Dr Peter Graham Brown | UNSW Research

Keywords

Fields of Research (FoR)

Health services and systems, Mobile computing

Biography

Dr Peter Brown is a postdoctoral fellow at the Graduate School of Biomedical Engineering. He completed his doctoral degree in Prof Yaoqi Zhou's lab at Griffith University prior to joining UNSW in 2021. His research interests are in the field of data driven telehealth services, and has a background in full-stack software engineering contributing to and maintaining the codebases powering critical remote patient monitoring telehealth mobile applications. As the academic coordinator of the Tyree Foundation Institute of Health Engineering (Tyree IHealthE) Connected Health Network Laboratory (CHANL), he is responsible for developing the scope and schedule of new projects, offering guidance and assistance including the delivery of training workshops on health application development, regulatory requirement expectations, and barriers constraining the design and development of mobile health applications. He is currently supervising around 30 undergraduate thesis students working with CHANL on biomedical software engineering projects.

My Grants

IHealthE Catalyst Award (CIA), "A Smart Mouthguard for Sleep Monitoring", 2021

UNSW Research Infrastructure Scheme (CI), "Connected HeAlth Network Laboratory (CHANL)", 2022-2023

My Qualifications

Doctor of Philosophy, School of Information and Communication Technology, Griffith University, 2019
Research area: Structural Alignments for Similarity Detection in Bioinformatics
Supervisors: Professor Yaoqi Zhou, Dr Wayne Pullan

Bachelor of Information Technology (Honours I), Griffith University, 2014

My Research Activities

TCC-Cardiac
TCC-Cardiac is an NSW Health-funded study that will examine the comparative efficacy of the TeleClinical Care - Cardiac solution comprising of a smartphone application, backend clinician dashboard and associated model of care, and its messages component as standalone, as an adjunct to usual standard care in patients who are being discharged home following an acute cardiac event. The system is designed to support patients who have recently been admitted with a heart attack or heart failure. It allows for the delivery of educational messages, the monitoring of physiological parameters (such as heart rate, blood pressure, weight and oxygen levels in the blood) by a team of hospital-based clinicians and provides a virtual cardiac rehabilitation exercise programme.

TCC-Stroke
TCC-Stroke is an NHMRC MRFF-funded study with the goal of detecting early onset of atrial fibrillation using a deep learning algorithm to better treat stroke patients. The system is designed to support patients who have recently been admitted with a stroke, or a Transient Ischaemic Attack (TIA). It allows for the delivery of educational messages, the monitoring of physiological parameters (such as heart rate, blood pressure, and electrocardiogram) by a team of hospital-based clinicians. The app also assists with medication adherence and provides a virtual stroke rehabilitation exercise programme.

My Research Supervision

Supervision keywords

agile software engineering

mobile applications

web services

computer science

home telehealth system

home telemonitoring

Areas of supervision

As an example of work that has been supported from a thesis student training perspective, a non-exhaustive list of projects from 2022 follows:

A new lightweight backend system for WalkingTall - Helping people with Parkinson's walk with confidence
App to assess and treat Benign Paroxysmal Positional Vertigo (BPPV)
Automated stitching of 3D ultrasound volumes
Backend development of system for post-surgical management of patients
Biosensor software development
Clinical and administration reporting module for telehealth backend
Clinical Decision Support System for COPD
Cloud Platform for Smart Mouthguard for Sleep Monitoring (OptoSleep)
Cloud-based backend for the sensoria smart band
CNN based approach to tissue fate prediction in acute ischaemic stroke
Conversational agent for people with low back pain
Deep learning on image data for detecting falls and classifying movement
Design of a smartphone app in React Native to manage the frail older person in the community through recording of physiological measurements and delivery of targeted exercises
Development of a mobile companion that supports patients on their cataract surgery journey
Development of a smartphone application for speech motor control rehabilitation
Development of an AR smartphone exercise game to reduce fall risk in older adults
Fall detection implementation on an Apple iWatch
FHIR Questionnaire Dashboard and Integration for telehealth
Front end integration with the Vlepis patch
Holo Lens 2 application for virtual surgery
Kinect-based depth mapping system for upper limb movement analysis in stroke patients
Medication Adherence Monitor from Webstercare
Module for atrial defibrillation detection on a smartphone
Passport for care system for childhood cancer survivors
React Native smartphone app and python backend for mental health and wellness
React Native smartphone app for monitoring of chronic obstructive pulmonary disease (COPD)
React Native smartphone app for monitoring of gestational diabetes and wellness
React Native smartphone app for post-surgical management of surgical patients
Remote monitoring application for pre-term babies
Risk of fall prediction through a vision camera (or mmWave radar, or infrared sensor) using AI
SmartCup predictive analytics
Smartphone app for a smartcup
Smartphone app for sleep apnoea monitoring
Smartphone app to help improve diagnosis of headache disorders
SmartVA - smartphone application for Verbal Autopsy
Software development platform for real-time infra-red based camera tracking for 3D ultrasound imaging
Teleclinical care mental health module (collaboration with Mindgardens)
Telehealth content management system for educational resources
Telehealth video conferencing solution
The SPHERE Digital Health Accelerator (DHA)
Using Machine Learning and Artificial Intelligence to classify behavior of persons living with dementia
Walking Tall Go: A physical fitness app targeted at elderly smartphone users
Waveapp for deriving parameters from heart pump systems