High frequency region of the snore spectra carry important information on the disease of sleep apnoea.

Snoring is the most common symptom of obstructive sleep apnoea (OSA). Several researchers have reported differences between the power spectra of non-OSA and OSA snorers. The traditional approach over the years has been to record snore sounds at a bandwidth of < 5 kHz. Narrowing of the upper airways during OSA events and the resulting upward shift of snore frequencies also lend support to the idea of examining snore sounds beyond 5 kHz. In this paper, we compute the power spectra of snores in three different bands defined as: low-frequency band (LFB: < 5 kHz); middle-frequency band (MFB: 5-10 kHz) and high-frequency band (HFB: 10-20 kHz). We illustrate that there is a significant difference between non-OSA snorers (Apnoea Hypopnoea Index (AHI) < 10) and OSA snorers (AHI > 10) in the region > 5 kHz. We then develop a feature to diagnose OSA based on the spectral differences in the high frequency region and evaluate its performance on a database of 20 subjects. Our results strongly suggest that the high-frequency region of the snore sounds carry information, hitherto disregarded, on the disease of sleep apnoea.

Feature extraction for snore sound via neural network processing.

Snore sound (SS) is the earliest and the most common symptom of Obstructive Sleep Apnea (OSA) which is a serious disease caused by the collapse of upper airways during sleep. SS should carry vital information on the state of the upper airways and is simple to acquire and rich in features but their analysis is complicated. In this study we use neural network (NN) based method to model SS via a simple second order one-step predictor. We show that the some hidden information/feature of a SS can be conveniently captured in the connection-weight-space (CWS) of the NN, after a process of supervised training. The availability of the proposed method is investigated by performing independent component analysis (ICA) on CWS.

New water disinfection system using UVA light-emitting diodes.

AIM: To evaluate the ability of high-energy ultraviolet A (UVA) light-emitting diode (LED) to inactivate bacteria in water and investigate the inactivating mechanism of UVA irradiation. METHODS AND RESULTS: We developed a new disinfection device equipped with high-energy UVA-LED. Inactivation of bacteria was determined by colony-forming assay. Vibrio parahaemolyticus, enteropathogenic Escherichia coli, Staphylococcus aureus and Escherichia coli DH5alpha were reduced by greater than 5-log(10) stages within 75 min at 315 J cm(-2) of UVA. Salmonella enteritidis was reduced greater than 4-log(10) stages within 160 min at 672 J cm(-2) of UVA. The formation of 8-hydroxy-2'-deoxyguanosine in UVA-LED irradiated bacteria was 2.6-fold higher than that of UVC-irradiated bacteria at the same inactivation level. Addition of mannitol, a scavenger of hydroxyl radicals (OH(*)), or catalase, an enzyme scavenging hydrogen peroxide (H(2)O(2)) to bacterial suspensions significantly suppressed disinfection effect of UVA-LED. CONCLUSION: This disinfection system has enough ability to inactivate bacteria and OH(*) and H(2)O(2) participates in the disinfection mechanism of UVA irradiation. SIGNIFICANCE AND IMPACT OF THE STUDY: We newly developed UVA irradiation system and found that UVA alone was able to disinfect the water efficiently. This will become a useful disinfection system.

Tracking the states of a nonlinear and nonstationary system in the weight-space of artificial neural networks.

We propose a novel interpretation and usage of Neural Network (NN) in modeling physiological signals, which are allowed to be nonlinear and/or nonstationary. The method consists of training a NN for the k-step prediction of a physiological signal, and then examining the connection-weight-space (CWS) of the NN to extract information about the signal generator mechanism. We define a novel feature, Normalized Vector Separation (gamma(ij)), to measure the separation of two arbitrary states "i" and "j" in the CWS and use it to track the state changes of the generating system. The performance of the method is examined via synthetic signals and clinical EEG. Synthetic data indicates that gamma(ij) can track the system down to a SNR of 3.5 dB. Clinical data obtained from three patients undergoing carotid endarterectomy of the brain showed that EEG could be modeled (within a root-means-squared-error of 0.01) by the proposed method, and the blood perfusion state of the brain could be monitored via gamma(ij), with small NNs having no more than 21 connection weight altogether.

Systematic identification for inert region of a brain from EEG.

Evaluation of biomedical signals is important in the diagnosis of neurology diseases, such as dementia, in neurology through the use of electroencephalograms (EEG). While automated techniques exist for EEG analysis, it is likely that additional information can be extracted from EEG signal through the use of new methods. We describe a method for identifying inert region from EEG. This method uses EEG as input to an artificial neural network with five outputs: activity in whole regoin and inert region separated by four regions.

Recognition mechanism of a neural network for character recognition.

We have developed a small scale four-layered neural network (NN) model for simple character recognition, which can recognize the patterns transformed by affine conversion. In this study 24 patterns are presented as input patterns. An input pattern is divided into 64 local patterns and connected with the 1st hidden layer. After the training, we investigated the recognition mechanism of NN using Alopex algorithm. Effectiveness of this method is demonstrated.

The Development of a Remote Patient Monitoring System using Java-enabled Mobile Phones.

A remote patient monitoring system is described. This system is to monitor information of multiple patients in ICU/CCU via 3G mobile phones. Conventionally, various patient information, such as vital signs, is collected and stored on patient information systems. In proposed system, the patient information is recollected by remote information server, and transported to mobile phones. The server is worked as a gateway between hospital intranet and public networks. Provided information from the server consists of graphs and text data. Doctors can browse patient's information on their mobile phones via the server. A custom Java application software is used to browse these data. In this study, the information server and Java application are developed, and communication between the server and mobile phone in model environment is confirmed. To apply this system to practical products of patient information systems is future work.

Studies on internal structure of tablets. VI. stress dispersion in tablets by excipients.

The aim of this study was to reduce the stress concentration of a medicine by dispersing the stress in tablets at tableting by addition of excipients. The mechanism of the stress dispersion was elucidated. Phenacetin (PHE) was used as a model of crystalline medicine with a high brittleness, and the degree of stress dispersion was evaluated by the change in the exposed surface area of PHE. To learn the mechanical strength of tablets, the crushing strength and friability were measured, their internal structure was analyzed by the porosity and pore size distribution, and stress relaxation experiments were performed. The results were as follows. Calcium silicate (Florite RE, FLR) showed a high stress dispersion effect, adding a high formability and mechanical strength to tablets. It was thought that the high stress dispersion resulted from the rapid stress relaxation caused by the plastic deformation and brittleness fracture of pores in FLR under a low compression pressure. Thus the stress caused locally on PHE particles may disperse.

Physical constitution and smoking habits of patients with idiopathic spontaneous pneumothorax.

This is a report on a statistical study comparing the Kaup index and the level of tobacco consumption of patients with idiopathic spontaneous pneumothorax and those of healthy subjects. A statistically significant difference was found between the average Kaup index of the patients with idiopathic spontaneous pneumothorax and that of normal healthy individuals in Japan as published by the Ministry of Health and Welfare. A statistically significant difference was also found in the physical features between 2,433 males with idiopathic pneumothorax and 1,906 healthy males when compared by means of the Kaup index. Again, a statistically significant difference was noted in the level of tobacco consumption between the males with idiopathic pneumothorax and normal males when compared by means of the Brinkmann index. The Kaup index of idiopathic pneumothorax patients was lower than that of healthy subjects, while the level of tobacco consumption of the former was higher. Idiopathic spontaneous pneumothorax is related to thin and tall individuals and the level of tobacco consumption among such patients is higher than among healthy subjects.

Effects of flurazepam and diazepam in isolated guinea-pig taenia coli and longitudinal muscle.

The effects of the benzodiazepine derivatives flurazepam and diazepam on K+- and Ca2+ -induced contracture were examined in isolated taenia coli and longitudinal muscle of the guinea-pig. Flurazepam and diazepam inhibited the tonic component more than the phasic component of the K+ -induced contracture of taenia coli. In longitudinal muscle, both flurazepam and diazepam inhibited the Ca2+ -induced contracture dose-dependently. These findings suggest that the observed effects of flurazepam and diazepam may have been due to inhibition of the transmembrane influx of Ca2+.