Abstract: A system includes an input device in operable communication with a processor. The input device generates a plurality of signals representing an intended control of a prosthesis. The processor executes a predetermined pattern recognition (PR) control method that applies the plurality of input signals to at least one machine learning model trained using a training data set augmented with synthetic noise. The at least one machine learning model is configured to align the plurality of input signals to a low-dimensional manifold defining features and classify the features to identify a command for moving the prosthesis. The predetermined PR control method leverages the deep learning of the at least one machine learning model and the augmented training data to improve noise tolerance.

Abstract: Embodiments of the invention provide for a prosthesis guided training system that includes a plurality of sensors for detecting electromyographic activity. A computing device, which can include a processor and memory, can extract data from the electromyographic activity. A real-time pattern recognition control algorithm and an autoconfiguring pattern recognition training algorithm can be stored in the memory. The computing device can determine movement of a prosthesis based on the execution of the real-time pattern recognition control algorithm. The computing device can also alter operational parameters of the real-time pattern recognition control algorithm based on execution of the autoconfiguring pattern recognition training algorithm.

Abstract: We present a novel swing phase control module for powered transfemoral prostheses based on minimum jerk theory. The control module allows physiologically appropriate swing movement at any walking speed, regardless of the stance controller action. Preliminary validation in a transfemoral amputee subject demonstrates that the control module provides physiological swing timing, without speed or patient-specific tuning.

Abstract: This disclosure relates to a hierarchy of classifiers, including linear discriminant analysis (LDA) classifiers, arranged to provide simultaneous control of multiple degrees of freedom of a prosthetic. The high accuracy of the hierarchical approach allows pattern recognition techniques to be extended to permit simultaneous control, potentially allowing amputees to produce more fluid, life-like movements, ultimately increasing their quality of life. The hierarchy may also be used to control a biological interface that allows input to computers for persons with disabilities, used as a potential video-game controller, and used as an input interface for tablets, and phones.

Abstract: Embodiments of the systems and methods described herein relate to a control unit comprising a memory having stored thereon a feature database that includes feature data, a portion of which is labeled with a transition from an ambulation mode and a memory having stored thereon a pattern recognition controller that is trained using the labeled feature data, wherein the pattern recognition controller is configured to predict the ambulation mode of an assistive device and the control unit is configured to communicate with sensors coupled to the assistive device.

Abstract: We present a novel swing phase control module for powered transfemoral prostheses based on minimum jerk theory. The control module allows physiologically appropriate swing movement at any walking speed, regardless of the stance controller action. Preliminary validation in a transfemoral amputee subject demonstrates that the control module provides physiological swing timing, without speed or patient-specific tuning.

Abstract: Embodiments of the invention provides myoelectric prosthesis control system that include a gel liner that has a plurality of layers and a plurality of leads at least partially positioned between the plurality of layers. In addition, a plurality of electrodes can be coupled to the leads and portions of the electrodes can also be positioned between the plurality of layers. At least some of the electrodes can include an electrode pole that is configured to contract the residual limb to detect electromyographic signals.

Abstract: Embodiments of the systems and methods described herein relate to a control unit comprising a memory having stored thereon a feature database that includes feature data, a portion of which is labeled with a transition from an ambulation mode and a memory having stored thereon a pattern recognition controller that is trained using the labeled feature data, wherein the pattern recognition controller is configured to predict the ambulation mode of an assistive device and the control unit is configured to communicate with sensors coupled to the assistive device.

Abstract: Embodiments of the invention provide for a prosthesis guided training system that includes a plurality of sensors for detecting electromyographic activity. A computing device, which can include a processor and memory, can extract data from the electromyographic activity. A real-time pattern recognition control algorithm and an autoconfiguring pattern recognition training algorithm can be stored in the memory. The computing device can determine movement of a prosthesis based on the execution of the real-time pattern recognition control algorithm. The computing device can also alter operational parameters of the real-time pattern recognition control algorithm based on execution of the autoconfiguring pattern recognition training algorithm.

Abstract: This disclosure relates to a hierarchy of classifiers, including linear discriminant analysis (LDA) classifiers, arranged to provide simultaneous control of multiple degrees of freedom of a prosthetic. The high accuracy of the hierarchical approach allows pattern recognition techniques to be extended to permit simultaneous control, potentially allowing amputees to produce more fluid, life-like movements, ultimately increasing their quality of life. The hierarchy may also be used to control a biological interface that allows input to computers for persons with disabilities, used as a potential video-game controller, and used as an input interface for tablets, and phones.

Abstract: Embodiments of the invention provides myoelectric prosthesis control system that include a gel liner that has a plurality of layers and a plurality of leads at least partially positioned between the plurality of layers. In addition, a plurality of electrodes can be coupled to the leads and portions of the electrodes can also be positioned between the plurality of layers. At least some of the electrodes can include an electrode pole that is configured to contract the residual limb to detect electromyographic signals.