Charlotte Gassor volunteered with Leeds Metropolitan University's 2011 team in India. She was organized and committed, helping to prepare materials for the team prior to departure. In India, she worked effectively with children and adults in challenging situations. When the teacher left, Charlotte kept the unruly children calm and disciplined where others had failed. Even when receiving distressing personal news, she continued with her volunteer work and the planned Christmas activities. The letter writer highly recommends Charlotte for roles involving children due to her skills, personality, and ability to engage and model for them.
Poster Presentation on "Artifact Reduction from Scalp EEG for Epilepsy Seizur...Md Kafiul Islam
This research presents a method to reduce artifacts from scalp EEG recordings to facilitate seizure diagnosis/detection for epilepsy patients. The proposed method is primarily based on stationary wavelet transform and takes the spectral band of seizure activities (i.e. 0.5 - 30 Hz) into account to separate artifacts from seizures. It requires a reference seizure epoch of N-sec which can either be generated from a patient-specific
seizure database (if available) or can be simulated by a simple mathematical model of seizure. The purpose of the algorithm is to reduce as much artifacts as possible without distorting the desired seizure events to be detected/diagnosed. Different artifact templates have been simulated to mimic the most commonly appeared artifacts in real EEG recordings. The algorithm is applied on three sets of synthesized data:
fully simulated, semi-simulated and real data to evaluate both the artifact removal performance and seizure detection performance. The EEG features responsible for detection of seizures from non-seizure epochs have been found to be easily distinguishable after artifacts are removed and consequently reduces the false alarms in seizure detection. Results from an extensive experiment with these datasets prove the efficacy of
the proposed algorithm and hence this algorithm (with some modifications) is expected to be a future candidate for artifact removal not only in epilepsy diagnosis applications but also in other applications (e.g. BCI or other neuroscience studies).
Poster Presentation on "Artifact Reduction from Scalp EEG for Epilepsy Seizur...Md Kafiul Islam
This research presents a method to reduce artifacts from scalp EEG recordings to facilitate seizure diagnosis/detection for epilepsy patients. The proposed method is primarily based on stationary wavelet transform and takes the spectral band of seizure activities (i.e. 0.5 - 30 Hz) into account to separate artifacts from seizures. It requires a reference seizure epoch of N-sec which can either be generated from a patient-specific
seizure database (if available) or can be simulated by a simple mathematical model of seizure. The purpose of the algorithm is to reduce as much artifacts as possible without distorting the desired seizure events to be detected/diagnosed. Different artifact templates have been simulated to mimic the most commonly appeared artifacts in real EEG recordings. The algorithm is applied on three sets of synthesized data:
fully simulated, semi-simulated and real data to evaluate both the artifact removal performance and seizure detection performance. The EEG features responsible for detection of seizures from non-seizure epochs have been found to be easily distinguishable after artifacts are removed and consequently reduces the false alarms in seizure detection. Results from an extensive experiment with these datasets prove the efficacy of
the proposed algorithm and hence this algorithm (with some modifications) is expected to be a future candidate for artifact removal not only in epilepsy diagnosis applications but also in other applications (e.g. BCI or other neuroscience studies).
1. 116 Bronte
Headingley Campus
LS6 3QX
30 April 2012
To whom it may concern
This is to confirm that Charlotte Gassor was a volunteer on the Leeds Metropolitan
University India Volunteering 2011 team, for which I was the team leader.
Charlotte was an outstanding volunteer full of energy, commitment and enthusiasm on a
four-week volunteering project in Ahmednagar, India, working with children and adults in
challenging situations.
When the team of 10 was asked to prepare materials prior to our departure, Charlotte was
one of the most organised and committed to the task, proactively setting up a teaching
session with an academic and preparing lesson plans which were of direct benefit to the
whole team. She also contributed to team fundraising activities and collected donated
materials to take to the projects.
Left unsupervised with a classroom of unruly children, when their teacher had to
accompany an injured student to hospital, Charlotte remained and kept the pupils calm and
disciplined where other volunteers had failed.
Charlotte also stands out for the way she dealt with distressing news on Christmas Eve of a
bereavement at home. Although obviously upset she refused the offer to return home early
and threw herself back into the planned Christmas activities with the children.
I would highly recommend Charlotte for any role involving working with children and young
adults as she has proven she has the skills, personality and energy to engage them in
activities, is a great role model and is a pleasure to work alongside.
Yours sincerely
Joyce Connolly
PR Officer & Leeds Met India Volunteering 2011 Team Leader