📄️ Best Practices for Collaborative Python Development
Develop in a Virtual Environment
📄️ Predictive modelling of Alzheimer's Disease
Alzheimer's is brutal brain disorder that is one of the leading causes of dementia across our aged community.
📄️ Predictive Modelling of Diabetes
Diabetes has become a leading cause for concern amongst Australia's population, with over 1.3 Million people confirmed cases and 500,000 more estimated undiagnosed type 2 cases.
📄️ Fall detection feature for Elderly Care Wearable
The aim of this feature is to implement functionality to detect and promptly alert care providers to falls. This feature also seeks to detect abnormal locomotion (i.e limping) to provide early warning to care providers for potential intervention.
📄️ Heart Attack Prediction
This feature has been built with the intention of providing an early warning for Heart disease based on indicators collected by the wearable's sensor array. This feature seeks to provide users and their support network an alert to worrying decreases in cardiovascular health.
📄️ Parkinson's Disease Prediction Model
This feature has been undertaken to predict the presence of Parkinson's Disease based on the features expressed by patients that can be extracted from the patient's vocal patterns. Parkinson's Disease is a neurodegenerative disorder that has the common symptoms of:
📄️ Sleep Disorder Prediction
This feature aims to quantify both sleep quality and quantity by measuring motion from sleeping wearers of the IoT device. Sleep quality and monitoring has proven to be significant in recent time for many preventative health care outcomes. For this reason Smartwatches boasting this capability have flooded the market. To capitalize on these capabilities and hopefully provide these benefits to our users, Redback has undertaken predictive modelling of sleep disorders.
📄️ Voice Assistant feature for Elderly Care Wearable.
The goal of this sub-project is to develop and integrate voice assistant functionality into the Elderly care wearable device.