Subject

Falls pose a significant health risk, particularly for individuals with neurological conditions, with 57-89% of neurological patients experiencing falls compared to 16.1% in healthy controls. During hospital or rehabilitation stays, 13-39% of neurological patients fall at least once, rising to over 50% for stroke patients.
The consequences of falls are far-reaching, including increased morbidity, mortality, healthcare costs, and reduced independence and activity. Therefore, accurate fall risk assessment is crucial for these high-risk populations.
Traditional balance assessments (e.g., Mini-BEST, BBS, TUG) have limitations in sensitivity and specificity, often failing to account for the complex interplay between physical and psychological factors. Recent research emphasizes the importance of integrating neuropsychological stress and cognitive load into fall risk evaluations, particularly during dual-task performances. However, incorporating these factors into clinical assessments remains challenging.
Innovative approaches, such as immersive virtual environments, could potentially enhance fall risk assessment by simulating real-world challenges while monitoring psychological responses. Virtual Reality (VR) is already used to provoke unstable or anxious situations in a controlled setting, but
mostly to answer fundamental science questions. Therefore, the experimental conditions have limited relation to daily life situation and anxiety is mostly triggered with elevated heights and therefore sets a postural threat.
This gap between fundamental research and clinical practice was to be closed by developing a stressful virtual everyday environment.
Thus, a virtual environment of a crowded railway station subway was created, testing the influence of divided attention and distraction on balance in a safe environment. The Environment was programmed in Godot (Juan Linietsky, Ariel Manzur and contributors, Version 4.4, hosted by the Godot Foundation). A wireless Oculus Quest 3 headset (Reality Labs, Meta Platforms, Menlo Park, California, US, 2023) was used to visualize the VR environment (VE). The VE was designed to simulate a realistic daily-life scenario, specifically walking through a busy train station, with various attentional demands integrated into the environment. Hand representation was possible with the integrated system from Oculus.
Various authors show that immersion in a VE, as well as the accuracy of foot placement, is significantly higher when participants can see their feet. With the current virtual environment, foot visualisation is not yet possible and requires the integration of external inertial measurement units
(IMUs) in the Godot engine.

Kind of work

Objectives
This master's thesis aims to enhance the validity of virtual balance assessments by using inertial measurement units (IMUs) to accurately reproduce foot positioning at real-life speeds in virtual environments. This innovation has the potential to significantly improve fall prevention strategies, particularly for neurological populations where falls are a major concern.
Traditional balance assessments often overlook the critical interplay
between emotional distress and balance performance. Factors such as fear of falling, anxiety, and cognitive stress can compromise balance control, yet these psychological aspects are not fully captured by conventional methods.
The goal is to develop personalized fall prevention strategies by identifying both physical and psychological risk factors. By combining biomechanical precision with emotional-state monitoring, clinicians can tailor interventions more effectively, ultimately enhancing safety and autonomy for individuals at risk of falls. This thesis aims to contribute to the development of more nuanced and effective balance assessments that address the complex needs of neurological patients.

Description of Work
The developments will be performed in close collaboration with the Rehabilitation Research (RERE) group in VUB Brussel and a rehabilitation
clinic in Switzerland. A feasibility testing will be performed either in Brussel or in Switzerland with a healthy population. This thesis will focus in the incorporation of the real life foot tracking with IMU sensors in the previous designed virtual environment.

The following tasks can be distinguished:
? Literature study
? Identification and testing of suitable IMU sensors
? Writing algorithms to include the real-time tracking in the VR
? Validation of the accuracy of the foot tracking and the immersion in the virtual environment with healthy participants
? Collaboration with physiotherapists performing the measurement