Evaluation of FNS control systems: software development and sensor characterization

Area of Science:

• Biomedical Engineering
• Rehabilitation Technology
• Neuroscience

Background:

• Functional Neuromuscular Stimulation (FNS) enables paralyzed limb function in individuals with thoracic spinal cord injury.
• Restoring posture and movement is crucial for improving quality of life after spinal cord injury.
• Advanced control algorithms are essential for effective FNS system performance.

Purpose of the Study:

• To describe software developed for implementing FNS control systems.
• To characterize a motion tracking sensor system for FNS evaluation.
• To improve the accuracy of sensor data used in FNS control.

Main Methods:

• Development of a versatile software package using LabVIEW for FNS control.
• Integration of sensor systems (Flock of Birds) for 6-DOF limb tracking.
• Characterization of sensor errors and development of nonlinear polynomial compensation models.

Main Results:

• The LabVIEW software facilitates real-time FNS control and data processing.
• Sensor error characterization identified key sources of inaccuracy.
• Nonlinear polynomial compensation reduced distance measurement error by 90%, achieving <1 cm maximum error.

Conclusions:

• The developed software and sensor compensation enhance the evaluation of FNS control algorithms.
• Accurate motion tracking is vital for precise FNS system control and rehabilitation.
• This work contributes to the advancement of FNS technology for restoring function after spinal cord injury.