Spinal stimulator systems for restoration of function
First Claim
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1. A device for use with a plurality of electrodes, and one or more sensors, the device comprising:
- a stimulation assembly connectable to the plurality of electrodes, wherein the plurality of electrodes are configured to connect to a spinal cord at a location below a lesion of the spinal cord;
the stimulation assembly being configured to deliver stimulation to selected ones of the plurality of electrodes when the stimulation assembly is connected to the plurality of electrodes;
a sensor interface connectable to the one or more sensors, the sensor interface being configured to receive signals from the one or more sensors when the sensor interface is connected to the one or more sensors, wherein the one or more sensors are selected from an electromyography sensor, an evoked potential sensor, a joint angle sensor, a flex sensor, an accelerometer, a gyroscope sensor, a flow sensor, a pressure sensor, a load sensor, a temperature sensor, or a combination thereof;
at least one processor connected to both the stimulation assembly and the sensor interface, the at least one processor being configured to direct the stimulation assembly to deliver at least one complex stimulation pattern to the selected ones of the plurality of electrodes, and to receive the signals from the sensor interface, the at least one processor being further configured to modify the at least one complex stimulation pattern by performing a machine learning method implementing a Gaussian Process Optimization operable to determine the stimulation parameters delivered by the stimulation assembly based on the signals received from the sensor interface.
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Abstract
Described are devices including stimulation assemblies connectable to a plurality of electrodes. The plurality of electrodes can be configured to connect to a spinal cord at a location below a lesion of the spinal cord. The stimulation assembly can be configured to deliver stimulation to selected ones of the plurality of electrodes when the stimulation assembly is connected to the plurality of electrodes when located below the lesion of the spinal cord. Methods of using the devices are also described.
255 Citations
23 Claims
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1. A device for use with a plurality of electrodes, and one or more sensors, the device comprising:
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a stimulation assembly connectable to the plurality of electrodes, wherein the plurality of electrodes are configured to connect to a spinal cord at a location below a lesion of the spinal cord;
the stimulation assembly being configured to deliver stimulation to selected ones of the plurality of electrodes when the stimulation assembly is connected to the plurality of electrodes;a sensor interface connectable to the one or more sensors, the sensor interface being configured to receive signals from the one or more sensors when the sensor interface is connected to the one or more sensors, wherein the one or more sensors are selected from an electromyography sensor, an evoked potential sensor, a joint angle sensor, a flex sensor, an accelerometer, a gyroscope sensor, a flow sensor, a pressure sensor, a load sensor, a temperature sensor, or a combination thereof; at least one processor connected to both the stimulation assembly and the sensor interface, the at least one processor being configured to direct the stimulation assembly to deliver at least one complex stimulation pattern to the selected ones of the plurality of electrodes, and to receive the signals from the sensor interface, the at least one processor being further configured to modify the at least one complex stimulation pattern by performing a machine learning method implementing a Gaussian Process Optimization operable to determine the stimulation parameters delivered by the stimulation assembly based on the signals received from the sensor interface. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A system for use with a subject having a spinal cord, and one or more sensors positioned to collect physiological data related to the subject, the system comprising:
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a plurality of electrodes arranged in an electrode array implantable adjacent to the spinal cord of the subject at a location below a lesion of the spinal cord; a neurostimulator device connected to the plurality of electrodes and configured to deliver complex stimulation patterns thereto; and a computing device configured to transmit stimulation parameters to the neurostimulator device, the neurostimulator device being configured to generate the complex stimulation patterns based at least in part on the stimulation parameters received from the computing device, the computing device being further configured to determine the stimulation parameters based on at least in part on the physiological data collected by the one or more sensors, wherein the computing device is configured to perform a machine learning method implementing a Gaussian Process Optimization operable to determine the stimulation parameters, wherein the one or more sensors are selected from an electromyography sensor, an evoked potential sensor, a joint angle sensor, a flex sensor, an accelerometer, a gyroscope sensor, a flow sensor, a pressure sensor, a load sensor, a temperature sensor, or a combination thereof. - View Dependent Claims (13, 14, 15, 16, 17, 18, 19, 20)
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21. A system including a network, a subject having a spinal cord, and one or more sensors positioned to collect physiological data related to the subject, the system comprising:
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a plurality of electrodes arranged in an electrode array implantable on the spinal cord or adjacent to the spinal cord of the subject at a location below a lesion of the spinal cord or nervous system; a neurostimulator device connected to the plurality of electrodes and configured to deliver complex stimulation patterns thereto; a first computing device connected to the network and configured to transmit stimulation parameters to the neurostimulator device, the neurostimulator device being configured to generate the complex stimulation patterns based at least in part on the stimulation parameters received from the first computing device, wherein the first computing device is configured to perform a machine learning method implementing a Gaussian Process Optimization operable to determine the stimulation parameters; and a remote second computing device connected to the network, the first computing device being configured to transmit the physiological data collected by the one or more sensors to the second computing device, the second computing device being configured to determine the stimulation parameters based at least in part on the physiological data collected by the one or more sensors, and transmit the stimulation parameters to the first computing device, wherein the one or more sensors are selected from an electromyography sensor, an evoked potential sensor, a joint angle sensor, a flex sensor, an accelerometer, a gyroscope sensor, a flow sensor, a pressure sensor, a load sensor, a temperature sensor, or a combination thereof. - View Dependent Claims (22, 23)
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Specification