Currently, there are only limited options for visualising symptoms such as pain. These symptoms are described in practice or recorded using scales, which makes them less tangible. If pain is visualised at all, it is typically done by drawing on male body representations. This can lead to incomplete depictions of health conditions.

The goal of the project is to design a documentation system in which those affected can record their subjective symptoms on a gender- and diversity-sensitive 3D model in the form of customisable avatars. Through intelligent data visualisations over time, these can be better communicated, illnesses diagnosed, and the effects of treatments understood.

At the heart of Embodied Perceptions is the question of how pain and other subjective symptoms (such as cramps, injuries, etc.) can be digitally visualised to ensure the following aspects:

• A gender- and diversity-sensitive form of representation in which those affected can recognise themselves
• Visualisation of different symptoms and types of pain, especially chronic pain
• Visualisation of temporal progressions or differences (e.g., before and after taking medication, by season/time of day)
• Possibility for documentation that supports both those affected and healthcare professionals
• Acceptance and understanding for people with chronic pain and other subjective symptoms

Project partners: AIT Austrian Institute of Technology GmbH (Projektlead), EURAG Österreich – Verein der Freunde des Bundes für die ältere Generation Europas, RISC Software GmbH, SYNYO GmbH

Duration: September 2024 – February 2027
Funds: FFG – Humanpotenzial, Humanpotenzial, FEMtech Forschungsprojekte 2023

The FFG is the central national funding organization and strengthens Austria’s innovative power. This project is funded by the FFG. www.ffg.at

       

Based on the findings of the previous project, we are creating a prototype and testing whether it can meet the expectations in a test environment. Particular attention is being paid to the key components of fall detection and systems that can independently call for help. These include:

• active emergency calls (i.e., the user calls for help),
• appropriate device responses to unusual situations (i.e., the user does not respond and the device independently detects the emergency), and
• fall prevention functions (i.e., the user is warned of potential obstacles).

In developing the system, we focus our research on the needs of future users, implement voice interaction systems as they are the most inclusive way of communication, use machine learning for emergency detection, and emphasize privacy, user-friendliness, and comfort in operating the assistance system.

 

 

Project Partners: Fachhochschule St. Pölten GmbH (Projektlead), Robert Bosch AG, Arbeiter-Samariter-Bund Gruppe Linz

Project Website: https://research.fhstp.ac.at/projekte/smart-companion-2
Duration: March 2022 – February 2025
Funds: FFG – IKT der Zukunft