In this paper is described the design and implementation of a wireless atrial fibrillation monitoring system, for realtime remote patient monitoring in a limited area, using wireless sensor networks (WSN). The proposed system consists of a lightweight and low power wireless ECG acquisition and processing device, connected to a central monitoring station through WSN. The device is able to detect the paroxysmal atrial fibrillation episodes and transmits alerts to the central monitoring station. The system can be used for long-time continuous monitoring of patients suspected to have atrial fibrillation, as part of a diagnostic procedure, or recovery from an acute or surgical event. In order to detect the atrial fibrillation episodes we used a simple method based on RR intervals, extracted from ECG signal. We evaluated the performance of the method on MIT-BIH Atrial Fibrilation Database from Physionet. The central monitoring station runs a patient monitor application that receives the real time heart rate and atrial fibrillation alerts from WSN. A user-friendly Graphical User Interface was developed for the patient monitor application to display the heart rate and alerts coming from the monitored patient. A prototype of the system has been developed, implemented and tested.

In this paper, the development of an eye-tracking-based human–computer interface for real-time applications is presented. To identify the most appropriate pupil detection algorithm for the proposed interface, we analyzed the performance of eight algorithms, six of which we developed based on the most representative pupil center detection techniques. The accuracy of each algorithm was evaluated for different eye images from four representative databases and for video eye images using a new testing protocol for a scene image. For all video recordings, we determined the detection rate within a circular target 50-pixel area placed in different positions in the scene image, cursor controllability and stability on the user screen, and running time. The experimental results for a set of 30 subjects show a detection rate over 84% at 50 pixels for all proposed algorithms, and the best result (91.39%) was obtained with the circular Hough transform approach. Finally, this algorithm was implemented in the proposed interface to develop an eye typing application based on a virtual keyboard. The mean typing speed of the subjects who tested the system was higher than 20 characters per minute.

Wirelessly enabling Medical Devices such as Vital Signs Monitors, Ventilators and Infusion Pumps allows central data collection. This paper discusses how data from these types of devices can be integrated into hospital systems using wireless sensor networking technology. By integrating devices you are protecting investment and opening up the possibility of networking with similar devices. In this context we present how Zigbee meets our requirements for bandwidth, power, security and mobility. We have examined the data throughputs for various medical devices, the requirement of data frequency, security of patient data and the logistics of moving patients while connected to devices. The paper describes a new tested architecture that allows this data to be seamlessly integrated into a User Interface or Healthcare Information System (HIS). The design supports the dynamic addition of new medical devices to the system that were previously unsupported by the system. To achieve this, the hardware design is kept generic and the software interface for different types of medical devices is well defined. These devices can also share the wireless resources with other types of sensors being developed in conjunction on this project such as wireless ECG (Electrocardiogram) and Pulse-Oximetry sensors.

The aim of our study was to evaluate the thermal index (TI) and mechanical index (MI), during the assessment of the fetal heart at the time of first-trimester scan, with different ultrasound machines. This was part of an observational study conducted in patients undergoing routine first-trimester screening. Cases were examined with Voluson E8 or 730Pro scanners using 2–8 MHz transabdominal probes. TI and MI were retrieved from the saved displays while in gray mode, color flow mapping and pulsed-wave (PW) Doppler examinations of the fetal heart and also from the ductus venosus (DV) assessment. We evaluated 552 fetal cardiac examinations, 303 (55%) performed with Voluson E8 and 249 (45%) with Voluson 730Pro ultrasound machines. The gray-scale exam of the heart and the PW Doppler DV assessment had TI values significantly lower for the Voluson E8 group (median, 0.04 vs. 0.2 and 0.1 vs. 0.2, respectively). The MI values from gray-scale and color flow mapping of the heart were significantly lower (median, 0.6 vs, 1.2 and 0.7 vs. 1) and for PW Doppler exam of the tricuspid flow were significantly higher (median 0.4 vs. 0.2) in the Voluson E8 group. The TI values from Doppler examinations of the heart, either color flow or PW imaging and MI values from DV assessment were not significantly different between the two groups. A different (newer) generation of ultrasound equipment provides lower or at least the same safety indices for most of the first-trimester heart examinations.

No abstract