Measurement of Hand Function by an Automated Device-System Validation and Usability Analysis

Area of Science:

• Biomedical Engineering
• Rehabilitation Technology
• Motion Capture

Background:

• Traditional goniometry for hand function assessment is time-consuming and prone to subjectivity and variability.
• Advancements in motion capture and sensor-based devices offer potential for improved efficiency and accuracy in hand rehabilitation.
• Existing technologies face limitations in objectivity, inter-rater reliability, and accuracy.

Purpose of the Study:

• To evaluate the repeatability and accuracy of a 9-axis inertial measurement unit (IMU)-based glove and an infrared (IR) camera system.
• To determine the potential of these novel systems to replace traditional goniometry in clinical settings.
• To assess the reliability and validity of new sensor technologies for hand mobility assessment.

Main Methods:

• Repeatability was assessed using a silicone hand model under controlled conditions.
• Accuracy was evaluated with a volunteer participant without movement constraints.
• Bland-Altman plots were utilized for visual comparison and accuracy assessment against a goniometer.

Main Results:

• The IMU-based glove (Nuada) demonstrated high repeatability (SD < 2 degrees), exceeding the goniometer's accuracy threshold.
• The IR camera system (UltraLeap) also showed comparable repeatability (deviations < 3.5 degrees).
• Accuracy limitations were noted, with significant deviations (>5 degrees) for both systems compared to the goniometer, though they were more consistent with each other.

Conclusions:

• Both the IMU-based glove and IR camera system exhibit excellent repeatability, indicating strong potential for clinical applications.
• Further refinement of accuracy is necessary for these technologies to fully replace traditional goniometry.
• These advanced sensor systems could enhance traditional hand mobility assessments, offering greater efficiency and objectivity in clinical practice.