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Full-Text Articles in Biomedical Engineering and Bioengineering

Multimodal Wearable Sensors For Human-Machine Interfaces, Mark Nolan Aug 2013

Multimodal Wearable Sensors For Human-Machine Interfaces, Mark Nolan

Doctoral

Certain areas of the body, such as the hands, eyes and organs of speech production, provide high-bandwidth information channels from the conscious mind to the outside world. The objective of this research was to develop an innovative wearable sensor device that records signals from these areas more conveniently than has previously been possible, so that they can be harnessed for communication. A novel bioelectrical and biomechanical sensing device, the wearable endogenous biosignal sensor (WEBS), was developed and tested in various communication and clinical measurement applications.

One ground-breaking feature of the WEBS system is that it digitises biopotentials almost at the ...


Footwear-Centric Body Area Network With Directional Uwb Antenna, Domenico Gaetano, Vit Sipal, Patrick Mcevoy, Max Ammann, C Brannigan, Louise Keating, Frances Horgan Jul 2013

Footwear-Centric Body Area Network With Directional Uwb Antenna, Domenico Gaetano, Vit Sipal, Patrick Mcevoy, Max Ammann, C Brannigan, Louise Keating, Frances Horgan

Articles

A footwear-centric body area network employing a directional antenna is compared with waist-centric systems using omnidirectional and directional antennas. The impact of body movements on path gain is analysed for two bands at 3.99 GHz and 7.99 GHz. The path gain and data rate results demonstrate that footwear-centric configurations are equivalent or better than waist-centric body area networks.


Comparison Of Non-Coherent Linear Breast Cancer Detection Algorithms Applied To A 2-D Numerical Breast Model, Giuseppe Ruvio, Raffaele Solimene, Antonio Cuccaro, Max Ammann Jan 2013

Comparison Of Non-Coherent Linear Breast Cancer Detection Algorithms Applied To A 2-D Numerical Breast Model, Giuseppe Ruvio, Raffaele Solimene, Antonio Cuccaro, Max Ammann

Articles

A comparative analysis of an imaging method based on a multi-frequency Multiple Signal Classification (MUSIC) approach against two common linear detection algorithms based on non-coherent migration is made. The different techniques are tested using synthetic data generated through CST Microwave Studio and a phantom developed from MRI scans of a mostly fat breast. The multi-frequency MUSIC approach shows an overall superior performance compared to the non-coherent techniques. This paper reports that this highly performing algorithm does not require any antenna calibration or phase response estimation and allows the use of efficient and complex antenna geometries without difficult algorithm redefinitions.