IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
-
IEEE Trans Neural Syst Rehabil Eng · Aug 2010
Continuous detection and decoding of dexterous finger flexions with implantable myoelectric sensors.
A rhesus monkey was trained to perform individuated and combined finger flexions of the thumb, index, and middle finger. Nine implantable myoelectric sensors (IMES) were then surgically implanted into the finger muscles of the monkey's forearm, without any adverse effects over two years postimplantation. Using an inductive link, EMG was wirelessly recorded from the IMES as the monkey performed a finger flexion task. ⋯ When the algorithm was trained and tested on data collected the same day, the average performance was 43.8+/-3.6% n=10. When the training-testing separation period was five months, the average performance of the algorithm was 46.5+/-3.4% n=8. These results demonstrated that using EMG recorded and wirelessly transmitted by IMES offers a promising approach for providing intuitive, dexterous control of artificial limbs where human patients have sufficient, functional residual muscle following amputation.
-
IEEE Trans Neural Syst Rehabil Eng · Aug 2010
Self-paced operation of an SSVEP-Based orthosis with and without an imagery-based "brain switch:" a feasibility study towards a hybrid BCI.
This work introduces a hybrid brain-computer interface (BCI) composed of an imagery-based brain switch and a steady-state visual evoked potential (SSVEP)-based BCI. The brain switch (event related synchronization (ERS)-based BCI) was used to activate the four-step SSVEP-based orthosis (via gazing at a 8 Hz LED to open and gazing at a 13 Hz LED to close) only when needed for control, and to deactivate the LEDs during resting periods. Only two EEG channels were required, one over the motor cortex and one over the visual cortex. ⋯ Six subjects participated in this study. This combination of two BCIs operated with different mental strategies is one example of a "hybrid" BCI and revealed a much lower rate of FPs per minute during resting periods or breaks compared to the SSVEP BCI alone ( FP=1.46+/-1.18 versus 5.40 +/- 0.90). Four out of the six subjects succeeded in operating the self-paced hybrid BCI with a good performance (positive prediction value PPVb > 0.70).