Towards a neonatal brain stethoscope: a framework for quantifying the accuracy of subjective and objective detection of neonatal brain injuries, and integration of a bluetooth communication system

Increasing and quantifying the accuracy of perceptual discrimination of brain injuries through auditory images. Appropriate conversion of a neonate EEG signal to an audio signal that is discriminative and sounds natural.The goal of this project is to work in different aspects of the development of a neonatal brain stethoscope. This tool is expected to be an alternative to the current devices, which are expensive and require a very specific training to be used. First, an interactive web interface has been developed to assess the detection of neonatal brain injuries by the users using an alternative interpretation method framework. The webpage presents the currently-used visual method, based on visualisation of electroencephalogram (EEG) traces, and an alternative way that also includes a sonification output and an AI-assisted decision support. Secondly, a connection has been established between an acquisition board and a portable device using Bluetooth Low Energy (BLE). This allows to wirelessly receive and store in real time the EEG signals that come from the electrodes through the acquisition board.La finalidad de este proyecto es trabajar en diferentes aspectos del desarrollo de un estetoscopio cerebral para recién nacidos. Esta herramienta está pensada como alternativa a los sistemas actuales, que generalmente son caros y cuyo uso requiere un entrenamiento muy específico. En primer lugar, se ha desarrollado una interfaz web interactiva para poder analizar y valorar la detección de daño cerebral en neonatos por parte de los usuarios utilizando un método alternativo de interpretación. La página web incluye el método gráfico actual, que corresponde a la visualización de señales electroencefalográficas (EEG), así como una forma alternativa de interpretar las señales, utilizando una representación acústica de éstas y un soporte de decisiones haciendo uso de un sistema asistido por inteligencia artificial. En segundo lugar, se ha establecido una conexión entre la placa de adquisición y una tableta táctil, utilizando la tecnología Bluetooth Low Energy. Esto permite, sin necesidad de cables, recibir y almacenar las señales EEG que provienen de los electrodos a través de la placa de adquisición.La finalitat d'aquest projecte es treballar en diferents aspectes del desenvolupament d'un estetoscopi cerebral per a nounats. Aquesta eina està concebuda com a alternativa als sistemes actuals, que resulten cars i el seu ús requereix un entrenament molt específic. Primer de tot, s'ha desenvolupat una interfície web interactiva per a analitzar i valorar la detecció per part dels usuaris de dany cerebral en neonats emprant un mètode alternatiu d?interpretació. La pàgina web inclou el mètode gràfic actual, que correspon a la visualització de senyals electroencefalogràfics (EEG), i també una forma alternativa d'interpretar les senyals, fent ús tant de la seva representació acústica com d'un suport de decisions emprant un sistema assistit per intel·ligència artificial. En segon lloc, s'ha establert la connexió entre una placa d'adquisició i una tauleta tàctil, fent ús de la tecnologia Bluetooth Low Energy. Això permet, sense necessitat de cables, rebre i emmagatzemar en temps real els senyals EEG que provenen dels elèctrodes a través de la placa d'adquisició

Android Implementation of a Visualisation, Sonification and AI-Assisted Interpretation of Neonatal EEG

Development of deep neural network models for detection of neonatal seizures. Implementation of the detection system as an Android application.The aim of this project is the implementation of an Android App to help healthcare professionals to check newborn health status by observing neonatal EEG signals, without having extensive training in EEG interpretation. To satisfy that aim, this project is divided in three blocks: AI-assisted neonatal EEG interpretation, EEG sonification and graphical user interface. The AI-assisted block has the function to detect neonatal seizures using a fully- convolutional deep neural network using the offline-trained existing model. The sonification work consisted of the adaptation of a previously developed algorithm, based on the phase vocoder, which was already implemented by another UPC student in the Android environment. The developed application core provides both sonification and AI detection functionalities, which are integrated in a user friendly graphical user interface.El objetivo de este proyecto era la implementación de una aplicación Android para ayudar a profesionales del ámbito médico a comprobar el estado de salud de neonatos en base a la observación del electroencefalograma (EEG), sin necesidad de tener mucha experiencia en el campo de la neonatología. Para cumplir dicho objetivo, el proyecto se ha dividido en tres bloques: interpretación asistida por IA, sonificación y interfaz de usuario gráfica. El bloque de IA se encarga de la detección de epilepsias en recién nacidos utilizando una red neuronal totalmente convolucional implementada en Android llevando a cabo la adaptación de un modelo ya existente en Python. El trabajo de sonificación del EEG ha consistido en la adaptación de un algoritmo basado en Phase Vocoder realizado por otro estudiante de la UPC La finalidad de la interfaz gráfica es mostrar de forma integrada la información recibida de la sonificación y la red neuronal para que el usuario pueda interpretarlas con facilidad, de forma que la aplicación resulte útil a un gran número de usuarios.L'objectiu d'aquest projecte era la implementació d'una aplicació Android per ajudar a professionals de l'àmbit mèdic a comprovar l'estat de salut de nounats en base a l'observació de l'electroencefalograma (EEG), sense necessitat de tenir molta experiència en neonatologia. Per tal d'acomplir aquest objectiu, el projecte s'ha dividit en tres blocs: interpretació assistida per IA, sonificació i interfície d'usuari gràfica. El bloc d'IA s'encarrega de la detecció d'epilèpsies en nadons utilitzant una xarxa neuronal totalment convolucional implementada en Android duent a terme l'adaptació d'un model ja existent programat en Python. El treball de sonificació de l'EEG ha consistit en l'adaptació d'un algoritme basat en Phase Vocoder realitzat per un altre estudiant de la UPC La finalitat de la interfície gràfica és mostrar de forma integrada la informació rebuda de la sonificació i la xarxa neuronal perquè l'usuari pugui interpretar-les amb facilitat, de manera que l'aplicació resulti útil a un gran nombre d'usuaris

System level framework for assessing the accuracy of neonatal EEG acquisition

Significant research has been conducted in recent years to design low-cost alternatives to the current EEG monitoring systems used in healthcare facilities. Testing such systems on a vulnerable population such as newborns is complicated due to ethical and regulatory considerations that slow down the technical development. This paper presents and validates a method for quantifying the accuracy of neonatal EEG acquisition systems and electrode technologies via clinical data simulations that do not require neonatal participants. The proposed method uses an extensive neonatal EEG database to simulate analogue signals, which are subsequently passed through electrical models of the skin-electrode interface, which are developed using wet and dry EEG electrode designs. The signal losses in the system are quantified at each stage of the acquisition process for electrode and acquisition board losses. SNR, correlation and noise values were calculated. The results verify that low-cost EEG acquisition systems are capable of obtaining clinical grade EEG. Although dry electrodes result in a significant increase in the skin-electrode impedance, accurate EEG recordings are still achievable

A portable and low-cost electroencephalography device with automated autism diagnosis

Capstone Project submitted to the Department of Engineering, Ashesi University in partial fulfillment of the requirements for the award of Bachelor of Science degree in Electrical and Electronic Engineering, May 2021Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by challenges in speech and communication, impairment in social skills, and repetitive behavior. Autistic children in Africa have very severe symptoms of autism due to the lateness in the diagnosis and treatment of autism on the continent. This work explores the use of a portable, low-cost electroencephalography (EEG) device with automated diagnosis as a means of expediting the process of autism diagnosis in Africa. This work compares two instrumentation amplifier designs for the EEG system. It also compares k-nearest neighbor, support vector machine, decision tree, and random forest as classifiers for providing automated diagnosis for the EEG system. The resulting design was a portable EEG system that can be interfaced with a smartphone for real-time visualization of the EEG signals and automated diagnosis with an accuracy of 85.1%.Ashesi Universit

Sonification of exosolar planetary systems

The purpose of this research is to investigate sonification techniques suitable for astronomers to explore exosolar planetary data. Four studies were conducted, one with sonification specialists and three with exosolar planetary astronomers. The first study was to establish existing practices in sonification design and obtain detailed information about design processes not fully communicated in published papers. The other studies were about designing and evaluating sonifications for three different fields of exosolar astronomy. One, to sonify atmospheric data of an exoplanet in a habitable zone. Another, to sonify accretion discs located in newly developing exosolar systems. The third sonification, planet detection in an asteroid belt. User-centred design was used so that mappings of the datasets could be easily comprehensible. Each sonification was designed to sound like the natural elements that were represented in the data. Spatial separation between overlapping datasets can make hidden information more noticeable and provide additional dimensionality for sound objects. It may also give a more realistic interpretation of the data object in a real-world capacity. Multiple psychoacoustic mappings can convey data dimensionality and immediate recognition of subtle changes. Sound design aesthetics that mimic natural sounds were more relatable for the user. Sonification has been effective within the context of these studies offering new insight by unmasking previously unnoticed data particulars. It has also given the astronomers a broader understanding of the dimension of the data objects that they study and their temporal-spatial behaviours. Future work pertains to the further development and creation of a sonification model consisting of different aspects of exosolar astronomy that could be developed for a platform that houses different data related to this field of study

The Impact of Digital Technologies on Public Health in Developed and Developing Countries

This open access book constitutes the refereed proceedings of the 18th International Conference on String Processing and Information Retrieval, ICOST 2020, held in Hammamet, Tunisia, in June 2020.* The 17 full papers and 23 short papers presented in this volume were carefully reviewed and selected from 49 submissions. They cover topics such as: IoT and AI solutions for e-health; biomedical and health informatics; behavior and activity monitoring; behavior and activity monitoring; and wellbeing technology. *This conference was held virtually due to the COVID-19 pandemic

Improving Access and Mental Health for Youth Through Virtual Models of Care

The overall objective of this research is to evaluate the use of a mobile health smartphone application (app) to improve the mental health of youth between the ages of 14–25 years, with symptoms of anxiety/depression. This project includes 115 youth who are accessing outpatient mental health services at one of three hospitals and two community agencies. The youth and care providers are using eHealth technology to enhance care. The technology uses mobile questionnaires to help promote self-assessment and track changes to support the plan of care. The technology also allows secure virtual treatment visits that youth can participate in through mobile devices. This longitudinal study uses participatory action research with mixed methods. The majority of participants identified themselves as Caucasian (66.9%). Expectedly, the demographics revealed that Anxiety Disorders and Mood Disorders were highly prevalent within the sample (71.9% and 67.5% respectively). Findings from the qualitative summary established that both staff and youth found the software and platform beneficial

The Impact of Digital Technologies on Public Health in Developed and Developing Countries

This open access book constitutes the refereed proceedings of the 18th International Conference on String Processing and Information Retrieval, ICOST 2020, held in Hammamet, Tunisia, in June 2020.* The 17 full papers and 23 short papers presented in this volume were carefully reviewed and selected from 49 submissions. They cover topics such as: IoT and AI solutions for e-health; biomedical and health informatics; behavior and activity monitoring; behavior and activity monitoring; and wellbeing technology. *This conference was held virtually due to the COVID-19 pandemic