Abstract: A functional electrical stimulation (FES) device includes electrodes arranged to apply functional electrical stimulation to a body part of the user. FES stimulation is performed by: receiving values of a set of user metrics for the user; receiving a target position of the body part represented as values for a set of body part position measurements; determining a user-specific energization pattern for producing the target position based on the received target position and the received values of the set of user metrics for the user; and energizing the electrodes of the FES device in accordance with the determined user-specific energization pattern. The determination may utilize an FES calibration database with records having fields containing: values of the set of user metrics for reference users; energization patterns; and values of the set of body part position metrics for positions assumed by the body part in response to applying the energization patterns.

Abstract: A functional electrical stimulation (FES) device includes electrodes arranged to apply functional electrical stimulation to a body part of the user. FES stimulation is performed by: receiving values of a set of user metrics for the user; receiving a target position of the body part represented as values for a set of body part position measurements; determining a user-specific energization pattern for producing the target position based on the received target position and the received values of the set of user metrics for the user; and energizing the electrodes of the FES device in accordance with the determined user-specific energization pattern. The determination may utilize an FES calibration database with records having fields containing: values of the set of user metrics for reference users; energization patterns; and values of the set of body part position metrics for positions assumed by the body part in response to applying the energization patterns.

Abstract: A gearcase for a marine propulsion system has an input shaft rotatable about a central axis of rotation and an output shaft coaxially arranged with the input shaft. A clutch assembly is operable between a first clutch position and a second clutch position, wherein, when the clutch assembly is in the first clutch position, the input shaft is coupled to the output shaft for rotating the output shaft in a first rotational direction. When the clutch assembly is in the second clutch position a gear assembly operably connects the input shaft to the output shaft for rotating the output shaft in an opposite second rotational direction. The gearcase can be part of a marine propulsion system, such as an outboard motor for a mud boat. A method of transferring power in a gearcase and a marine propulsion system are also disclosed.

Abstract: A portable and wearable hand-grasp neuro-orthosis is configured for use in a home environment to restore volitionally controlled grasp functions for a subject with a cervical spinal cord injury (SCI). The neuro-orthosis may include: a wearable sleeve with electrodes; electronics for operating the wearable sleeve to perform functional electrical stimulation (FES) and electromyography (EMG), the electronics configured for mounting on a wheelchair; and a controller configured for mounting on a wheelchair. The controller controls the electronics to read EMG via the sleeve, decode the read EMG to determine an intent of the user, and operate the electronics to apply FES via the sleeve to implement the intent of the user. The neuro-orthosis may restore hand function. The controller may include a display arranged to be viewed by the subject, for example mounted on an articulated arm attached to the wheelchair.

Abstract: A brain-computer interface (BCI) includes a multichannel stimulator and a decoder. The multichannel stimulator is operatively connected to deliver stimulation pulses to a functional electrical stimulation (FES) device to control delivery of FES to an anatomical region. The decoder is operatively connected to receive at least one neural signal from at least one electrode operatively connected with a motor cortex. The decoder controls the multichannel stimulator based on the received at least one neural signal. The decoder comprises a computer programmed to process the received at least one neural signal using a deep neural network. The decoder may include a long short-term memory (LSTM) layer outputting to a convolutional layer in turn outputting to at least one fully connected neural network layer. The decoder may be updated by unsupervised updating. The decoder may be extended to include additional functions by transfer learning.

Abstract: The present disclosure provides systems and processes for compensating disruptions in a brain-machine interface (BMI). Briefly described, the systems and processes detect and compensate for transient disruptions, reversible disruptions, irreversible compensable disruptions, or irreversible non-compensable disruptions.

Abstract: Systems and methods for generating a finite element model (FEM) of current flow in an anatomical human forearm are disclosed. The disclosed FEM may assist in determining optimal stimulation parameters in electrical stimulation systems for achieving movement of paralyzed limbs or enhancement of able limbs. This model will allow users to determine which muscle groups are receiving stimulation under different parameters. Systems and methods which leverage electrical impedance tomography (EIT) for autonomous recalibration following garment donning are also disclosed. The method may comprise performing an EIT measurement across an electrode array of an electrode garment and constructing an anatomical model based on the EIT measurement. Next, one or more alignment variations may be estimated based on an alignment variation model. Finally, the electrode array is adjusted, automatically or manually, to accommodate the alignment variations using an alignment adjustment function.

Abstract: A portable and wearable hand-grasp neuro-orthosis is configured for use in a home environment to restore volitionally controlled grasp functions for a subject with a cervical spinal cord injury (SCI). The neuro-orthosis may include: a wearable sleeve with electrodes; electronics for operating the wearable sleeve to perform functional electrical stimulation (FES) and electromyography (EMG), the electronics configured for mounting on a wheelchair; and a controller configured for mounting on a wheelchair. The controller controls the electronics to read EMG via the sleeve, decode the read EMG to determine an intent of the user, and operate the electronics to apply FES via the sleeve to implement the intent of the user. The neuro-orthosis may restore hand function. The controller may include a display arranged to be viewed by the subject, for example mounted on an articulated arm attached to the wheelchair.

Abstract: A brain-computer interface (BCI) includes a multichannel stimulator and a decoder. The multichannel stimulator is operatively connected to deliver stimulation pulses to a functional electrical stimulation (FES) device to control delivery of FES to an anatomical region. The decoder is operatively connected to receive at least one neural signal from at least one electrode operatively connected with a motor cortex. The decoder controls the multichannel stimulator based on the received at least one neural signal. The decoder comprises a computer programmed to process the received at least one neural signal using a deep neural network. The decoder may include a long short-term memory (LSTM) layer outputting to a convolutional layer in turn outputting to at least one fully connected neural network layer. The decoder may be updated by unsupervised updating. The decoder may be extended to include additional functions by transfer learning.

Abstract: At least one electrical brain signal is received from a patient and is demultiplexed into an efferent motor intention signal and at least one afferent sensory signal (such as an afferent touch sense signal and/or an afferent proprioception signal). A functional electrical stimulation (FES) device is controlled to apply FES to control a paralyzed portion of the patient that is paralyzed due to a spinal cord injury of the patient. The controlling of the FES device is based on at least the efferent motor intention signal. A demultiplexed afferent touch sense signal may be used to control a haptic device. The afferent sensory signal(s) may be used to adjust the FES control.

Abstract: Systems and methods which leverage electrical impedance tomography (EIT) for autonomous recalibration following garment donning are disclosed. The method may comprise performing an EIT measurement across an electrode array of an electrode garment and generating an anatomical model based on the EIT measurement. Next, one or more alignment variations may be estimated based on an alignment variation model. Finally, the electrode array is adjusted, automatically or manually, to accommodate the alignment variations using an alignment adjustment function.

Abstract: A device is provided for delivering somatosensation. A garment is wearable on a body part, and includes an array of electrodes in electrical contact with skin of the body part when the garment is worn on the body part. An electronics module is configured to use the array of electrodes of the garment to apply a somatosensation pattern providing guidance in performing a motor action, or providing a pain sensation to the wearer.

Abstract: EMG training systems, devices and methods are disclosed. In an approach, a computing device may receive a first input and a second input. The first input may be from an EMG device, such as the NeuroLife® sleeve provided by Battelle. A second input may be from a joint position capturing device. The computing device may create a mapping between the first input and the second input and then train a decoding algorithm based on the mapping. The decoding algorithm may be used to determine a position of the EMG device based on input received from the EMG device.

Abstract: In a method of neurological assessment, multichannel electromyography (EMG) data are acquired for an anatomical region. A pairwise EMG channel-EMG channel similarity matrix is generated from the acquired multichannel EMG data. Network analysis is performed on the similarity matrix to generate a network representing the similarity matrix. One or more metrics of the network are computed. One or more biomarkers are determined for the anatomical region based on the one or more metrics. In another method, EMG data are acquired using an electrode array contacting skin of a target anatomy, the EMG data are processed to produce reduced-dimensionality data; and time-invariant muscle synergies and corresponding time-varying activation functions are determined in the reduced-dimensionality data.

Abstract: The present disclosure relates generally to systems, methods, and devices for interpreting neural signals to determine a desired movement of a target, transmitting electrical signals to the target, and dynamically monitoring subsequent neural signals or movement of the target to change the signal being delivered if necessary, so that the desired movement is achieved. In particular, the neural signals are decoded using a feature extractor, decoder(s) and a body state observer to determine the electrical signals that should be sent.

Abstract: In an approach to neural interface systems, a system includes feature extraction circuitry to identify one or more features of one or more input signals; and neural processing circuitry. The neural processing circuitry is configured to: identify a first context of a plurality of contexts based on a first trigger event; decode the one or more features of the one or more input signals to determine a first task of a plurality of tasks in the first context; and responsive to detecting a second trigger event, change the first context to a second context of the plurality of contexts.

Abstract: At least one electrical brain signal is received from a patient and is demultiplexed into an efferent motor intention signal and at least one afferent sensory signal (such as an afferent touch sense signal and/or an afferent proprioception signal). A functional electrical stimulation (FES) device is controlled to apply FES to control a paralyzed portion of the patient that is paralyzed due to a spinal cord injury of the patient. The controlling of the FES device is based on at least the efferent motor intention signal. A demultiplexed afferent touch sense signal may be used to control a haptic device. The afferent sensory signal(s) may be used to adjust the FES control.

Abstract: The present disclosure relates generally to systems, methods, and devices for interpreting neural signals to determine a desired movement of a target, transmitting electrical signals to the target, and dynamically monitoring subsequent neural signals or movement of the target to change the signal being delivered if necessary, so that the desired movement is achieved. In particular, the neural signals are decoded using a feature extractor, decoder(s) and a body state observer to determine the electrical signals that should be sent.

Abstract: A functional electrical stimulation (FES) device includes electrodes arranged to apply functional electrical stimulation to a body part of the user. FES stimulation is performed by: receiving values of a set of user metrics for the user; receiving a target position of the body part represented as values for a set of body part position measurements; determining a user-specific energization pattern for producing the target position based on the received target position and the received values of the set of user metrics for the user; and energizing the electrodes of the FES device in accordance with the determined user-specific energization pattern. The determination may utilize an FES calibration database with records having fields containing: values of the set of user metrics for reference users; energization patterns; and values of the set of body part position metrics for positions assumed by the body part in response to applying the energization patterns.

Abstract: A functional electrical stimulation (FES) device includes electrodes arranged to apply functional electrical stimulation to a body part of the user. FES stimulation is performed by: receiving values of a set of user metrics for the user; receiving a target position of the body part represented as values for a set of body part position measurements; determining a user-specific energization pattern for producing the target position based on the received target position and the received values of the set of user metrics for the user; and energizing the electrodes of the FES device in accordance with the determined user-specific energization pattern. The determination may utilize an FES calibration database with records having fields containing: values of the set of user metrics for reference users; energization patterns; and values of the set of body part position metrics for positions assumed by the body part in response to applying the energization patterns.