Systems and methods for approximating musculoskeletal dynamics

Inventors

Sobinov, Anton • Yakovenko, Sergiy • Gritsenko, Valeriya • Boots, Matthew • Gaunt, Robert • Collinger, Jennifer • Fisher, Lee

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Assignees

University of Pittsburgh

West Virginia University

West Virginia University is a public R1 research institution offering diverse undergraduate and graduate programs across science, engineering, business, creative arts, and media. The university emphasizes experiential learning, research, and innovation, with notable strengths in academic program development, research excellence, community engagement, and a commitment to affordability, career readiness, and student success. WVU supports a vibrant campus environment, industry partnerships, and impactful scholarship, preparing students for careers through hands-on education, research, and applied learning.

Publication Number

US-11998460-B2

Patent

Publication Date

2024-06-04

Expiration Date


Abstract

A system and method for controlling a device, such as a virtual reality (VR) and/or a prosthetic limb are provided. A biomimetic controller of the system comprises a signal processor and a musculoskeletal model. The signal processor processes M biological signals received from a residual limb to transform the M biological signals into N activation signals, where M and N are integers and M is less than N. The musculoskeletal model transforms the N activation signals into intended motion signals. A prosthesis controller transforms the intended motion signals into three or more control signals that are outputted from an output port of the prosthesis controller. A controlled device receives the control signals and performs one or more tasks in accordance with the control signals.

Core Innovation

The invention relates to a biomimetic controller that receives a biological signal from a residual limb and expands the biological signal into one or more activation signals based at least in part on a scaling coefficient and a number of degrees of freedom (DOFs). The biomimetic controller performs a modeling algorithm that transforms the one or more activation signals into one or more intended motion signals, and then performs a control algorithm that transforms the intended motion signals into control signals. The biomimetic controller sends the control signals to a controlled device.

The invention further uses feedback and signal routing to support different device modes, including a virtual reality (VR) prosthesis system and a prosthetic limb. A switching device selectively places the selected component in communication with a prosthesis controller so it receives the control signals for performing one or more tasks. In corresponding switching configurations, feedback signals associated with virtual motion and actual motion are provided to a processor to be used in transforming the biological signal into the activation signals.

A core technical contribution described is a musculoskeletal-dynamics approximation approach based on polynomial approximation and constrained relationships between muscle length and moment arms, with optimization using corrected Akaike Information Criterion (AICc) to select polynomial structures. The document also describes real-time or near real-time applicability and includes similarity/structure analyses such as similarity index (SI), hierarchical clustering, and principal component analysis (PCA) for comparing structures. Experimental and simulation validation for multi-DOF hand motion is reported using root mean squared (RMS) error.

Claims Coverage

The independent claims are system claim 1 and method claim 12. Across these independent claims, the document includes multiple inventive features centered on residual-limb biological signal processing into activation signals with scaling and DOFs, transforming activation signals into intended motion signals, transforming intended motion signals into control signals, and sending the control signals to a controlled device; additional inventive features specify switching between VR prosthesis and prosthetic limb and include polynomial-approximation-based handling conditioned on switching configurations, as described in dependent claims.

Residual-limb biological signal expansion into activation signals

Receive a biological signal from a residual limb and expand the biological signal into one or more activation signals based at least in part on a scaling coefficient and a number of degrees of freedom (DOFs) associated with the biological signal.

Activation-to-intended-motion modeling algorithm

Perform a modeling algorithm that transforms the one or more activation signals into one or more intended motion signals.

Intended-motion-to-control-signal control algorithm

Perform a control algorithm that transforms the intended motion signals into control signals.

Control signals sent to a controlled device

Send the control signals to a controlled device.

Switchable VR prosthesis and prosthetic limb configurations with feedback routing

Include either a virtual reality (VR) prosthesis system or a prosthetic limb, and use a switching device to route control signals so that the VR system performs tasks in a first configuration and the prosthetic limb performs the same tasks in a second configuration, with respective feedback-signal sets corresponding to virtual motion and actual motion fed back to a processor for transforming the biological signal into one or more activation signals.

Configuration-dependent polynomial approximation for muscle dynamics

Use a polynomial approximation (Poly) block conditioned on switching configurations to receive third feedback signals from a modeling algorithm or fourth feedback signals from a prosthetic limb, and then approximate muscle dynamics to generate intended motion signals.

The independent claim set covers a biomimetic controller and corresponding method that process a residual-limb biological signal into activation signals using a scaling coefficient and DOFs, transform activation signals into intended motion signals via a modeling algorithm, convert intended motion signals into control signals via a control algorithm, and send the control signals to a controlled device; dependent inventive features additionally include switching between VR prosthesis and a prosthetic limb with configuration-dependent feedback and a polynomial approximation (Poly) block for muscle dynamics handling conditioned on the switching configuration.

Stated Advantages

High approximation accuracy is reported (including moment arms and muscle lengths).

Greatly reduced evaluation time and memory versus splines are reported.

Real-time or near real-time applicability is reported.

Similarity/structure analyses are described, including similarity index (SI), hierarchical clustering, and principal component analysis (PCA).

Documented Applications

Controlling a controlled device using a biomimetic controller, including a myoelectric prosthesis or a VR prosthesis system for prosthetic or virtual motion.

Demonstration/validation involving multi-DOF hand motion using experimental and simulation results.

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