Augmented Reality Framework to Measure and Analyze Eye-Hand Coordination in Stroke Patients with Unilateral Neglect:...

Area of Science:

• Neuroscience
• Rehabilitation Medicine
• Human-Computer Interaction

Background:

• Stroke often causes unilateral spatial neglect (USN), hindering recovery.
• Traditional assessments lack insight into real-world eye-hand coordination.
• Augmented reality (AR) offers potential for advanced behavioral tracking.

Purpose of the Study:

• Validate a multimodal AR system for accurate clinical data capture.
• Demonstrate reliable detection of USN behavioral patterns.
• Explore how comprehensive data enhances understanding of eye-hand coordination deficits in USN.

Main Methods:

• Developed an AR system using HoloLens 2 and body tracking.
• Synchronized and fused gaze, hand, and body movement data.
• Compared tracking performance with optical motion capture; assessed 7 USN patients and 8 controls in a reaching task.

Main Results:

• AR system fusion reduced tracking loss to 2.4% with 3.27 cm error.
• USN patients showed ipsilesional gaze bias (P<.05) and slower contralesional target finding (P=.02).
• USN group exhibited altered gaze anchoring during reaching (P=.02).

Conclusions:

• The AR framework offers a novel, data-driven method for naturalistic behavioral assessment.
• The system effectively measures USN symptoms like gaze bias and eye-hand coordination deficits.
• This approach enhances USN assessment and provides deeper patient behavioral insights.