Abstract: Described is a goal-oriented sensorimotor controller for generating musculoskeletal simulations with neural excitation commands. The controller receives a task-level motion command for motion of a musculoskeletal system, the musculoskeletal system having musculoskeletal dynamics that include steady state tendon forces. The controller then generates, based on the task-level motion command, a set of muscle activations associated with the steady state tendon forces. A set of excitation commands are then generated that minimizes required muscle activations amongst the set of muscle activations to generate motion consistent with the task-level motion command, thereby performing a musculoskeletal simulation.

Abstract: Described is a low power system for mobile devices that provides continuous, behavior-based security validation of mobile device applications using neuromorphic hardware. A mobile device comprises a neuromorphic hardware component that runs on the mobile device for continuously monitoring time series related to individual mobile device application behaviors, detecting and classifying pattern anomalies associated with a known malware threat in the time series related to individual mobile device application behaviors, and generating an alert related to the known malware threat. The mobile device identifies pattern anomalies in dependency relationships of mobile device inter-application and intra-applications communications, detects pattern anomalies associated with new malware threats, and isolates a mobile device application having a risk of malware above a predetermined threshold relative to a risk management policy.

Abstract: Described is a system for patient-specific rehabilitation that can be performed outside a clinic. The system monitors a patient in real-time to generate a quantitative assessment of a physical state and a motivational state of the patient using sensor data obtained from sensors. Predictions related to the patient are generated utilizing patient-specific biomechanical and neurocognitive models implemented with predictive simulations. Video feed of the patient is registered with sensor data and a set of simulation data. Rehabilitation guidance instructions are conveyed to the patient through dialog-based interactions.

Abstract: Described is a system for system for gait intervention and fall prevention. The system is incorporated into a body suit having a plurality of distributed sensors and a vestibulo-muscular biostim array. The sensors are operable for providing biosensor data to the analytics module, while the vestibulo-muscular biostim array includes a plurality of distributed effectors. The analytics module is connected with the body suit and sensors and is operable for receiving biosensor data and analyzing a particular user's gait and predicting falls. Finally, a closed-loop biostim control module is included for activating the vestibulo-muscular biostim array to compensate for a risk of a predicted fall.

Abstract: A computer-implemented method and system for modifying a musculoskeletal model is provided. Test data for a set of ergonomic tests performed by a number of test subjects fitting a profile is obtained. A number of muscle parameters for a number of muscles in the musculoskeletal model are adjusted using the test data to modify the musculoskeletal model to adapt to the profile.

Abstract: A computer-implemented method and system for modifying a musculoskeletal model is provided. Test data for a set of ergonomic tests performed by a number of test subjects fitting a profile is obtained. A number of muscle parameters for a number of muscles in the musculoskeletal model are adjusted using the test data to modify the musculoskeletal model to adapt to the profile.

Abstract: Described is a system for system for gait intervention and fall prevention. The system is incorporated into a body suit having a plurality of distributed sensors and a vestibulo-muscular biostim array. The sensors are operable for providing biosensor data to the analytics module, while the vestibulo-muscular biostim array includes a plurality of distributed effectors. The analytics module is connected with the body suit and sensors and is operable for receiving biosensor data and analyzing a particular user's gait and predicting falls. Finally, a closed-loop biostim control module is included for activating the vestibulo-muscular biostim array to compensate for a risk of a predicted fall.

Abstract: Described is system for tele-robotic operations over time-delayed communication links. Sensor data is acquired from at least one sensor for sensing surroundings of a robot having at least one robotic arm for manipulating an object. A three-dimensional model of the sensed surroundings is generated, and the sensor data is fit to the three-dimensional model. Using the three-dimensional model, a user demonstrates a movement path for the at least one robotic arm. A flow field representing the movement path is generated and combined with obstacle-repellent forces to provide force feedback to the user through a haptic device. The flow field comprises a set of parameters, and the set of parameters are transmitted to the robot to execute a movement of the at least one robotic arm for manipulating the object.

Abstract: A method and apparatus for monitoring musculoskeletal performance. A person repeatedly performing a physical task is monitored using a sensor system to generate task performance data. A simulation of the person performing the physical task over a number of cycles is run using a musculoskeletal model for the person and at least one of the task performance data and task description data. Muscle activation data and tendon force data are generated based on the simulation. Muscle fatigue and tendon fatigue resulting from performing the physical task are simulated for each cycle using a fatigue model system, the muscle activation data, and the tendon force data. The musculoskeletal model is adjusted to account for the muscle fatigue and the tendon fatigue after each cycle and prior to a next cycle. A prediction is made as to when a predetermined risk threshold for the person is reached based on the simulation.

Abstract: Described is a system for controlling a torque controlled prosthetic device given motor intent inferred from neuroimaging data. The system includes at least one torque controlled prosthetic device operably connected with one or more processors. Further, the system is configured to receive neuroimaging data of a user from a neuroimaging device and decode the neuroimaging data to infer spatial motion intent of the user, where the spatial motion intent includes desired motion commands of the torque controlled prosthetic device represented in a coordinate system. The system thereafter executes, with a prosthesis controller, the motion commands as torque commands to cause the torque controlled prosthetic device to move according to the spatial motion intent of the user.

Abstract: Described is a system for controlling motion and constraint forces in a robotic system, the system infers constraints, at each time step, from a sensed state of robot/environment interactions. The inferred constraints are appended to known internal robot constraints to generate constrained dynamics. Properties associated with the constrained dynamics are determined provided to a controller. Inequality conditions associated with maintaining desired robot/environment interactions are also determined. A set of equality conditions based on the inequality conditions are then specified. The set of equality conditions are aggregated with any internal robot constraints to generate aggregated conditions that are provided to the controller. Joint torque commands are then generated for the robot based on the aggregated conditions and a specified task and null space motion command. Finally, the robot is actuated based on the joint torque commands.

Abstract: A computer-implemented method and system for modifying a musculoskeletal model is provided. Test data for a set of ergonomic tests performed by a number of test subjects fitting a profile is obtained. A number of muscle parameters for a number of muscles in the musculoskeletal model are adjusted using the test data to modify the musculoskeletal model to adapt to the profile.