摘要:
A system includes one or more sensors and a processor. Each of the sensors generates a signal as a function of at least one physiological parameter of a patient that may discernibly change when the patient is asleep. The processor monitors the physiological parameters, and determines whether the patient is asleep based on the parameters. In some embodiments, the processor determines plurality of sleep metric values, each of which indicates a probability of the patient being asleep, based on each of a plurality of physiological parameters. The processor may average or otherwise combine the plurality of sleep metric values to provide an overall sleep metric value that is compared to a threshold value in order to determine whether the patient is asleep. In addition, an electroencephalogram signal may be used to identify sleep states of the patient.
摘要:
Techniques for controlling delivery of a therapy to a patient by a medical device, such as an implantable medical device (IMD), involve a sensitivity analysis of a performance metric. The performance metric may relate to efficacy or side effects of the therapy. For example, the performance metric may comprise a sleep quality metric, an activity level metric, a movement disorder metric for patients with Parkinson's disease, epilepsy, or the like. The sensitivity analysis identifies values of therapy parameters that defines a substantially maximum or minimum value of the performance metric. The identified therapy parameters are a baseline therapy parameter set, and a medical device may control delivery of the therapy based on the baseline therapy parameter set.
摘要:
A system includes one or more sensors and a processor. Each of the sensors generates a signal as a function of at least one physiological parameter of a patient that may discernibly change when the patient is asleep. The processor monitors the physiological parameters, and determines whether the patient is asleep based on the parameters. In some embodiments, the processor determines plurality of sleep metric values, each of which indicates a probability of the patient being asleep, based on each of a plurality of physiological parameters. The processor may average or otherwise combine the plurality of sleep metric values to provide an overall sleep metric value that is compared to a threshold value in order to determine whether the patient is asleep. In addition, an electroencephalogram signal may be used to identify sleep states of the patient.
摘要:
A medical device, such as an implantable medical device (IMD), determines values for one or more metrics that indicate the quality of a patient's sleep, and controls delivery of a therapy based on the sleep quality metric values. For example, the medical device may compare a sleep quality metric value with one or more threshold values, and adjust the therapy based on the comparison. In some embodiments, the medical device adjusts the intensity of therapy based on the comparison, e.g., increases the therapy intensity when the comparison indicates that the patient's sleep quality is poor. In some embodiments, the medical device automatically selects one of a plurality of therapy parameter set available for use in delivering therapy based on a comparison sleep quality metric values associated with respective therapy parameter sets within the plurality of available therapy parameter sets.
摘要:
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.
摘要:
A device, such as an implantable medical device (IMD), programming device, or other computing device determines when a patient is attempting to sleep. When the device determines that the patient is attempting to sleep, the device determines values for one or more metrics that indicate the quality of a patient's sleep based on at least one physiological parameter of the patient. When the device determines that the patient is not attempting to sleep, the device periodically determines activity levels of the patient. Activity metric values may be determined based on the determined activity levels. A clinician may use sleep quality information and patient activity information presented by a programming device to, for example, evaluate the effectiveness of therapy delivered to the patient by a medical device.
摘要:
A system includes one or more sensors and a processor. Each of the sensors generates a signal as a function of at least one physiological parameter of a patient that may discernibly change when the patient is asleep. The processor monitors the physiological parameters, and determines whether the patient is asleep based on the parameters. In some embodiments, the processor determines plurality of sleep metric values, each of which indicates a probability of the patient being asleep, based on each of a plurality of physiological parameters. The processor may average or otherwise combine the plurality of sleep metric values to provide an overall sleep metric value that is compared to a threshold value in order to determine whether the patient is asleep. In addition, an electroencephalogram signal may be used to identify sleep states of the patient.
摘要:
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.
摘要:
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.
摘要:
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.