TY - GEN
T1 - Multi-scale recordings for neuroprosthetic control of finger movements
AU - Baker, Justin
AU - Bishop, William
AU - Kellis, Spencer
AU - Levy, Todd
AU - House, Paul
AU - Greger, Bradley
PY - 2009
Y1 - 2009
N2 - We trained a rhesus monkey to perform individuated and combined finger flexions and extensions of the thumb, index, and middle finger. A Utah Electrode Array (UEA) was implanted into the hand region of the motor cortex contralateral to the monkey's trained hand. We also implanted a microwire electrocorticography grid CoG) epidurally so that it covered the UEA. The μECoG grid spanned the arm and hand regions of both the primary motor and somatosensory cortices. Previously this monkey had Implantable MyoElectric Sensors (IMES) surgically implanted into the finger muscles of the monkey's forearm. Action potentials (APs), local field potentials (LFPs), and ECoG signals were recorded from wired head-stage connectors for the UEA and μECoG grids, while EMG was recorded wirelessly. The monkey performed a finger flexion/extension task while neural and EMG data were acquired. We wrote an algorithm that uses the spike data from the UEA to perform a real-time decode of the monkey's finger movements. Also, analyses of the LFP and μECoG data indicate that these data show trial-averaged differences between different finger movements, indicating the data are potentially decodeable.
AB - We trained a rhesus monkey to perform individuated and combined finger flexions and extensions of the thumb, index, and middle finger. A Utah Electrode Array (UEA) was implanted into the hand region of the motor cortex contralateral to the monkey's trained hand. We also implanted a microwire electrocorticography grid CoG) epidurally so that it covered the UEA. The μECoG grid spanned the arm and hand regions of both the primary motor and somatosensory cortices. Previously this monkey had Implantable MyoElectric Sensors (IMES) surgically implanted into the finger muscles of the monkey's forearm. Action potentials (APs), local field potentials (LFPs), and ECoG signals were recorded from wired head-stage connectors for the UEA and μECoG grids, while EMG was recorded wirelessly. The monkey performed a finger flexion/extension task while neural and EMG data were acquired. We wrote an algorithm that uses the spike data from the UEA to perform a real-time decode of the monkey's finger movements. Also, analyses of the LFP and μECoG data indicate that these data show trial-averaged differences between different finger movements, indicating the data are potentially decodeable.
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U2 - 10.1109/IEMBS.2009.5332692
DO - 10.1109/IEMBS.2009.5332692
M3 - Conference contribution
C2 - 19963841
AN - SCOPUS:77950994601
SN - 9781424432967
T3 - Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009
SP - 4573
EP - 4577
BT - Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society
PB - IEEE Computer Society
T2 - 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009
Y2 - 2 September 2009 through 6 September 2009
ER -