Control within a virtual environment is correlated to functional outcomes when using a physical prosthesis.

Area of Science:

• Biomedical Engineering
• Rehabilitation Science
• Prosthetics

Background:

• Evaluating upper limb myoelectric prosthesis control is challenging.
• Virtual environments offer cost-effective practice but their translation to physical outcomes is unclear.
• Targeted muscle reinnervation and pattern recognition control show promise for improved prosthesis function.

Purpose of the Study:

• To investigate the effectiveness of in-home practice with a pattern recognition-controlled myoelectric prosthesis.
• To determine the relationship between virtual and physical functional outcomes after prosthesis use.
• To assess improvements in prosthesis control following a 6-week home trial.

Main Methods:

• Nine individuals with transhumeral amputations and targeted muscle reinnervation surgery participated.
• Participants used a myoelectric prosthesis with pattern recognition control during a 6-week home trial.
• Virtual and physical outcome measures were collected pre- and post-trial.

Main Results:

• Significant improvements were observed in offline classification error, virtual Target Achievement Control, and physical Southampton Hand Assessment Procedure and Box and Blocks Test.
• Virtual test completion times strongly correlated with several physical assessment scores.
• Classification error performance showed a significant correlation with the physical Clothespin Relocation Test.

Conclusions:

• In-home practice with pattern recognition myoelectric prostheses enhances functional control, validated by both virtual and physical measures.
• Virtual assessment tools require further validation and standardization for reliable clinical and research use.
• This study supports the use of virtual environments for prosthesis training and evaluation.