Abstract: An example method includes determining, by an implantable medical device (IMD), an electrode of a plurality of electrodes of a lead to be used to deliver electrical stimulation to a patient at a particular time; selecting, by the IMD and based on the determined electrode, a set of electrodes of the plurality of electrodes; and sensing, by the IMD and via the selected set of electrodes, electrical signals of the patient at the particular time.

Abstract: A device includes one or more processors configured to generate simulation data by providing first sets of first values of first input parameters to a simulation of a physical system. The processors are configured to develop at least one surrogate model based on the simulation data, and to select second input parameters from the first input parameters based on the at least one surrogate model. A count of the second input parameters is less than a count of the first input parameters. The processors are configured to generate second simulation data by providing second sets of second values of the second input parameters to the simulation. The processors are configured to develop at least a second surrogate model based on the second simulation data.

Abstract: An example method for controlling delivery of electrical stimulation therapy includes maintaining, by one or more processors of a medical device configured to deliver electrical stimulation to a patient, a counter tied to a clock used by the medical device to deliver the electrical stimulation to the patient; and obtaining, by the one or more processors, one or more representations of sensed electrical signals for the patient that are referenced to counts of the counter. In this example, the method also includes identifying, based on the one or more representations of the sensed electrical signals for the patient, a count of the counter at which stimulation is to be delivered to the patient; and delivering, by the medical device and to the patient, electrical stimulation based on the identified count of the counter.

Abstract: An apparatus for storing data records associated with a medical monitoring event in a data structure. An implanted device obtains data and stores the data in the data record in a first data structure that is age-based. Before an oldest data record is lost, the oldest data record may be stored in a second data structure that is priority index-based. The priority index may be determined by a severity level and may be further determined by associated factors. The implanted device may organize, off-load, report, and/or display a plurality of data records based on an associated priority index. Additionally, the implanted device may select a subset or composite of physiologic channels from the available physiologic channels based on a selection criterion.

Abstract: Methods for storing data records associated with a medical monitoring event in a data structure. An implanted device obtains data and stores the data in the data record in a first data structure that is age-based. Before an oldest data record is lost, the oldest data record may be stored in a second data structure that is priority index-based. The priority index may be determined by a severity level and may be further determined by associated factors. The implanted device may organize, off-load, report, and/or display a plurality of data records based on an associated priority index. Additionally, the implanted device may select a subset or composite of physiologic channels from the available physiologic channels based on a selection criterion.

Abstract: An example method for controlling delivery of electrical stimulation therapy includes maintaining, by one or more processors of a medical device configured to deliver electrical stimulation to a patient, a counter tied to a clock used by the medical device to deliver the electrical stimulation to the patient; and obtaining, by the one or more processors, one or more representations of sensed electrical signals for the patient that are referenced to counts of the counter. In this example, the method also includes identifying, based on the one or more representations of the sensed electrical signals for the patient, a count of the counter at which stimulation is to be delivered to the patient; and delivering, by the medical device and to the patient, electrical stimulation based on the identified count of the counter.

Abstract: Various embodiments concern identifying a biomarker in the presence of electrical stimulation. Various embodiments concern delivering electrical stimulation to a patient and sensing one or more signals while the electrical stimulation is being delivered, the one or more signals including data indicative of physiological activity. Various embodiments further include determining an intensity of the electrical stimulation and determining whether the data indicates the presence of a biomarker based on a variable threshold, the variable threshold being variable based on the intensity of the electrical stimulation. Various embodiments concern determining a relationship between stimulation intensity and a biomarker parameter to determine the variability of the variable threshold.

Abstract: This disclosure describes techniques for controlling spectral aggressors in a sensing device that uses a chopper amplifier to amplify an input signal prior to sampling the signal. In some examples, the techniques for controlling spectral aggressors may include generating a chopper-stabilized amplified version of an input signal based on a chopper frequency, sampling the chopper-stabilized amplified version of the input signal at a sampling rate to generate a sampled signal, and analyzing a target frequency band of the sampled signal. The chopper frequency and the sampling rate may cause spectral interference that is generated due to the chopper frequency to occur in the sampled signal at one or more frequencies that are outside of the target frequency band of the sampled signal. The techniques for controlling spectral aggressors may reduce the noise caused by the chopper frequency in the resulting sampled signal, thereby improving the quality of the signal.

Abstract: This disclosure describes techniques for controlling spectral aggressors in a sensing device that uses a low power sleep mode to manage the power consumed by the device. In some examples, the techniques for controlling spectral aggressors may include configuring one or more of an algorithm processing rate for a processor, a buffering rate for the processor, a sampling rate for an analog-to-digital converter, an execution unit processing rate for the processor, and an algorithm subdivision factor for the processor such that spectral interference caused by a sleep cycle rate of the processor occurs outside of one or more target frequency bands of a sampled signal. The techniques of this disclosure may be used to reduce noise in a sensing system that uses a low power sleep mode to manage the power consumed by the device.

Abstract: Methods and apparatus for storing data records associated with a medical monitoring event in a data structure. These include initiating loop recording in an implantable medical device upon determination of a neurological event, wherein loop recording comprises storing a data record of a plurality of data records in a data structure, the plurality of data records representing information about determined neurological events. Methods and apparatus can further include determining a priority index for the plurality of data records based on severity levels of the determined neurological events and replacing older data records of the plurality of data records on the data structure with new data records according to the priority index, wherein the new data records selectively replace those data records in the data structure having the lowest associated priority index.

Abstract: This disclosure describes a state machine framework for programming closed-loop algorithms that control the delivery of therapy to a patient by an implantable medical device (IMD). The state machine framework may use one or more programmable state parameters to define at least part of a structure of a state machine that generates one or more therapy decisions based on one or more sensed states of the patient. The state machine framework may include a state machine runtime environment that executes on an IMD and that is configurable to implement a variety of different state machines depending on programmable state parameters that are received from an external device. The techniques of this disclosure may, in some cases, allow IMD developers and/or users to program, change, and/or download new closed-loop control policy algorithms during the lifespan of the IMD without requiring new firmware code to be downloaded onto the IMD.

Abstract: Apparatus and method detect a detection cluster that is associated with a neurological event, such as a seizure, of a nervous system disorder and update therapy parameters that are associated with a treatment therapy. The occurrence of the detection cluster is detected when the maximal ratio exceeds an intensity threshold. If the maximal ratio drops below the intensity threshold for a time interval that is less than a time threshold and subsequently rises above the intensity threshold, the subsequent time duration is considered as being associated with the detection cluster rather than being associated with a different detection cluster. Consequently, treatment of the nervous system disorder during the corresponding time period is in accordance with one detection cluster. Treatment therapy may be provided by providing electrical stimulation, drug infusion or a combination.

Abstract: Bioelectrical signals may be sensed within a brain of a patient with a plurality of sense electrode combinations. A stimulation electrode combination for delivering stimulation to the patient to manage a patient condition may be selected based on the frequency band characteristics of the sensed signals. In some examples, a stimulation electrode combination associated with the sense electrode combination that sensed a bioelectrical brain signal having a relatively highest relative beta band power level may be selected to deliver stimulation therapy to the patient. Other frequency bands characteristics may also be used to select the stimulation electrode combination.

Abstract: Bioelectrical signals may be sensed within a brain of a patient with a plurality of sense electrode combinations. A stimulation electrode combination for delivering stimulation to the patient to manage a patient condition may be selected based on the frequency band characteristics of the sensed signals. In some examples, a stimulation electrode combination associated with the sense electrode combination that sensed a bioelectrical brain signal having a relatively highest relative beta band power level may be selected to deliver stimulation therapy to the patient. Other frequency bands characteristics may also be used to select the stimulation electrode combination.

Abstract: Methods and apparatus for storing data records associated with a medical monitoring event in a data structure. These include initiating loop recording in an implantable medical device upon determination of a neurological event, wherein loop recording comprises storing a data record of a plurality of data records in a data structure, the plurality of data records representing information about determined neurological events. Methods and apparatus can further include determining a priority index for the plurality of data records based on severity levels of the determined neurological events and replacing older data records of the plurality of data records on the data structure with new data records according to the priority index, wherein the new data records selectively replace those data records in the data structure having the lowest associated priority index.

Abstract: This disclosure describes a state machine framework for programming closed-loop algorithms that control the delivery of therapy to a patient by an implantable medical device (IMD). The state machine framework may use one or more programmable state parameters to define at least part of a structure of a state machine that generates one or more therapy decisions based on one or more sensed states of the patient. The state machine framework may include a state machine runtime environment that executes on an IMD and that is configurable to implement a variety of different state machines depending on programmable state parameters that are received from an external device. The techniques of this disclosure may, in some cases, allow IMD developers and/or users to program, change, and/or download new closed-loop control policy algorithms during the lifespan of the IMD without requiring new firmware code to be downloaded onto the IMD.

Abstract: Apparatus and method detect a detection cluster that is associated with a neurological event, such as a seizure, of a nervous system disorder and update therapy parameters that are associated with a treatment therapy. The occurrence of the detection cluster is detected when the maximal ratio exceeds an intensity threshold. If the maximal ratio drops below the intensity threshold for a time interval that is less than a time threshold and subsequently rises above the intensity threshold, the subsequent time duration is considered as being associated with the detection cluster rather than being associated with a different detection cluster. Consequently, treatment of the nervous system disorder during the corresponding time period is in accordance with one detection cluster. Treatment therapy may be provided by providing electrical stimulation, drug infusion or a combination.

Abstract: This disclosure describes techniques for controlling spectral aggressors in a sensing device that uses a low power sleep mode to manage the power consumed by the device. In some examples, the techniques for controlling spectral aggressors may include configuring one or more of an algorithm processing rate for a processor, a buffering rate for the processor, a sampling rate for an analog-to-digital converter, an execution unit processing rate for the processor, and an algorithm subdivision factor for the processor such that spectral interference caused by a sleep cycle rate of the processor occurs outside of one or more target frequency bands of a sampled signal. The techniques of this disclosure may be used to reduce noise in a sensing system that uses a low power sleep mode to manage the power consumed by the device.

Abstract: This disclosure describes techniques for controlling spectral aggressors in a sensing device that uses a chopper amplifier to amplify an input signal prior to sampling the signal. In some examples, the techniques for controlling spectral aggressors may include generating a chopper-stabilized amplified version of an input signal based on a chopper frequency, sampling the chopper-stabilized amplified version of the input signal at a sampling rate to generate a sampled signal, and analyzing a target frequency band of the sampled signal. The chopper frequency and the sampling rate may cause spectral interference that is generated due to the chopper frequency to occur in the sampled signal at one or more frequencies that are outside of the target frequency band of the sampled signal. The techniques for controlling spectral aggressors may reduce the noise caused by the chopper frequency in the resulting sampled signal, thereby improving the quality of the signal.

Abstract: Methods and apparatus for storing data records associated with a medical monitoring event in a data structure. These include initiating loop recording in an implantable medical device upon determination of a neurological event, wherein loop recording comprises storing a data record of a plurality of data records in a data structure, the plurality of data records representing information about determined neurological events. Methods and apparatus can further include determining a priority index for the plurality of data records based on severity levels of the determined neurological events and replacing older data records of the plurality of data records on the data structure with new data records according to the priority index, wherein the new data records selectively replace those data records in the data structure having the lowest associated priority index.