Patrick Gaydecki BSc, PhD, FIET, SMIEEE,
MInstP, MInstNDT, CPhys, CEng
Professor of Digital Signal Processing
|
Email: |
|
|
Telephone: |
[UK-44] (0) 161 306 4906 |
|
|
07980 751417 |
|
Address: |
Sensing, Imaging and Signal Processing Group School of Electrical and Electronic Engineering United Kingdom |
Patrick Gaydecki’s research team presently comprises 5
research associates, 2 MPhil students, 6 PhD students and 2 Academic Visitors.
Over the last ten years, the team’s research projects have involved the
development of instrumentation and software for nondestructive testing of
materials using a variety of sensing modalities, the development of systems and
software for the analysis of cardiovascular and autonomic function, and the
design and development of real-time digital signal processing hardware for
audio bandwidth applications. The research initiatives are listed in more
detail below.
·
Signal Wizard
2.5. Design and development of a real-time digital signal
processing system (circuit board, firmware operating system and high-level
software) for audio-bandwidth signal processing. Essentially, it is a very
flexible linear systems emulator, that can be used to design standard or
entirely arbitrary filters and execute them in real-time. This includes FIR,
IIR and adaptive types. It is called the Signal Wizard. It has been used at the
University of Cambridge in a joint research initiative to replicate with high
fidelity the sound of acoustic violins through digital technology. Signal
Wizard 2.5 is now available as a commercial product, and is distributed by
Saelig Inc. Click
here for more information on the background.
·
Signal Wizard
3. A multi-channel audio DSP system, incorporating 6
analogue inputs, 8 analogue outputs, digital (S/PDIF) in/out audio, USB, JTAG and
parallel support. The DSP core operates at 0.55 GMACC. Click here for more information on the background.
·
Vsound, a new generation of real-time
digital signal processing system for violinists. The system produces an
acoustic-violin sound when fed with the input from an electric or silent
violin.
·
Biomedical systems and software for
intelligent clothing, including ECG, respiration, incontinence, temperature and
other parameters.
·
Analysis and interpretation of EEG
signals in preterm neonates.
·
Intravenous needle guidance systems.
·
Software for cough analysis
·
Software and instrumentation for the
automated analysis of cardiovascular and autonomic function in the study of
vasovagal syncope.
·
Signal processing algorithms for the
automatic recognition and classification of atrial fibrillation events in ECG
data.
·
Hardware and software systems for
monitoring acceleration levels experienced by preterm neonates during emergency
transportation.
·
Image processing software for the
automatic recognition of biological tissue types based on texture histogram and
Fourier spectrum correlation techniques.
·
Software based on the wavelet transform
for the automatic classification and segmentation of ECG waveforms for clinical
analysis and matching.
·
Inductive scan imaging systems for the
visualisation of steel reinforcing bars and cables embedded within pre-stressed
and reinforced concrete. These systems generate images of the steel by
exploiting eddy current generation and detection when a time-varying magnetic
field is impressed on the material through the use of a resonant transmitter
coil. Extensive image processing software development is required to improve
the spatial and axial resolution of the raw images.
·
Real-time magnetic field camera imaging
systems.
·
Inductive imaging systems for detection
of faults in pre-stressing wire of large bore water pipes.
·
Intelligent, autonomous sensors for
monitoring fatigue damage of welded steel components (CrackFirst).
·
Remote, autonomous ultrasonic sensors
for monitoring flood conditions in the reinforcing cross-beams of oil rigs.
·
Ultrasonic systems for detection and
imaging of fault conditions in pre-stressed and reinforced concrete, including
visualization of steel embedments and voids. These systems have exploited the
analysis of the frequency content of the returned echoes for fault
identification, or the Synthetic Aperture Focusing Technique (SAFT) applied to
signals received from multiple transducers to generate 3D images of the
internal concrete matrix.
·
Instrumentation for fault detection in
pre-stressing cables exploiting the principle of electrical time domain
reflectometry.
Downloads
Last
updated: April 2009