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AI Biotech/Diagnostics: Cardio
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Application US20200282223
Published 2020-09-10
Meeting Brain-computer Interface User Performance Expectations Using A Deep Neural Network Decoding Framework
A brain-computer interface (BCI) includes a multichannel stimulator and a decoder. The multichannel stimulator is operatively connected to deliver stimulation pulses to a functional electrical stimulation (FES) device to control delivery of FES to an anatomical region. The decoder is operatively connected to receive at least one neural signal from at least one electrode operatively connected with a motor cortex. The decoder controls the multichannel stimulator based on the received at least one neural signal. The decoder comprises a computer programmed to process the received at least one neural signal using a deep neural network. The decoder may include a long short-term memory (LSTM) layer outputting to a convolutional layer in turn outputting to at least one fully connected neural network layer. The decoder may be updated by unsupervised updating. The decoder may be extended to include additional functions by transfer learning.
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- 1. A brain-computer interface (BCI) comprising:
a multichannel stimulator operatively connected to deliver stimulation pulses to a functional electrical stimulation (FES) device to control delivery of FES to an anatomical region; and a decoder operatively connected to receive at least one neural signal from at least one electrode operatively connected with a motor cortex and to control the multichannel stimulator based on the received at least one neural signal; wherein the decoder comprises a computer programmed to process the received at least one neural signal using a deep neural network.
- 23. An assistance method for assisting a patient having a spinal cord injury to manipulate an anatomical region of the patient that is paralyzed due to the spinal cord injury, the assistance method comprising:
applying a decoder to at least one neural signal received from at least one electrode operatively connected with a motor cortex of the patient to generate a predicted movement of the anatomical region, wherein the decoder comprises a computer programmed to process the at least one neural signal using a deep neural network to generate the predicted movement of the anatomical region; and performing functional electrical stimulation (FES) to cause the predicted movement of the anatomical region using a multichannel stimulator that is operatively connected to deliver stimulation pulses to a functional electrical stimulation (FES) device operatively connected to the anatomical region.
- 29. An assistance system comprising:
a brain-computer interface (BCI) comprising a computer operatively connected to receive at least one neural signal from a patient and programmed to apply a decoder to the at least one neural signal to generate a predicted movement, wherein the decoder comprises a deep neural network; and an assistive device, the BCI operatively connected to control the assistive device to perform the predictive movement.
