Delaunay triangulation based image enhancement for echocardiography images

A novel image enhancement approach for automatic echocardiography image processing is proposed. The main steps include undecimated wavelet based speckle noise reduction, edge detection, followed by a regional enhancement process that employs Delaunay triangulation based thresholding. The edge detection is performed using a fuzzy logic based center point detection and a subsequent radial search based fuzzy multiscale edge detection. The edges obtained are used as the vertices for Delaunay triangulation for enhancement purposes. This method enhances the heart wall region in the echo image. This technique is applied to both synthetic and real image sets that were obtained from a local hospital

EEuGene: employing electroencephalograph signals in the rating strategy of a hardware-based interactive genetic algorithm

We describe a novel interface and development platform for an interactive Genetic Algorithm (iGA) that uses Electroencephalograph (EEG) signals as an indication of fitness for selection for successive generations. A gaming headset was used to generate EEG readings corresponding to attention and meditation states from a single electrode. These were communicated via Bluetooth to an embedded iGA implemented on the Arduino platform. The readings were taken to measure subjects’ responses to predetermined short sequences of synthesised sound, although the technique could be applied any appropriate problem domain. The prototype provided sufficient evidence to indicate that use of the technology in this context is viable. However, the approach taken was limited by the technical characteristics of the equipment used and only provides proof of concept at this stage. We discuss some of the limitations of using biofeedback systems and suggest possible improvements that might be made with more sophisticated EEG sensors and other biofeedback mechanisms

Does feedback on daily activity level from a Smart watch during in-patient stroke rehabilitation increase physical activity levels? Study protocol for a randomized controlled trial

Background. Practicing activities improves recovery after stroke, but many people in hospital do little activity. Feedback on activity using an accelerometer is a potential method to increase activities in hospital inpatients. This study’s goal is to investigate the effect of feedback, enabled by a Smart watch, on daily physical activity levels during inpatient stroke rehabilitation and the short-term effects on simple functional activities, primarily mobility. Methods/design. A randomized controlled trial will be undertaken within the stroke rehabilitation wards of the 2nd affiliated hospital of Anhui University of Traditional Chinese Medicine, Hefei, China. The study participants will be stroke survivors who meet inclusion criteria for the study, primarily: able to participate, no more than four months after stroke, and walking independently before stroke. Participants will all receive standard local rehabilitation and will be randomly assigned either to receive regular feedback about activity levels, relative to a daily goal tailored by the smart watch over five time periods throughout a working day, or to no feedback, but still wearing the Smart watch. The intervention will last up to three weeks, ending sooner if discharged. The data to be collected in all participants includes measures of: daily activity (Smart watch measure); mobility (Rivermead Mobility Index and ten metre walking time); independence in personal care (the Barthel ADL index); overall activities (the WHO Disability Assessment Scale, 12-item version); and quality of life (the Euro-Qol 5L5D). Data will be collected by masked assessors at baseline, three weeks or at discharge (whichever is the sooner); and a reduced data set at 12 weeks by telephone interview. The primary outcome will be change in daily accelerometer activity scores. Secondary outcomes are compliance and adherence to wearing the watch, and changes in mobility, independence in personal care activities, and health-related quality of life. Discussion. This project is being implemented in a large city hospital with limited resources and limited research experience. There has been a pilot feasibility study using the Smart Watch, which highlighted some areas needing change and these are incorporated in this protocol

Myocardial ischemia detection algorithm (MIDA) for automated diagnosis of heart wall damage and abnormal wall motion

This article discusses myocardial ischemia detection algorithm (MIDA) for automated diagnosis of heart wall damage and abnormal wall motion