time by shifting of the HFECG by a few samples to NN.

Influence of exposure to diesel emissions in rats and distribution profile for R-R interval.

In order to evaluate the influence of diesel emissions on cardiac function we extracted resting R-R interval and a body activity index derived on a distribution profile of R-R interval. After seven months of exposure in rats revealed that particulate matter in diesel emissions decreases resting R-R interval and activity.