Advancing Precision Rehabilitation Through a Sensor-Based 6-DoF Robotic Exoskeleton: Clinical Validation and...

Area of Science:

• Rehabilitation Engineering
• Biomechanics
• Robotics

Background:

• Conventional upper-extremity rehabilitation lacks precise motion tracking.
• Existing robotic exoskeletons face challenges with ergonomic misalignment and adaptability.
• The AssistOn-Arm is a new self-aligning exoskeleton designed for comfort and natural interaction.

Purpose of the Study:

• To evaluate the usability and ergonomics of the AssistOn-Arm in healthy individuals.
• To conduct a pilot clinical assessment of the AssistOn-Arm in patients with shoulder impairments.
• To validate the accuracy of the AssistOn-Arm's motion tracking capabilities.

Main Methods:

• Thirty healthy participants and twelve patients with shoulder impairments performed tasks.
• Kinematic data were collected using the AssistOn-Arm and Xsens MVN systems.
• Data were analyzed for agreement and differences in joint kinematics under active and device-controlled conditions.

Main Results:

• Strong agreement was found between AssistOn-Arm and Xsens MVN kinematic data.
• No significant differences (p > 0.05) were observed in key shoulder movements like flexion, elevation, abduction-adduction, and external rotation.
• Minor differences (p < 0.05) in hyperextension and internal rotation indicated device-specific mechanical constraints.

Conclusions:

• The AssistOn-Arm demonstrates clinical feasibility as a sensor-driven, self-aligning exoskeleton.
• The device accurately tracks natural joint axes, enhancing precision rehabilitation.
• AssistOn-Arm integration into clinical practice is supported, bridging engineering and rehabilitation.