Abstract: Methods and systems for testing and treating spinal cord stimulation (SCS) patients are disclosed. Patients are eventually treated with sub-perception (paresthesia free) therapy. However, supra-perception stimulation is used during “sweet spot searching” during which active electrodes are selected for the patient. This allows sweet spot searching to occur much more quickly and without the need to wash in the various electrode combinations that are tried. After selecting electrodes using supra-perception therapy, therapy is titrated to sub-perception levels using the selected electrodes. Such sub-perception therapy has been investigated using pulses at or below 10 kHz, and it has been determined that a statistically significant correlation exists between pulse width (PW) and frequency (F) in this frequency range at which SCS patients experience significant reduction in symptoms such as back pain.

Abstract: This document discusses, among other things, systems and methods for managing pain of a subject. A system includes a first sensor circuit to sense a first signal indicative of a functional state of the subject, a second sensor circuit to sense a second signal different from the first signal, and a controller circuit. The controller circuit may determine an operating mode of the second sensor circuit according to the sensed first signal, trigger the second senor circuit to sense the second signal under the determined operating mode, and generate a pain score using at least the second signal sensed under the determined operating mode. The pain score may be output to a patient or used for closed-loop control of a pain therapy.

Abstract: This document discusses, among other things, systems and methods for managing pain of a subject. A system includes a first sensor circuit to sense a first signal indicative of a functional state of the subject, a second sensor circuit to sense a second signal different from the first signal, and a controller circuit. The controller circuit may determine an operating mode of the second sensor circuit according to the sensed first signal, trigger the second senor circuit to sense the second signal under the determined operating mode, and generate a pain score using at least the second signal sensed under the determined operating mode. The pain score may be output to a patient or used for closed-loop control of a pain therapy.

Abstract: Methods and systems for testing and treating spinal cord stimulation (SCS) patients are disclosed. Patients are eventually treated with sub-perception (paresthesia free) therapy. However, supra-perception stimulation is used during “sweet spot searching” during which active electrodes are selected for the patient. This allows sweet spot searching to occur much more quickly and without the need to wash in the various electrode combinations that are tried. After selecting electrodes using supra-perception therapy, therapy is titrated to sub-perception levels using the selected electrodes. Such sub-perception therapy has been investigated using pulses at or below 10 kHz, and it has been determined that a statistically significant correlation exists between pulse width (PW) and frequency (F) in this frequency range at which SCS patients experience significant reduction in symptoms such as back pain.

Abstract: Systems and methods for managing pain in patient are described. A system may include sensors configured to sense physiological or functional signals, and a pain analyzer to generate signal metrics from the physiological or functional signals. The pain analyzer also generates weight factors corresponding to the signal metrics. The weight factors may indicate the signal metrics reliability in representing an intensity of the pain. The pain analyzer generates a pain score using a plurality of signal metrics and a plurality of weight factors. The pain score may be output to a user or a process. The system may additionally include an electrostimulator to generate and deliver closed-loop pain therapy according to the pain score.

Abstract: This document discusses, among other things, systems and methods for managing pain of a subject. A system includes one or more physiological sensors configured to sense a physiological signal indicative of patient brain activity. The physiological signals may include an electroencephalography signal, a magnetoencephalography signal, or a brain-evoked potential. The system may extract from the brain activity signal one or more signal metrics indicative of strength or pattern of brain electromagnetic activity associated with pain, and generate a pain score using the one or more signal metrics. The pain score can be output to a patient or a process. The system may select an electrode configuration for pain-relief electrostimulation based on the pain score, and deliver a closed-loop pain therapy according to the selected electrode configuration.

Abstract: An example of a system for managing pain may include a pain monitoring circuit, a pain relief device, and a control circuit. The pain monitoring circuit may include a parameter analyzer and a pain score generator. The parameter analyzer may be configured to receive and analyze at least two parameters selected from a physiological parameter indicative of a physiological function or state of a patient, a functional parameter indicative of a physical activity or state of the patient, or a patient parameter including subjective information provided by the patient. The pain score generator may be configured to compute a composite pain score using an outcome of the analysis. The composite pain score may indicate a degree of the pain. The pain relief device may be configured to deliver a pain-relief therapy. The control circuit may be configured to control the delivery of the pain-relief therapy using the composite pain score.

Abstract: An example of a system may include a processor and a memory device comprising instructions, which when executed by the processor, cause the processor to: access a patient metric of a subject; use the patient metric as an input to a machine learning algorithm, the machine learning algorithm to search a plurality of neuromodulation parameter sets and to identify a candidate neuromodulation parameter set of the plurality of neuromodulation parameter sets, the candidate neuromodulation parameter set designed to produce a non-regular waveform that varies over a time domain and a space domain; and program a neuromodulator using the candidate neuromodulation parameter set to stimulate the subject.

Abstract: An Example of a system for providing a patient with pain management may include a sleep monitoring circuit, a pain relief device, and a control circuit. The sleep monitoring circuit may be configured to sense one or more sleep signals from the patient and to determine a sleep state of the patient using the one or more sleep signals. The one or more sleep signals may include one or more physiological signals corresponding to the sleep state of the patient. The pain relief device may be configured to deliver one or more pain relief therapies. The control circuit may be configured to control the delivery of the one or more pain relief therapies using therapy parameters and to adjust the therapy parameters based on the determined sleep state.

Abstract: An example of a system may include a processor and a memory device comprising instructions, which when executed by the processor, cause the processor to: access a patient metric of a subject; use the patient metric as an input to a machine learning algorithm, the machine learning algorithm to search a plurality of neuromodulation parameter sets and to identify a candidate neuromodulation parameter set of the plurality of neuromodulation parameter sets, the candidate neuromodulation parameter set designed to produce a non-regular waveform that varies over a time domain and a space domain; and program a neuromodulator using the candidate neuromodulation parameter set to stimulate the subject.

Abstract: This document discusses, among other things, systems and methods for managing pain in a subject. A system may include one or more sensors configured to sense from the subject information corresponding to emotional reaction to pain, such as emotional expression. The emotional expression includes facial or vocal expression. A pain analyzer circuit may generate a pain score using signal metrics of facial or vocal expression extracted from the sensed information. The pain score may be output to a user or a process. The system may additionally include a neurostimulator that can adaptively control the delivery of pain therapy by automatically adjusting stimulation parameters based on the pain score.

Abstract: This document discusses, among other things, systems and methods for managing pain of a subject. A system includes one or more physiological sensors configured to sense a physiological signal indicative of patient brain activity. The physiological signals may include an electroencephalography signal, a magnetoencephalography signal, or a brain-evoked potential. The system may extract from the brain activity signal one or more signal metrics indicative of strength or pattern of brain electromagnetic activity associated with pain, and generate a pain score using the one or more signal metrics. The pain score can be output to a patient or a process. The system may select an electrode configuration for pain-relief electrostimulation based on the pain score, and deliver a closed-loop pain therapy according to the selected electrode configuration.

Abstract: Methods and systems for proving spinal cord stimulation (SCS) for treating pain in a patient are described. Embodiments of the described methods and systems can provide sub-perception SCS that has a fast wash-in time by using stimulation parameters that activate surround inhibition in the patient. Measuring retrograde potentials evoked by the stimulation can be performed to facilitate choosing the best stimulation parameters, in particular, the best stimulating electrode contact configurations for activating surround inhibition. For example, peripheral electrodes may be placed at the center of the patient's pain (within a local receptive field (LRF), with respect to the patient's pain center) and within an area surrounding the patient's pain center (within a surrounding receptive field (SRF), with respect to the patient's pain center). Retrograde evoked potentials measured and the SRF and/or the LRF can be used to guide the selection of the stimulation parameters.

Abstract: This document discusses, among other things, systems and methods for managing pain in a subject. A system may include one or more sensors configured to sense from the subject information corresponding to emotional reaction to pain, such as emotional expression. The emotional expression includes facial or vocal expression. A pain analyzer circuit may generate a pain score using signal metrics of facial or vocal expression extracted from the sensed information. The pain score may be output to a user or a process. The system may additionally include a neurostimulator that can adaptively control the delivery of pain therapy by automatically adjusting stimulation parameters based on the pain score.

Abstract: This document discusses, among other things, systems and methods for managing pain of a subject. A system includes one or more physiological sensors configured to sense a physiological signal indicative of patient brain activity. The physiological signals may include an electroencephalography signal, a magnetoencephalography signal, or a brain-evoked potential. The system may extract from the brain activity signal one or more signal metrics indicative of strength or pattern of brain electromagnetic activity associated with pain, and generate a pain score using the one or more signal metrics. The pain score can be output to a patient or a process. The system may select an electrode configuration for pain-relief electrostimulation based on the pain score, and deliver a closed-loop pain therapy according to the selected electrode configuration.

Abstract: This document discusses, among other things, systems and methods for managing pain of a subject. A system includes a first sensor circuit to sense a first signal indicative of a functional state of the subject, a second sensor circuit to sense a second signal different from the first signal, and a controller circuit. The controller circuit may determine an operating mode of the second sensor circuit according to the sensed first signal, trigger the second senor circuit to sense the second signal under the determined operating mode, and generate a pain score using at least the second signal sensed under the determined operating mode. The pain score may be output to a patient or used for closed-loop control of a pain therapy.

Abstract: Systems and methods for managing pain in patient are described. A system may include sensors configured to sense physiological or functional signals, and a pain analyzer to generate signal metrics from the physiological or functional signals. The pain analyzer also generates weight factors corresponding to the signal metrics. The weight factors may indicate the signal metrics reliability in representing an intensity of the pain. The pain analyzer generates a pain score using a plurality of signal metrics and a plurality of weight factors. The pain score may be output to a user or a process. The system may additionally include an electrostimulator to generate and deliver closed-loop pain therapy according to the pain score.

Abstract: Systems and methods for managing pain in patient are described. A system may include sensors configured to sense physiological or functional signals, and a pain analyzer to generate signal metrics from the physiological or functional signals. The pain analyzer also generates weight factors corresponding to the signal metrics. The weight factors may indicate the signal metrics reliability in representing an intensity of the pain. The pain analyzer generates a pain score using a plurality of signal metrics and a plurality of weight factors. The pain score may be output to a user or a process. The system may additionally include an electrostimulator to generate and deliver closed-loop pain therapy according to the pain score.

Abstract: This document discusses, among other things, systems and methods for managing pain of a subject. A system includes a first sensor circuit to sense a first signal indicative of a functional state of the subject, a second sensor circuit to sense a second signal different from the first signal, and a controller circuit. The controller circuit may determine an operating mode of the second sensor circuit according to the sensed first signal, trigger the second senor circuit to sense the second signal under the determined operating mode, and generate a pain score using at least the second signal sensed under the determined operating mode. The pain score may be output to a patient or used for closed-loop control of a pain therapy.

Abstract: This document discusses, among other things, systems and methods for managing pain of a subject. A system may include a motion sensor configured to sense at least one functional signal indicative a physical state of the subject. The at least one functional signal may include at least one motor activity signal or at least one sleep state signal. A pain analyzer circuit may extract, from the functional signal, signal metrics indicative of subject motor control or kinetics, and generate a pain score using the signal metrics. The pain score may be output to a user or a process. The system may additionally include an electrostimulator to generate and deliver a closed-loop pain therapy according to the pain score.