Automatic synchronization of functional electrical stimulation and robotic assisted treadmill training

Area of Science:

• Biomedical Engineering
• Rehabilitation Technology
• Neuroscience

Background:

• Stroke survivors often experience gait deficits, impacting mobility and quality of life.
• Current gait training technologies like functional electrical stimulation (FES-IM) and robotic exoskeletons (Lokomat) show promise but require precise synchronization.
• Manual synchronization between FES-IM and the Lokomat can be inconsistent, limiting training effectiveness.

Purpose of the Study:

• To develop and validate a system for automatic synchronization of intramuscular functional electrical stimulation (FES-IM) with the Lokomat robotic gait orthosis.
• To enhance the precision and reliability of gait training for stroke survivors.

Main Methods:

• A novel hardware and software system was engineered to enable automatic synchronization.
• Bench tests were conducted to evaluate the feasibility, reliability, and accuracy of the automatic synchronization system.
• Performance was compared against manually triggered FES-IM.

Main Results:

• Automatic synchronization of FES-IM to the Lokomat gait cycle was demonstrated as feasible and reliable.
• The system achieved a 10-fold smaller standard deviation in latency compared to manual triggering.
• Stimulation was timed with 2.5% accuracy within the gait cycle, with no early or missed stimulations across 634 strides.

Conclusions:

• Automatic synchronization of FES-IM and Lokomat is a reliable and accurate method for gait training.
• This technology offers improved consistency over manual triggering, potentially enhancing rehabilitation outcomes for stroke survivors.
• The developed system represents a significant advancement in integrated neurorehabilitation technologies.