System for detecting electric signals

A computing system comprising:

• one or more processors;
• and
• one or more computer-readable media having stored thereon computer-executable instructions that are structured such that, when executed by the one or more processors, the computer-executable instructions configure the computing system to:
• receive a first set of neural signals generated in a continuous manner by a plurality of sensors positioned at a plurality of particular positions on a human body for sensing neural signals from the human body;
• simultaneous with the receiving of the first set of neural signals, receive a first set of motion intents associated with a first sequence of body movements in a continuous manner, wherein the first set of motion intents are received in conjunction with at least one of:
• (i) mimicked training in which a user attempts to mimic a sequence of motions performed by a virtual limb;
• and (ii) mirrored training in which the user mirrors motions performed by a not-amputated limb;
• and
• train an artificial intelligence (AI) regression model using a machine learning neural network, wherein:
• the AI regression model continuously maps the first set of neural signals to joint angle values of a virtual hand based upon the first set of motion intents,
• in response to receiving a second set of neural signals generated by the plurality of sensors in a continuous manner and during a different training session, the AI regression model is configured to predict a second set of motion intents, causing an electronic device to perform an action associated with the second set of motion intents, wherein the second set of motion intents are different than the first set of motion intents, and
• on a session-to-session basis, incrementally updating the AI regression model by accounting for a continuous mapping of the second set of neural signals to the second set of motion intents.

A sleeve connected to an electronic device, comprising:

• a plurality of sensors configured to be positioned at a plurality of predetermined positions of a human body to generate electric signals in a continuous manner;
• and
• an alignment indicator configured to align one or more ultra violet (UV) tattoo markers of on the human body with one or more markers of the sleeve;
• wherein the sleeve is in communication with one or more processors and one or more computer-readable media having stored thereon an artificial intelligence (AI) regression model and computer-executable instructions, the computer-executable instructions are structured such that, when executed by the one or more processors, the computer-executable instructions configure the sleeve to:
• sense a first set of neural signals from the human body in a continuous manner, wherein the sensing of the neural signals is performed during at least one of:
• (i) mimicked training in which a user attempts to mimic a sequence of motions performed by a virtual limb;
• and (ii) mirrored training in which the user mirrors motions performed by a not-amputated limb,
• use the AI regression model to predict a first motion intent in response to the first set of neural signals, wherein the first motion intent comprises a continuous mapping of neural signals to joint angle values of a virtual hand,
• in a different training session, receiving a second set of neural signals from the plurality of sensors in a continuous manner;
• based upon the AI regression model, predicting a second motion intent in response to the second set of neural signals, wherein the second set of motion intents are different than the first set of motion intents;
• causing the electronic device to perform an action based upon the second motion intent;
• and
• on a session-to-session basis, incrementally updating the AI regression model by accounting for a continuous mapping of the second set of neural signals to the second motion intent.