Noritaka Mamorita

Model of bidirectional modulated parasystole as a mechanism for cyclic bursts of ventricular premature contractions

Abstract.Cyclic bursts of ventricular premature contractions (VPC) coming at minute-order intervals have been discerned by analyzing ambulatory ECG recordings, and their mechanism has not been clarified. The present study simulates this phenomenon by constructing a bidirectional modulated parasystole model. With Ts and Te as the intrinsic periods of the sinus and ectopic pacemakers, there are distinct and initial condition-dependent solutions in the model with Ts/Te values close to 1, 1/2, 1/4, etc. Typically, two distinct stable solutions are found existing together around Ts/Te = 1/2. We have verified theoretically the coexistence of different solutions and their dependence on the model parameters. The solution presented switches between those by a premature stimulus and those by fluctuations in the model parameters such as Ts. Patterns of RR intervals were generated by simulation with randomly fluctuating Ts. They included cyclic bursts of bigeminy of the “flat type” and the “dome type” reported by Takayanagi et al. (1999) and other transient types with Wenckebach or reverse Wenckebach rhythm of coupling intervals. This model provides a mathematical representation of the atrioventricular feedback mechanism and enables the modulated parasystole hypothesis to be applied to wider classes of VPCs.

Development of a comprehensive medical recorder on a cellphone

Paper medical diaries have effectively been used in chronic diseases for self-management without information and communication technology for many cases. To facilitate self-control in chronic diseases, and observe ones own condition objectively and continuously, we developed a cellphone-based medical recorder (MedData) for patients with chronic diseases. The MedData is based on the Java2 Micro Edition and DoJa-3.5 (NTT DoCoMo, Inc.), and it runs like a scheduler with a calendar, diary, and data entry canvas. The MedData stores laboratory data, such as blood pressure, BUN (blood urea nitrogen), creatinine, Hb A1c (glycosylated hemoglobin), and other pertinent comments, into a cellphone memory. Detailed graphic displays of the data are automatically visualized. The MedData can customize recording events, items, prescriptions, and graphics all on the cellphone. These can then be transferred via an infrared port between a cellphone and a PC.

Two types of distribution patterns of bigeminy and trigeminy in long-term ECG: a model-based interpretation

Two types of distribution patterns of bigeminy and trigeminy are found in analysis of long-term ECG. To investigate the mechanism underlying this finding, a simplified equation of a modulated parasystole model was used and symbolic solutions for cyclic VPC patterns were obtained. The map of these solutions in a model parameter plane showed two different solutions for bigeminy, four kinds of trigeminy, two kinds of quadrigeminy, combinations of these patterns, and apparently normal ECG. These results are used to explain the features of the distribution patterns.

Development of an Alarm Sound Database and Simulator

Objectives. The purpose of this study was to develop an interactive software package of alarm sounds to present, recognize and share problems about alarm sounds among medical staff and medical manufactures. Methods. The alarm sounds were recorded in variable alarm conditions in a WAV file. The alarm conditions were arbitrarily induced by modifying attachments of various medical devices. The software package that integrated an alarm sound database and simulator was used to assess the ability to identify the monitor that sounded the alarm for the medical staff. Results. Eighty alarm sound files (40MB in total) were recorded from 41 medical devices made by 28 companies. There were three pairs of similar alarm sounds that could not easily be distinguished, two alarm sounds which had a different priority, either low or high. The alarm sound database was created in an Excel file (ASDB.xls 170 kB, 40 MB with photos), and included a list of file names that were hyperlinked to alarm sound files. An alarm sound simulator (AlmSS) was constructed with two modules for simultaneously playing alarm sound files and for designing new alarm sounds. The AlmSS was used in the assessing procedure to determine whether 19 clinical engineers could identify 13 alarm sounds only by their distinctive sounds. They were asked to choose from a list of devices and to rate the priority of each alarm. The overall correct identification rate of the alarm sounds was 48%, and six characteristic alarm sounds were correctly recognized by beetween 63% to 100% of the subjects. The overall recognition rate of the alarm sound priority was only 27%. Conclusions. We have developed an interactive software package of alarm sounds by integrating the database and the alarm sound simulator (URL: http://info.ahs.kitasato-u.ac.jp/tkweb/alarm/asdb.html). The AlmSS was useful for replaying multiple alarm sounds simultaneously and designing new alarm sounds interactively.

Estimation of the upper limit of the reference value of the QT interval in rest electrocardiograms in healthy young Japanese men using the bootstrap method.

BACKGROUND A prolonged QT interval (QT) is associated with cardiac arrhythmia, and methods for identification of QT prolongation are required. METHODS The relationship between RR and QT was investigated in resting electrocardiograms of 1276 healthy young Japanese men using the bootstrap method. RESULTS The upper limit of QT (QT(upper limit)) was approximated well by the exponential equation: QT(upper limit) = 435 x RR(0.3409). We also defined an alternative upper limit of QTc(G upper limit) = 435 milliseconds, where QTc(G) was calculated by dividing QT by RR(0.3409). Thirty-two (2.51%) of the 1276 cases exceeded the criterion and were diagnosed as cases of QT prolongation. CONCLUSION Using this limit, we propose a criterion to discriminate cases with prolonged QT intervals. The accuracy of the estimation of the mean and the upper limit of the reference value of the QT was good within the range of the RR interval from 0.812 to 1.263 s (heart rates from 48 to 74 beats per minute). Our approach for estimation of the exponent of RR differs from the well-known exponential equations proposed by Fridericia, but the exponent of RR in our equation is very close to that of Fridericia.

Trial of real-time locating and messaging system with Bluetooth low energy

BACKGROUND Hospital real-time location systems (RTLS) are increasing efficiency and reducing operational costs, but room access tags are necessary. OBJECTVE We developed three iPhone 5 applications for an RTLS and communications using Bluetooth low energy (BLE). METHODS The applications were: Peripheral device tags, Central beacons, and a Monitor. A Peripheral communicated with a Central using BLE. The Central communicated with a Monitor using sockets on TCP/IP (Transmission Control Protocol/Internet Protocol) via a WLAN (wireless local area network). To determine a BLE threshold level for the received signal strength indicator (RSSI), relationships between signal strength and distance were measured in our laboratory and on the terrace. RESULTS The BLE RSSI threshold was set at -70 dB, about 10 m. While an individual with a Peripheral moved around in a concrete building, the Peripheral was captured in a few 10-sec units at about 10 m from a Central. The Central and Monitor showed and saved the approach events, location, and Peripherals nickname sequentially in real time. Remote Centrals also interactively communicate with Peripherals by intermediating through Monitors that found the nickname in the event database. CONCLUSIONS Trial applications using BLE on iPhones worked well for patient tracking, and messaging in indoor environments.

Development of a Smartphone App for Visualizing Heart Sounds and Murmurs

Background: Auscultation is one of the basic techniques for the diagnosis of heart disease. However, the interpretation of heart sounds and murmurs is a highly subjective and difficult skill. Objectives: To assist the auscultation skill at the bedside, a handy phonocardiogram was developed using a smartphone (Samsung Galaxy J, Android OS 4.4.2) and an external microphone attached to a stethoscope. Methods and Results: The Android app used Java classes, “AudioRecord,” “AudioTrack,” and “View,” that recorded sounds, replayed sounds, and plotted sound waves, respectively. Sound waves were visualized in real-time, simultaneously replayed on the smartphone, and saved to WAV files. To confirm the availability of the app, 26 kinds of heart sounds and murmurs sounded on a human patient simulator were recorded using three different methods: a bell-type stethoscope, a diaphragm-type stethoscope, and a direct external microphone without a stethoscope. The recorded waveforms were subjectively confirmed and were found to be similar to the reference waveforms. Conclusions: The real-time visualization of the sound waves on the smartphone may help novices to readily recognize and learn to distinguish the various heart sounds and murmurs in real-time.

Simulation system of arrhythmia and HRV analyzer

We aim to integrate our interactive simulation systems of arrhythmia and heart rate variability (HRV) analyzer by a Windows message to understand the theoretical mechanisms of arrhythmia and HRV. The arrhythmia simulator (250 kB, Visual Basic 6.0) was composed of 4 normal and 2 ectopic foci. The electrical activity of each cell was modeled by the conduction speed and the phase response curve. The ECG waves were graphically plotted with impulse conduction on a ladder diagram. An RR interval was sequentially messaged to the HRV analyzer (90 kB, Visual Basic 6.0), which automatically calculated power spectrum (PS) of HRV by Lombs method and FFT. The power of VLF, LF and HF bands, mean, SD and range were listed. The HRV analyzer interactively showed the variation of PS influenced by a baseline trend of RR intervals, ectopic beats, sampling rate, the number of samples and window function