A system and method for transferring proprioceptive and/or sensory information from a prosthesis or from a sensing system disposed at a body part having poor or no sensation, to the skin of a user wearing the prosthesis or the sensing system, includes: a device for providing electrotactile feedback in the form of an electrical stimulation pattern with coding scheme for at least one input signal; and at least one multi-pad electrode configured to be positioned on a part of the body of the user. The multi-pad electrode includes a plurality of pads configured to be selectively and discretely activated/deactivated according to the predefined stimulation pattern.

A system for attachment of a device to a bone is provided. The system includes an internal axial rod with a proximal and distal end that is configured to be inserted and secured into a bone cavity's distal end. The system can also include an internal-external transfer rod with a proximal and distal end mounted into the distal end of the axial rod and a central channel extending through the transfer rod from the proximal end to the distal end and a plurality of attachment rings for attaching at least one tissue or muscle group to the transfer rod. The system also includes a bio-compatible and bio-occlusive artificial membranes (BIOCAMS) lamina, wherein the lamina includes either a polyetheretherketone (PEEK) mesh, a biocompatible polymer, a carbon fiber polymer, an artificial tissue polymer, molded donor tissue, allogenic tissue, a collagen/hyaluronic acid-based tissue, or connective tissue biosynthetic substrate material suitable as webbing.

Systems and methods for simultaneous position and impedance control for myoelectric interfaces are disclosed herein. Properties such as control refinement, retention, generalization, and transfer allow users to learn simultaneous and proportional motion simply by interacting with a myoelectric interface, regardless of its initial intuitiveness. The presently disclosed technology expands on these motor learning approaches by implementing a multidirectional impedance controller in this framework. Using sEMG inputs from upper limb muscles, users simultaneously control both the stiffness and set-point of 3-DOFs. Users stabilize control in the presence of external forces in an analogous way to natural limb movements. Despite having no haptic feedback, subjects learn to tune the stiffness of the object being controlled to stabilize movement along desired paths.

Various aspects of the present disclosure characterize apparatuses and/or methods as may be implemented with a variety of prosthetic components and applications. As may be consistent with one or more embodiments described herein, respective manipulators are operable and/or operate to manipulate a prosthetic foot component about respective (e.g., separate) axes. A sensor circuit senses movement characteristics of the prosthetic foot component (e.g., movement, surroundings, and/or load applied due to movement). The manipulators operate with the sensor circuit to manipulate the prosthetic foot component about the axes in response to the sensed movement characteristics indicating that the prosthetic foot component is elevated over a surface.

Various aspects of the present disclosure characterize apparatuses and/or methods as may be implemented with a variety of prosthetic components and applications. As may be consistent with one or more embodiments described herein, respective manipulators are operable and/or operate to manipulate a prosthetic foot component about respective (e.g., separate) axes. A sensor circuit senses movement characteristics of the prosthetic foot component (e.g., movement, surroundings, and/or load applied due to movement). The manipulators operate with the sensor circuit to manipulate the prosthetic foot component about the axes in response to the sensed movement characteristics indicating that the prosthetic foot component is elevated over a surface.

An implantable human-machine interfacing system is disclosed that includes an implantable muscle interface device including a substrate including a first plurality of sensors and a second plurality of amplifiers that capture and amplify, respectively, electromyographic (EMG) signals arising from motor units under control of neural signals representative of volitional limb movements; and a transceiver device connected to the first plurality of sensors that wirelessly transmits signals to an external decoder that produces decoded signals that discriminate motor signals representative of movements of the motor units, wherein the substrate at least partially surrounds a muscle from which the EMG signals arise; and a receiver device that uses the decoded signals for interaction with an external system. The system includes a first plurality of electrodes and a second implantable power source that imparts electrical stimulation to the underlying tissues and sensory axons within for the purposes of sensory feedback and neuromodulation.

An implantable human-machine interfacing system is disclosed that includes an implantable muscle interface device including a substrate including a first plurality of sensors and a second plurality of amplifiers that capture and amplify, respectively, electromyographic (EMG) signals arising from motor units under control of neural signals representative of volitional limb movements; and a transceiver device connected to the first plurality of sensors that wirelessly transmits signals to an external decoder that produces decoded signals that discriminate motor signals representative of movements of the motor units, wherein the substrate at least partially surrounds a muscle from which the EMG signals arise; and a receiver device that uses the decoded signals for interaction with an external system. The system includes a first plurality of electrodes and a second implantable power source that imparts electrical stimulation to the underlying tissues and sensory axons within for the purposes of sensory feedback and neuromodulation.

A brain machine interface system for use with an electroencephalogram to identify a behavioral intent of a person is disclosed. The system includes an electroencephalogram configured to sense electromagnetic signals generated by a brain of a person. The electromagnetic signals include a time component and a frequency component. A monitor monitors a response of the person to a stimulus and a characteristic of the stimulus. A synchronization module synchronizes the sensed electromagnetic signals with the response and the characteristic to determine a set of electromagnetic signals corresponding to the monitored response and the characteristic. A processor processes the set of electromagnetic signals and extracts feature vectors. The feature vectors define a class of behavioral intent. The processor determines the behavioral intent of the person based on the feature vectors. A brain machine interface and a method for identifying a behavioral intent of a person is also disclosed.

A brain machine interface system for use with an electroencephalogram to identify a behavioral intent of a person is disclosed. The system includes an electroencephalogram configured to sense electromagnetic signals generated by a brain of a person. The electromagnetic signals include a time component and a frequency component. A monitor monitors a response of the person to a stimulus and a characteristic of the stimulus. A synchronization module synchronizes the sensed electromagnetic signals with the response and the characteristic to determine a set of electromagnetic signals corresponding to the monitored response and the characteristic. A processor processes the set of electromagnetic signals and extracts feature vectors. The feature vectors define a class of behavioral intent. The processor determines the behavioral intent of the person based on the feature vectors. A brain machine interface and a method for identifying a behavioral intent of a person is also disclosed.

Systems and methods of generating and applying a synthetic neuromodulatory signal are described. A subject may be put under a particular condition that causes an effect in the subject. While the subject is under the condition, a recording of neurogram signals derived from the condition can be made from the subject. For example, neuronal signals traveling on the vagus nerve of the subject may be monitored and recorded. The neurogram may then be used to create a synthetic neuromodulatory signal that can be administered to a user. When the synthetic neuromodulatory signal is administered to the user, the user may experience the same effect as the subject that had been placed in the condition, even though the user was never put under the same condition.