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