CPC G10L 15/22 (2013.01) [A61B 5/0031 (2013.01); A61B 5/24 (2021.01); A61B 5/686 (2013.01); A61B 5/7264 (2013.01); A61B 5/741 (2013.01); G06N 3/08 (2013.01); G10L 13/00 (2013.01); G10L 15/02 (2013.01); G10L 15/16 (2013.01); G10L 15/183 (2013.01); G10L 19/00 (2013.01); A61B 2562/046 (2013.01); G10L 2015/025 (2013.01)] | 20 Claims |
1. A neuronal speech system for decoding intended speech from neuronal signals, comprising:
a neuronal signal recorder configured to be implanted into a human user's brain, comprising:
an array of microelectrodes, each microelectrode in the array of microelectrodes providing at least one channel for measurement of neuronal activity;
a voltage threshold filtering circuitry configured to:
apply a band-pass filter to each measurement; and
apply a voltage threshold to the band-pass filtered measurements of between −3× and −5× of root mean squared voltage of the at least one channel to produce a binary value indicating the presence or absence of an action potential (AP) for the at least one channel;
a controller circuitry, where the controller circuitry is configured to:
record local field potentials (LFPs) and APs from each microelectrode in the array of microelectrodes via the voltage threshold filtering circuitry; and
bin features describing the LFPs and APs from each microelectrode in the array of microelectrodes in a plurality of bins, where each covers a time window between 5 ms and 100 ms;
a communication circuitry configured to wirelessly transmit values of the bins as neuronal signal data to a neuronal signal decoder;
the neuronal signal decoder configured to be located external to the user's body, comprising:
a processor;
an input/output interface; and
a memory, where the memory contains a neuronal speech application that directs the processor to:
obtain neuronal signal data from the neuronal signal recorder, where the neuronal signal data describes neuronal activity proximate to the implanted neuronal signal recorder;
decode speech features from the neuronal signal data using a neuronal decoding machine learning model;
construct a speech string from the decoded speech features; and
output the constructed speech string via an output device.
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