16 research outputs found
Neonatal EEG graded for severity of background abnormalities in hypoxic-ischaemic encephalopathy
This report describes a set of neonatal electroencephalogram (EEG) recordings
graded according to the severity of abnormalities in the background pattern.
The dataset consists of 169 hours of multichannel EEG from 53 neonates recorded
in a neonatal intensive care unit. All neonates received a diagnosis of
hypoxic-ischaemic encephalopathy (HIE), the most common cause of brain injury
in full term infants. For each neonate, multiple 1-hour epochs of good quality
EEG were selected and then graded for background abnormalities. The grading
system assesses EEG attributes such as amplitude and frequency, continuity,
sleep--wake cycling, symmetry and synchrony, and abnormal waveforms. Background
severity was then categorised into 4 grades: normal or mildly abnormal EEG,
moderately abnormal EEG, severely abnormal EEG, and inactive EEG. The data can
be used as a reference set of multi-channel EEG for neonates with HIE, for EEG
training purposes, or for developing and evaluating automated grading
algorithms
EMG wrist-hand motion recognition system for real-time Embedded platform
Electromyography (EMG) signal analysis is a popular method for controlling
prosthetic and gesture control equipment. For portable systems, such as
prosthetic limbs, real-time low-power operation on embedded processors is
critical, but to date, there has been no record of how existing EMG analysis
approaches support such deployments. This paper presents a novel approach to
time-domain classification of multi-channel EMG signals harnessed from
randomly-placed sensors according to the wrist-hand movements which caused
their occurrence. It shows how, by employing a very small set of time-domain
features, Kernel Fisher discriminant feature projection and Radial Bias
Function neural network classifiers, nine wrist-hand movements can be detected
with accuracy exceeding 99% - surpassing the state-of-the-art on record. It
also shows how, when deployed on ARM Cortex-A53, the processing time is not
only sufficient to enable real-time processing but is also a factor 50 shorter
than the leading time-frequency techniques on record.Comment: 5 pages, to appear in upcoming IEEE ICASSP 2019 (Paper: 1810,
Session: DISPS-P2: Algorithm and Architecture Optimization, Topic: Design and
Implementation of Signal Processing Systems / Low-power signal processing
techniques and architectures
Unilateral pathology associated with bilateral etiologies
Hormonal fluctutaions affect not only a woman's reproductive system but surprisingly they have a strong influence on the oral cavity also. These changes are not necessarily the result of direct hormonal action on the tissue, but are perhaps best explained as the effects of the local factors (e.g. plaque on tissues exacerbated by hormonal activity). One such case of pubertal induced gingival enlargement associated with chronic generalized periodontitis caused by the combined influence of hormones and the habit of unilateral mastication is presented here. A 14-year-old girl reported with a complaint of swollen gums in the right maxillary and mandibular arches of the mouth since 2 years. The patient also had the habit of unilateral mastication (left side) since childhood which was revealed upon history. Amelioration of the gingival inflammation and the periodontal attachment loss was obtained through conventional periodontal therapy, including plaque control, scaling, root planing, and surgical removal of the soft tissue using Modified Widman Flap and bone grafting. Postoperative follow-up did not show any signs of recurrence. Pubertal induced gingival enlargement with unilateral masticatory habit needs early removal of enlargement to prevent further bone loss