Medtronic, Inc.

Jonathan C Werder

Nina M Graves

Jonathon E Giftakis

Eric J Panken

David L Carlson

Touby Austin Drew

Keith Alan Miesel

Kenneth Timothy Heruth

Steve R LaPorte

Mark G Frei

Ivan Osorio

David C Ullestad

Gregory F Molnar

Naresh C Bhavaraju

Thomas E Peters

David L Thompson

Timothy J Denison

John Louis Sommer

Gregory John Haubrich

Eric H Bonde

Warren W Ball

Steven D Goedeke

Peter Joseph Kovach

Sarah B Alme

Eric V Blaha

Ryan Cobian

Nels Nerison

Carl D Wahlstrand

Steven Streatfield Gill

Mark S Lent

Mark Turner Rise

Paul H Stypulkowski

Douglas N Hess

Kevin J Kelly

Gabriela C Miyazawa

Elisabeth Lacy Belden

Matthew J Michaels

Todd D Heathershaw

Scott F Schaffner

Michele H Herzog

Leslie A LeMire

David I Carlson

E Jonathon Giftakis

An indication that a patient event occurred may be used to evaluate the efficacy of at least one therapy program and/or adjust therapy delivery to the patient. In some examples, the patient event indication includes patient input that may be received via an event indication button of a programming device. In some examples, therapy delivery may be adjusted by adjusting at least one therapy parameter value, switching therapy programs or therapy program groups or restarting a therapy cycle of a medical device.

Therapy adjustment

Therapy adjustment based on patient event indication

A device determines values for one or more metrics that indicate the quality of a patient's sleep based on sensed physiological parameter values. Sleep efficiency, sleep latency, and time spent in deeper sleep states are example sleep quality metrics for which values may be determined. The sleep quality metric values may be used, for example, to evaluate the effectiveness of a therapy delivered to the patient by a medical device. In some embodiments, determined sleep quality metric values are automatically associated with the therapy parameter sets according to which the medical device delivered the therapy when the physiological parameter values were sensed, and used to evaluate the effectiveness of the various therapy parameter sets. The medical device may deliver the therapy to treat a non-respiratory neurological disorder, such as epilepsy, a movement disorder, or a psychological disorder. The therapy may be, for example, deep brain stimulation (DBS) therapy.

Determination of sleep quality for neurological disorders

Intracranial pressure of a patient may be monitored in order to evaluate a seizure disorder. In some examples, trends in the intracranial pressure over time may be monitored, e.g., to detect changes to the patient's condition. In addition, in some examples, a seizure metric may be generated for a detected seizure based on sensed intracranial pressures. The seizure metric may indicate, for example, an average, median, or highest relative intracranial pressure value observed during a seizure, a percent change from a baseline value during the seizure, or the time for the intracranial pressure to return to a baseline state after the occurrence of a seizure. In addition to or instead of intracranial pressure, patient motion or posture may be monitored in order to assess the patient's seizure disorder. For example, a seizure type or severity may be determined based on patient motion sensed during a seizure.

Seizure disorder evaluation based on intracranial pressure and patient motion

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.

Apparatus for data retention in an implantable medical device

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.

Methods for data retention in an implantable medical device

An indication that a patient event occurred may be used to evaluate the efficacy of at least one therapy program and/or adjust therapy delivery to the patient. In some examples, the patient event indication includes patient input that may be received via an event indication button of a programming device. In addition to or instead of the patient input, the patient event indication may be generated based on a physiological parameter of the patient. In some examples, therapy delivery may be adjusted by adjusting at least one therapy parameter value, switching therapy programs or therapy program groups or restarting a therapy cycle of a medical device. The patient input via an event indication button may also help evaluate whether a therapy system is useful for the patient.

Patient event indication

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.

Techniques for data retention upon detection of an event in an implantable medical device

An implantable medical device such as an implantable pulse generator that includes EEG sensing for monitoring and treating neurological conditions, and leadless ECG sensing for monitoring cardiac signals. The device includes a connector block with provisions for cardiac leads which may be used/enabled when needed. If significant co-morbid cardiac events are observed in patients via the leadless ECG monitoring, then cardiac leads may be subsequently connected for therapeutic use.

Implantable medical device for treating neurological conditions including ECG sensing

Implantable medical devices switch from a constant current mode of operation to a constant voltage mode of operation. The switching may be based on the device determining that tissue impedance stability has occurred. The determination may be a measurement of output voltage stability of the constant current source or based on other factors such as an amount of time that has elapsed. The switching may be as the result of an externally generated request such as by a clinician via an external device. The implantable medical device may begin constant voltage mode by utilizing stimulation parameters based on those initially programmed for constant current mode and based upon a measurement of voltage amplitude being output by the constant current source prior to the switch.

Stimulation mode switching based on tissue impedance stability

Methods of generating an extended cluster are disclosed. A first cluster including data representative of a first signal indicative of an abnormal physiological symptom is generated. A second signal is detected as representing a second abnormal physiological symptom and the second abnormal physiological symptom continues after the first abnormal physiological symptom ends. An extended cluster including the data from the first signal and the second signal is generated that extends from the time when the first abnormal physiological symptom occurs to the time when the second abnormal physiological symptom ends. The first and the extended cluster may include data of both the first and second signals the entire period of the clusters. If desired, the first signal or the second signal may be provided from a sensor implanted in a patient's brain tissue.

Clustering with combined physiological signals

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Corcoran, MN, United States of America

Jonathan C Werder