Abstract: Systems, articles, and methods for improved capacitive electromyography (“EMG”) sensors are described. The improved capacitive EMG sensors include one or more sensor electrode(s) that is/are coated with a protective barrier formed of a material that has a relative permittivity ?r of about 10 or more. The protective barrier shields the sensor electrode(s) from moisture, sweat, skin oils, etc. while advantageously contributing to a large capacitance between the sensor electrode(s) and the user's body. In this way, the improved capacitive EMG sensors provide enhanced robustness against variations in skin and/or environmental conditions. Such improved capacitive EMG sensors are particularly well-suited for use in wearable EMG devices that may be worn by a user for an extended period of time and/or under a variety of skin and/or environmental conditions. A wearable EMG device that provides a component of a human-electronics interface and incorporates such improved capacitive EMG sensors is described.

Abstract: Methods and system for predicting the onset of a motor action using neuromuscular signals. The system comprises a plurality of sensors configured to continuously record a plurality of neuromuscular signals from a user and at least one computer processor programmed to provide as input to a trained statistical model, the plurality of neuromuscular signals or information based on the plurality of neuromuscular signals, predict, based on an output of the trained statistical model, whether an onset of a motor action will occur within a threshold amount of time; and send a control signal to at least one device based, at least in part, on the output probability, wherein the control signal is sent to the at least one device prior to completion of the motor action by the user.

Abstract: Systems, articles, and methods for surface electromyography (“EMG”) sensors that combine elements from traditional capacitive and resistive EMG sensors are described. For example, capacitive EMG sensors that are adapted to resistively couple to a user's skin are described. Resistive coupling between a sensor electrode and the user's skin is galvanically isolated from the sensor circuitry by a discrete component capacitor included downstream from the sensor electrode. The combination of a resistively coupled electrode and a discrete component capacitor provides the respective benefits of traditional resistive and capacitive (respectively) EMG sensor designs while mitigating respective drawbacks of each approach. A wearable EMG device that provides a component of a human-electronics interface and incorporates such capacitive EMG sensors is also described.

Abstract: Method and apparatus for rendering a visual representation based on a musculoskeletal representation. The method comprises updating the musculoskeletal representation based, at least in part, on a plurality of neuromuscular signals recorded from a user, wherein the musculoskeletal representation is updated based at least in part on: position information describing a spatial relationship between two or more connected segments of the musculoskeletal representation, and force information describing a force exerted by at least one segment of the musculoskeletal representation, and rendering, via a user interface, the visual representation based on the updated musculoskeletal representation, wherein the visual representation includes a visual indication of the position information and a visual indication of the force information.

Abstract: Methods and apparatus for enabling a user or third-party to select or adjust parameters of one or more statistical models used to generate a musculoskeletal representation. The method comprises providing as input to the statistical model(s), a plurality of neuromuscular signals recorded by a plurality of neuromuscular sensors during performance of at least one gesture by a user, wherein the at least one gesture is performed by the user while wearing a wearable device having the plurality of neuromuscular sensors arranged thereon, rendering at least one visual representation based on an output of the statistical model(s), and receiving user or third-party input to adjust parameters of the statistical model(s) based on the rendered at least one visual representation, the user input including a selection of a particular statistical model of the statistical model(s) and/or an adjustment of parameters associated with the particular statistical model.

Abstract: Methods and apparatus for anonymizing neuromuscular signals used to generate a musculoskeletal representation. The method comprises recording, using a plurality of neuromuscular sensors arranged on one or more wearable devices, a plurality of neuromuscular signals from a user, providing as input to a trained statistical model, the plurality of neuromuscular signals and/or information based on the plurality of neuromuscular signals; and generating, the musculoskeletal representation based, at least in part, on an output of the trained statistical model, wherein the musculoskeletal representation is an anonymized musculoskeletal representation from which at least one personal characteristic of the user has been removed.

Abstract: Methods and apparatus for calibrating performance of one or more statistical models used to generate a musculoskeletal representation. The method comprises controlling presentation of instructions via a user interface to instruct the user to perform the at least one gesture and updating at least one parameter of the one or more statistical models based, at least in part on a plurality of neuromuscular signals recorded by a plurality of neuromuscular sensors during performance of the at least one gesture by the user.

Abstract: Methods and systems for dynamically reconstructing handstate information based on multiple inputs are described. The methods and systems use data from multiple inputs including a plurality of neuromuscular sensors arranged on one or more wearable devices and one or more cameras. The multimodal data is provided as input to a trained statistical model. The methods and systems determine, based on the data from the multiple inputs, an estimate and representation of the spatial relationship between two or more connected segments of the musculoskeletal representation and force information describing a force exerted by at least one segment of the musculoskeletal representation. The methods and systems further update the computerized musculoskeletal representation based, at least in part, on the position information and the force information.

Abstract: System and methods are provided for providing a dynamically-updated musculoskeletal representation of a hand. The system includes a plurality of neuromuscular sensors configured to continuously record a plurality of neuromuscular signals from a user, and at least one computer processor programmed to provide as input to a trained statistical model, the plurality of neuromuscular signals and temporally smooth in real-time an output of the trained statistical model. The system is also programmed to determine, based on the smoothed output of the trained statistical model, position information describing a spatial relationship between two or more connected segments of the musculoskeletal representation, force information describing a force exerted by at least one segment of the musculoskeletal representation, and update the musculoskeletal representation of the hand based, at least in part, on the position information and the force information.

Abstract: Methods and apparatus for mitigating neuromuscular signal artifacts are described. The method comprises detecting in real-time, by at least one computer processor, one or more artifacts in a plurality of neuromuscular signals recorded by a plurality of neuromuscular sensors, determining, based at least in part, on the detected one or more artifacts, a plurality of derived neuromuscular signals to mitigate the one or more artifacts, and providing, as input to one or more trained statistical models, the plurality of derived neuromuscular signals.

Abstract: Methods and apparatus for providing a dynamically-updated computerized musculo-skeletal representation comprising a plurality of rigid body segments connected by joints. The method comprises recording, using a plurality of autonomous sensors arranged on one or more wearable devices, a plurality of autonomous signals from a user, wherein the plurality of autonomous sensors include a plurality of neuromuscular sensors configured to record neuromuscular signals. The method further comprises providing as input to a trained statistical model, the plurality of neuromuscular signals and/or information based on the plurality of neuromuscular signals.

Abstract: Dual-supply analog circuitry for amplifying surface EMG (sEMG) signals is described. The circuitry includes a differential amplifier configured to be powered from dual-supply voltages. A positive input terminal of the differential amplifier is configured to be DC-coupled to a first sEMG electrode of a dry sEMG electrode pair and a negative input terminal of the differential amplifier is configured to be DC-coupled to a second sEMG electrode of the dry sEMG electrode pair.

Abstract: A system comprising a plurality of neuromuscular sensors, each of which is configured to record a time-series of neuromuscular signals from a surface of a user's body; and at least one computer hardware processor programmed to perform: applying a source separation technique to the time series of neuromuscular signals recorded by the plurality of neuromuscular sensors to obtain a plurality of neuromuscular source signals and corresponding mixing information; providing features, obtained from the plurality of neuromuscular source signals and/or the corresponding mixing information, as input to a trained statistical classifier and obtaining corresponding output; and identifying, based on the output of the trained statistical classifier, and for each of one or more of the plurality of neuromuscular source signals, an associated set of one or more biological structures.

Abstract: A method, comprising applying a source separation technique to the time series of neuromuscular signals recorded by the plurality of neuromuscular sensors to obtain a plurality of neuromuscular source signals and corresponding mixing information; aligning the plurality of neuromuscular source signals to a plurality of template neuromuscular source signals, the aligning comprising: determining, using a cost function, a distance between first features and second features, the first features obtained from the plurality of neuromuscular source signals and/or the corresponding mixing information, the second features obtained from the template neuromuscular source signals and/or corresponding template mixing information; and identifying, based on results of the aligning and for each of one or more of the plurality of neuromuscular source signals, an associated set of one or more biological structures.