PTPilotJournal of neuroengineering and rehabilitation2017

A brain-computer interface driven by imagining different force loads on a single hand: an online feasibility study.

Kun Wang, Zhongpeng Wang, Yi Guo and 4 others

PMID 28893295

WHAT IT FOUND

Eleven healthy people learned to control a brain-computer interface by imagining different grip strengths.

They correctly selected high, low, or relaxed states with 70.9% accuracy. This proves the concept works in healthy users but provides no evidence for stroke patients.

Key findings

01Healthy participants achieved a mean accuracy of 70.9% in identifying three mental states (high force, low force, relaxed) using an online brain-computer interface.

02Imagining a higher force load produced stronger brain activity patterns (ERD) in the motor cortex compared to imagining a lower load.

03Electromyogram data confirmed that participants successfully avoided actual muscle contraction while performing the mental imagery tasks.

STILL TO COME

How it was doneWhat they foundWhat it means for PTs

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What it does not show

The study involved only 11 healthy young adults, so it does not show how stroke patients or people with movement disorders would perform. Participants received extensive training and real-time voice feedback, which may not be practical in typical clinical settings. The accuracy, while above chance, was modest (70.9%), and the system struggled to distinguish between high and low force levels. This was a feasibility study designed to test if the concept works, not a trial testing if it improves patient outcomes.

Declared interests

The study was funded by the National Natural Science Foundation of China, the Natural Science Foundation of Tianjin City, and the Tianjin science and technology support program.

The easy way to misread this

Do not assume this technology is ready for clinical use with stroke patients. The study tested only healthy young people in a highly controlled lab setting with feedback. It did not test whether this approach helps any patient recover function.

Read it on PubMed →