The Validity of a Mixed Reality-Based Automated Functional Mobility Assessment.

Area of Science:

• Biomedical Engineering
• Gerontology
• Human-Computer Interaction

Background:

• Functional mobility assessments are crucial for screening mobility and fall risk in older adults.
• Current methods often require direct clinical supervision and can be subjective.

Purpose of the Study:

• To develop and validate a novel Mixed Reality (MR)-based functional mobility assessment system.
• To evaluate the accuracy of MR headset sensors against reference inertial sensors for kinematic measurements.

Main Methods:

• An automated functional mobility assessment application was developed using the Microsoft HoloLens platform.
• Twenty-two healthy adults (10 older, 12 young) performed mobility tests guided by the MR headset.
• Mobility performance was recorded using the HoloLens's built-in sensors and reference inertial sensors (APDM Opal).

Main Results:

• Vertical kinematic measurements from the HoloLens showed good agreement with reference sensors (Normalized RMSE ~10%).
• Test completion times measured by the HoloLens perfectly matched clinical stopwatch measurements.
• The MR system successfully guided participants without severe mobility deficits through functional tests.

Conclusions:

• Mixed Reality (MR) technology can automate functional mobility assessments, providing objective kinematic data.
• This MR-based approach offers an efficient, sensor-based mobility assessment method.
• The system has the potential to reduce the need for direct clinical oversight in mobility screening.