Matthew W. Flood

Matthew W. Flood
LIH Luxembourg Institute of Health | CRP Santé · Human Motion, Orthopaedics, Sports Medicine and Digital Methods

Doctor of Engineering

About

13
Publications
1,462
Reads
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114
Citations
Citations since 2017
13 Research Items
114 Citations
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Education
September 2014 - April 2019
University College Dublin
Field of study
  • Electrical & Electronic Engineering
September 2012 - May 2014
University College Dublin
Field of study
  • Biomedical Engineering

Publications

Publications (13)
Article
Objectives: To investigate differences in surface electromyography (EMG) features in individuals with idiopathic Parkinson’s disease (PD) and aged-matched controls. Methods: Surface EMG was recorded during isometric leg extension in PD patients prior to, and after undergoing a locomotor training programme, and in aged-matched controls. Differenc...
Article
Objective: A novel method based on the application of the Teager-Kaiser Energy Operator is presented to estimate instances of initial contact (IC) and final contact (FC) from accelerometry during gait. The performance of the proposed method was evaluated against four existing gait event detection (GED) methods under three walking conditions design...
Article
Full-text available
Motor unit (MU) firing times are weakly coupled across a range of frequencies during voluntary contractions. Coherent activity within the beta-band (15-35 Hz) has been linked to oscillatory cortical processes, providing evidence of functional connectivity between the motoneuron pool and motor cortex. The aim of this study was to investigate whether...
Article
Full-text available
Background: LSVT-BIG® is an intensively delivered, amplitude-oriented exercise therapy reported to improve mobility in individuals with Parkinson's disease (PD). However, questions remain surrounding the efficacy of LSVT-BIG® when compared with similar exercise therapies. Instrumented clinical tests using body-worn sensors can provide a means to o...
Article
Full-text available
An increasing number of studies across many research fields from biomedical engineering to finance are employing measures of entropy to quantify the regularity, variability or randomness of time series and image data. Entropy, as it relates to information theory and dynamical systems theory, can be estimated in many ways, with newly developed metho...
Article
Background Monitoring systems have been developed during the COVID-19 pandemic enabling clinicians to remotely monitor physiological measures including pulse oxygen saturation (SpO2), heart rate (HR), and breathlessness in patients after discharge from hospital. These data may be leveraged to understand how symptoms vary over time in COVID-19 patie...
Article
Observations from laboratory-based gait analysis are difficult to extrapolate to real-world environments where gait behavior is modulated in response to complex environmental conditions and surface profiles. Inertial measurement units (IMUs) permit real-world gait analysis; however, automatic detection of surfaces encountered remains largely unexpl...
Preprint
Full-text available
Background The level of assistance provided to the user is an important decision in rehabilitation training using robotic devices. Both fully assistive and assist-as-needed paradigms have shown benefits in functional outcomes in healthy individuals and users with chronic stroke and spinal cord injury. The effect of assistance level on muscle activi...
Article
Gas leakage during minimally invasive surgery is an aerosolization hazard. Sensitive optical and thermographic imaging can demonstrate and differentiate between mechanistic categories, enabling engineering solutions to fortify surgical care against pollutants and pathogens affecting operating room teams.
Article
Recent advances in wearable sensors enable recording of electromyography (EMG) outside the laboratory for extended periods of time. However, the properties of wearable EMG systems designed for long-term recording may differ from those of laboratory-standard systems, potentially impacting data. This study evaluated EMG features derived from signals...
Conference Paper
Nonlinear features extracted from surface EMG signals have been previously used to infer information on coherent or synchronous activity in the underlying motor unit discharges. However, it has not yet been assessed how these features are affected by the density of the surface EMG signal, and whether changes in the level of muscle activation can in...
Conference Paper
The Teager-Kaiser energy operator (TKEO), when applied to a signal gives an estimation of the instantaneous energy of that signal. It, therefore, accentuates both frequency and amplitude changes in a signal. To date, it has been primarily used in communications systems and most popularly in electromyographic signal analysis to detect bursts of musc...

Questions

Question (1)
Question
I am currently trying to employ measures of fractal dimension to analyse EEG data. In particular, the methods proposed by Higuchi, Maragos & Sun, Petrosian, as well as the box-counting dimension.
In one way or another, each method calculates the fractal dimension from the slope of a double logarithmic plot, where the abscissa is given as Ln(1/k) - where k represents a scaling parameter.
However, there appears to be no guidance provided in the literature that suggests which value of k, or how many k points should be used to accurately calculate the FD. 
I appreciate that the choice of the scaling parameter k is specific to each fractal dimension. 
Any advice on how to define the scaling parameter region, either on a global level or for one of the individual fractal measures mention above, would be greatly appreciated.
Thank you in advance,
Matt.

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