Patent Grant
11738197
Many patients benefit from therapy provided by an implantable medical device. For example, a portion of the population suffers from various forms of sleep disorder breathing (SDB). In some patients, external breathing therapy devices and/or mere surgical interventions may fail to treat the sleep disordered breathing behavior. With these and other implantable medical device therapy applications, operation of such systems can be improved with reference to sensed patient information.
In the following detailed description, reference is made to the accompanying drawings which form a part hereof, and in which is shown by way of illustration specific examples in which the disclosure may be practiced. It is to be understood that other examples may be utilized and structural or logical changes may be made without departing from the scope of the present disclosure. The following detailed description, therefore, is not to be taken in a limiting sense. It is to be understood that features of the various examples described herein may be combined, in part or whole, with each other, unless specifically noted otherwise.
At least some examples of the present disclosure are directed to systems and devices for diagnosis, therapy and/or other care of medical conditions. At least some examples may comprise implantable devices and/or methods comprising use of implantable devices.
At least some examples of present disclosure are directed to systems and methods for controlling at least one function or operation of an implantable medical device system, including an implantable medical device implanted within a patient, based upon sensed posture information of the patient. In some embodiments, one or more sensors implanted in the patient are utilized to sense or detect the posture information of the patient. In some embodiments, the operations of the implantable medical device system that are controlled in response to the sensed posture information relate to an operational mode of the implantable medical device in delivering therapy to the patient. In some embodiments, the systems and methods of the present disclosure incorporate one or more algorithms that result in an action being taken in response to a determination that the patient is in a designated posture or a determination that the probability the patient is in a designated posture is above a threshold; in other embodiments, the system and methods of the present disclosure incorporate one or more algorithms that result in an action being taken in response to a determination that the patient is not in a designated posture or a determination that the probability the patient is not in a designated posture is above a threshold. In some embodiments, the operations of the implantable medical device system that are controlled in response to the sensed posture information relate to determining or designating a current posture of the patient. In some embodiments, the operations of the implantable medical device system that are controlled in response to the sensed posture information relate to determining or designating that a current posture of the patient is not a designated or particular posture. In some embodiments, the operations of the implantable medical device system that are controlled in response to the sensed posture information relate to calibrating information signaled by one or more sensors. In some embodiments, the operations of the implantable medical device system that are controlled in response to the sensed posture information relate to generating information or data for review by the patient and/or caregiver.
In some examples, the systems and methods of the present disclosure are configured and used for sleep disordered breathing (SDB) therapy, such as obstructive sleep apnea (OSA) therapy, which may comprises monitoring, diagnosis, and/or stimulation therapy. However, in other examples, the system is used for other types of therapy, including, but not limited to, other types of neurostimulation or cardiac therapy. In some embodiments, such other implementations include therapies, such as but not limited to, central sleep apnea, complex sleep apnea, cardiac disorders, pain management, seizures, deep brain stimulation, and respiratory disorders.
One example of a patient therapy system 20 in accordance with principles of the present disclosure is schematically represented in
In some embodiments, the stimulation lead 54 includes a lead body 80 with a distally located stimulation electrode 82. At an opposite end of the lead body 80, the stimulation lead 54 includes a proximally located plug-in connector 84 which is configured to be removably connectable to the interface block 66 (e.g., the interface block 66 can optionally include or provide a stimulation port sized and shaped to receive the plug-in connector 84 as is known in the art).
In general terms, the stimulation electrode 82 can optionally be a cuff electrode, and can include some non-conductive structures biased to (or otherwise configurable to) releasable secure the stimulation electrode 82 about a target nerve. Other formats are also acceptable. Moreover, the stimulation electrode 82 can include an array of electrode bodies to deliver a stimulation signal to a target nerve. In some non-limiting embodiments, the stimulation electrode 82 can comprise at least some of substantially the same features and attributes as described within at least U.S. Pat. No. 8,340,785 issued Dec. 25, 2012 and/or U.S. Patent Application Publication No. 2011/0147046 published Jun. 23, 2011 the entire teachings of each of which are incorporated herein by reference in their entireties.
In some examples, the lead body 80 is a generally flexible elongate member having sufficient resilience to enable advancing and maneuvering the lead body 80 subcutaneously to place the stimulation electrode 82 at a desired location adjacent a nerve, such as an airway-patency-related nerve (e.g. hypoglossal nerve, vagus nerve, etc.). In some examples, such as in the case of obstructive sleep apnea, the nerves may include (but are not limited to) the nerve and associated muscles responsible for causing movement of the tongue and related musculature to restore airway patency. In some examples, the nerves may include (but are not limited to) the hypoglossal nerve and the muscles may include (but are not limited to) the genioglossus muscle. In some examples, lead body 80 can have a length sufficient to extend from the IPG assembly 52 implanted in one body location (e.g. pectoral) and to the target stimulation location (e.g. head, neck). Upon generation via the circuitry 62, a stimulation signal is selectively transmitted to the interface block 68 for delivery via the stimulation lead 54 to such nerves.
Returning to
The implantable sensor 32 can be connected to the IMD 30 in various fashions. For example, and with additional reference to the IMD 50 of
Alternatively, and as reflected by the block diagram of
In some embodiments, in order for the motion-based transducer-type implantable sensor 32 to fit on top of (e.g. next to) the housing 60 of the IPG assembly 52, a housing of the implantable sensor 32 has a size and shape that can maintain the motion-based transducer sensor component in a fixed orientation relative to the IPG assembly 52. This arrangement facilitates achieving and maintaining a proper orientation of the multiple orthogonal axes of the motion-based transducer sensor component relative to various axes of the patient's body, such as an anterior-posterior axis.
In related embodiments, and as reflected by the block diagram of
In yet other embodiments, the implantable sensor 32 can be incorporated into a structure of the stimulation lead 54. For example,
In yet other embodiments, the implantable sensor 32 can be wirelessly connected to the IMD 30. For example,
Regardless of how the implantable sensor 32 is associated with the IPG assembly 52, in some embodiments the implantable sensor 32 is configured to generate information indicative of sensed forces in three directions or axes. For example, in some embodiments, the implantable sensor 32 is a three-axis accelerometer that can sense or measure the static and/or dynamic forces of acceleration on three axes. Static forces include the constant force of gravity. By measuring the amount of static acceleration due to gravity, logic or programming (e.g., software) acting upon information from an accelerometer sensor can figure out the angle the sensor is tilted at with respect to the earth. By sensing the amount of dynamic acceleration, logic or programming acting upon information from the accelerometer sensor can find out fast and in what direction the sensor is moving. Single- and multi-axis models of accelerometers detect magnitude and direction of acceleration (or proper acceleration) as a vector quantity. With these and similar types of sensor constructions, an output from the implantable sensor can include vector quantities in one, two or three axes. For example,
Returning to
Posture Determination
As implicated by the above, in some embodiments the posture module 34 is programmed or designed (e.g., appropriate algorithms) to detect, determine or designate a current posture of the patient based upon information from the implantable sensor 32. In at least this context, the term “posture” can refer at least to identifying whether a patient is in a generally vertical position or a lying down position, such as a supine position, a prone position, a left side position (e.g., left lateral decubitus), a right side position (e.g., right lateral decubitus), etc. In some instances, the term “posture” may sometimes be referred to as “body position”.
In some examples, the posture module 34 rejects non-posture components from an accelerometer-type implantable sensor via low pass filtering relative to each axis of the multiple axes of the accelerometer sensor. In some examples, posture is at least partially determined via detecting a gravity vector from the filtered axes.
In some examples, one potential posture classification protocol implemented by the posture module 34 includes determining whether the patient is active or at rest. In some examples, when a vector magnitude of the acceleration measured via the accelerometer-type implantable sensor meets or exceeds a threshold (optionally for a period of time), the measurement may indicate the presence of non-gravitational components indicative of non-sleep activity. In some examples, the threshold is about 1.15 G. Conversely, measurements of acceleration of about 1 G (corresponding to the presence of the gravitational components only) may be indicative of rest.
In some examples, one potential posture classification protocol implemented by the posture module 34 includes determining whether at least an upper body portion (e.g., torso, head/neck) of the patient is in a generally vertical position (e.g., upright position) or lying down. In some examples, a generally vertical position may comprising standing or sitting. In some examples, this determination may observe the angle of the accelerometer-based implantable sensor between the Y axis and the gravitational vector, which sometimes may be referred to as a y-directional cosine. In some examples, when such an angle is less than 40 degrees, the measurement suggests the patient is in a generally vertical position, and therefore likely not asleep.
In some examples, if the measured angle (e.g., a y-directional cosine) is greater than 40 degrees, then the measured angle indicates that the patient is lying down. In this case, one example posture classification protocol implemented by the posture module 34 includes classifying sub-postures, such as whether the patient is in a supine position, a prone position, or in a lateral decubitus position. In some non-limiting examples, after confirming a likely position of lying down, the posture classification protocol determines if the patient is in a supine position or a prone position. In some examples, the determination of a supine state is made when an absolute value of the z-directional cosine (the angle of the accelerometer-type implantable sensor between the Z axis (calibrated to represent the A-P axis of the patient's body and the gravitational vector) is less than or equal to 45 degrees, and the determination of a prone state when the absolute value of the z-directional cosine is greater than or equal to 135 degrees. If neither of those criteria are satisfied, then the patient may be lying on their left or right side (e.g., lateral decubitus position). Accordingly, in some non-limiting examples, the posture classification protocol performs a further classification via the pitch angle such that the patient is designated as lying on their right side if the pitch angle is less than or equal to negative 45 degrees or greater than or equal to negative 135 degrees; the patient is designated as lying on their left side if the pitch angle is greater than or equal to 45 degrees or the pitch angle is less than or equal to 135 degrees. In some examples, a similar determination can be made using directional cosines.
The above explanations provide a few non-limiting examples of some posture determination or designation protocols implemented by the posture module 34. A number of other posture determination or designation techniques are also envisioned by the present disclosure, and can be function of the format of the implantable sensor 32 and/or other information provided by one or more additional sensors.
In some embodiments, the posture module 34 is programmed to distinguish between a supine sleep position and a generally supine reclined position. As a point of reference, a generally supine reclined position can be one in which the patient is on a recliner, on an adjustable-type bed, laying on a couch, or the like and not attempting to sleep (e.g., watching television) vs. sleeping in bed. An absolute vertical distance between the head and torso of the patient in the supine sleep position is less than the absolute vertical distance between the head and torso in the generally supine reclined position. Alternatively or in addition, in some embodiments, the posture module 34 is programmed to consider or characterize a position of the patient's neck and/or head and/or body position (e.g., as part of a determination of the patient's rotational position while lying down). For example, the posture module 34 can be programmed to estimate a position of the patient's neck based on body position. A determination that the patient's torso is slightly offset may imply different head positions. In some non-limiting embodiments, the systems and methods of the present disclosure can consider or characterize a position of the patient's neck and/or head via information from a sensor provided with a microstimulator that is implanted in the patient's neck or in conjunction with a sensor integrated into the stimulation lead. In other examples, two (or more) position-type sensors (e.g., accelerometers) can be provided, each implanted in a different region of the patient's body (e.g., torso, head, neck) and providing information to the posture module 34 sufficient to estimate neck and/or head and/or body positions of the patient.
In addition to, or as an alternative to, the above, in some embodiments, the systems and methods of the present disclosure can include the posture module 34 programmed to determine or designate lying down positions in addition to the four “primary” lying down positions described above (i.e., supine, prone, left lateral decubitus, and right lateral decubitus). For example, and with additional reference to
Additionally or alternatively, in some embodiments, the systems and methods of the present disclosure can include the posture module 34 programmed to determine or designate a current posture or position of the patient utilizing a temporal analysis or probabilistic based approached. For example, the posture module 34 can be programmed (e.g., a time averaging algorithm) to designate a current posture or position based upon a time average of information from the implantable sensor 32, thus minimizing the impact of small artifacts in the information from the implantable sensor 32 due to, for example, arm movement, leg movement, jerking, etc., especially when the patient is sleeping. By way of example, one approach for determining or designated that the patient is lying supine and sleeping can include reviewing a dot product of vector information from the implantable sensor 32 (e.g., vector information in a head-to-toe direction of the patient) with a gravity or vertical reference vector or head-to-toe (described in greater detail below); when the patient is lying supine and sleeping, this dot product will be approximately zero. If the patient randomly jerks an appendage while sleeping, the dot product of corresponding vector information from the implantable sensor 32 with the gravity or vertical reference vector may no longer be approximately zero yet the patient is still lying supine and asleep. By utilizing a time averaging or other probabilistic approach, the posture module 34 will not designate a “new” posture or position for the patient in response to the information generated by the implantable sensor 32 at the time the patient jerks his/her appendage. However, in some embodiments, the temporal analysis or probabilistic approach will be able to distinguish between the patient making a small movement while asleep and the patient rising from bed upon waking. In related embodiments, motion artifacts can be filtered by considering an overall magnitude of vector information from the implantable sensor 32 over short periods of time. For example, where the patient is lying down and asleep, the overall magnitude of vector information from the implantable sensor 32 will be approximately 1 g; if the patient jerks an appendage while sleeping, the overall magnitude will temporarily spike. Motion artifacts such as these can be filtered by ignoring temporary spikes in overall magnitude of less than a predetermined period of time (e.g., a few seconds). In other embodiments, a low pass filter can be applied to the implantable sensor signal to achieve similar results.
Additionally or alternatively, in some embodiments, the systems and methods of the present disclosure can include the posture module 34 programmed to determine or designate a current posture or position of the patient utilizing other probabilistic-based approaches. For example, the systems and methods can be programmed or operate an algorithm to perform an action when the probability that the patient is in a particular posture exceeds a certain threshold. Low or high thresholds may be appropriate depending upon the function that will be triggered by the detection. Likewise, the systems and method of the present disclosure optionally include taking an action when the probability that the patient is in a particular posture is below a particular threshold. In yet other examples, the systems and methods of the present disclosure include determining, based on information from the implantable sensor 32, that the patient is not in a particular posture (e.g., the system is programmed to take an action when information from the implantable sensor 32 is designated by the posture module 34 as implicating that the patient is not supine) or that the probability the patient is not in a particular posture is above a threshold. By way of non-limiting example, some of the probabilistic-based approaches or techniques of the present disclosure can include correlating the likelihood of the patient not being in a particular posture with the likelihood of the patient being in the particular posture. For example, where the “particular posture” is supine, a relationship of the probability of the patient not being supine (“not_probability_supine” can be correlated with the probability of the patient being supine (“probability_supine”) as:
not_probability_supine=1−probability_supine
In practice, there may be different error sources in determining “not_probability_supine” and “probability_supine”. For example, if different sensors or algorithms are used in the determination of each, the above equation would not hold and therefore, these two probabilities are distinct. This extends to the probability of multiple posture indications, each with a distinct error source. Also, the threshold (where applicable) that can be utilized for “not_probability_supine” may be different than the threshold utilized with for “1−probability_supine” if, for example, there is an interest to add a bias to the algorithm to reduce sensitivity to one error source at the expense of the other.
Additionally or alternatively, the systems and methods of the present disclosure can include calibrating to compensate, account, or address the possibility that a position of the implantable sensor 32 (from which posture determinations can be made) within the patient's body is unknown and/or has changed over time (e.g., migration, temporary re-orientation due to change in the implant pocket with changing posture as mentioned above). In some examples, the posture module 34 can be programmed (e.g., algorithm) to perform such calibration (indicated generally at 250 in
In some embodiments, calibration performed by the posture module 34 can include establishing or creating a vertical baseline gravity vector. For example, the vertical baseline gravity vector can be determined by the posture module 34 during times when the patient is deemed to be likely by upright (e.g., based on various information such as information from the implantable sensor, information from other sensors, time of day, patient history, etc., the likelihood or probability that the patient is upright and/or is engaged in an activity in which the patient is likely to be upright (e.g., walking) can be determined), and can be determined as a time average value during periods of higher activity. Once established, the vertical baseline gravity vector can be utilized by the posture module 34 to calibrate subsequently-received information from the implantable sensor 32. The vertical baseline gravity vector can be determined/re-set periodically (e.g., at pre-determined intervals).
In addition or alternatively, calibration performed by the posture module 34 can include establishing or creating a horizontal baseline gravity plane (alternatively a horizontal baseline vector or “head-to-toe” vector (relative to the patient's anatomy)). As a point of reference, the “vertical gravity vector” can be considered a vector truly aligned with the direction of gravity relative to earth. A “horizontal gravity plane” can be considered the plane that is truly orthogonal to the vertical gravity vector; a horizontal gravity vector (such as a head-to-toe vector) can be considered a vector that lies solely in the horizontal gravity plane. With this in mind, in some embodiments, the horizontal baseline gravity plane can be determined by the posture module 34 during times when the patient is deemed to be likely by lying down (e.g., based on various information such as information from the implantable sensor 32, information from other sensors, time of day, patient history, etc., the likelihood or probability that the patient is lying down and/or is engaged in a low activity in which the patient is likely to be lying down (e.g., sleeping) can be determined), and can be determined as a time average value during periods of low activity. Once established, the horizontal baseline gravity plane can be utilized by the posture module 34 to calibrate subsequently-received information from the implantable sensor 32. The horizontal baseline gravity plane can be determined/re-set periodically (e.g., at pre-determined intervals). In some embodiments, the horizontal baseline gravity plane can be determined by the cross product of various vectors obtained during periods of low activity so as to reduce or eliminate artifacts from rotation (e.g., the patient is lying down and changes positions from back, stomach, side, etc.). The cross product of two vectors obtained from the implantable sensor 32 when it is believed the patient is lying down should approximately equal the vertical baseline gravity vector; under circumstances where this is not true, it can be assumed that one or both of the vectors under consideration are not indicative of the patient in a lying down position and thus less useful in determining or designating a horizontal baseline gravity plane (or used as a horizontal baseline gravity vector).
In addition or alternatively, calibration performed by the posture module 34 can include establishing or creating a vertical baseline gravity vector and a horizontal baseline gravity plane (or horizontal baseline gravity vector otherwise within the horizontal baseline gravity plane) as described above (and useful for calibrating information from the implantable sensor 32 as part of a posture characterization or determination process), and confirming usefulness of the so obtained calibration values. For example, a dot product of a designated vertical baseline gravity vector and a designated vector of the horizontal baseline gravity plane is generated and compared to a threshold value. From this comparison, a usefulness of one or both of the designated vertical baseline gravity vector and the designated horizontal baseline gravity plane (or designated horizontal baseline gravity vector) is generated. For example, if the dot product is close to zero, then one or both of the designated vertical baseline gravity vector and the designated horizontal baseline gravity vector (or plane) are verified, and can be employed for calibrating information from the implantable sensor 32.
In addition or alternatively, calibration performed by the posture module 34 can include receiving a predetermined vertical baseline gravity vector and one or more predetermined horizontal baseline gravity vectors (e.g., indicative of prone, supine, left lateral decubitus, right lateral decubitus) useful for calibrating information from the implantable sensor 32. The predetermined baseline gravity vectors can be entered during the implant procedure (e.g., entered by a clinician using the external device 36 in the operating room), as part of a programming appointment (e.g., following implant, the patient mimics each posture or position of interest, and the posture module 34 is prompted (e.g., via the external device 36) to denote the corresponding vector information from the implantable sensor 32 as being the predetermined baseline gravity vector), as part of an in-home calibration procedure performed by the patient (e.g., the external device 36 is a smart phone or the like operating a software application), etc. In some embodiments, the posture module 34 is programmed to confirm the usefulness of the so-generated, predetermined baseline gravity vectors. For example, dot products and/or cross products of respective pairs of the predetermined baseline gravity vectors can be obtained to error check and ensure that all the predetermined baseline gravity vectors are approximately perpendicular (i.e., within 5 percent of a truly perpendicular relationship). To the extent any predetermined baseline gravity vector(s) are found to not be approximately perpendicular, the predetermined baseline gravity vector(s) can be further reviewed for possible usefulness as a calibration factor, or other steps taken to obtain viable predetermined baseline gravity vector(s). Conversely, to the extent the error check confirms viability of the predetermined baseline gravity vectors, the predetermined baseline gravity vectors can then be employed for calibrating information from the implantable sensor 32. In yet other embodiments, the posture module 34 can be programmed such that if the vectors are compared to reference vectors and there appears to be differences, a notification can be provided to the patient and/or clinician to re-preform the predetermined baseline gravity vector entry procedures.
In addition or alternatively, calibration performed by the posture module 34 can include determining an orientation of the implantable sensor 32 in the patient's body based upon respiratory and/or cardiac waveform polarity information provided by or derived from the implantable sensor 32 and/or other appropriate sensor components associated with the patient. In one aspect, motion signals have a significantly greater amplitude than respiration signals, and therefore the motion signals are extracted from a respiratory waveform or otherwise rejected. In some examples, this extraction may be implemented via an awareness of motion associated with an X axis or Y axis of an accelerometer sensor having signal power significantly greater than the signal power of a Z axis in the accelerometer sensor, such as where the accelerometer sensor is implanted in some examples such that its Z axis is generally parallel to an anterior-posterior axis of the patient's body. If a patient's respiration signal is largest in a particular axis (not necessarily aligned with one of X, Y, Z), motion artifact can be rejected by filtering signals not aligned with the axis where respiration is largest. In one aspect, motion signals sensed via the accelerometer sensor can be distinguished from the respiration signals sensed via the accelerometer according to the high frequency content above a configurable threshold. The respiratory and/or cardiac waveform polarity information can, for example, be reviewed to determine a likelihood of the patient being asleep (and thus lying down) and/or to determine a likelihood of the patient engaged in higher activity (and thus upright). Upon determining that the patient is currently likely lying down and/or likely upright, the posture module 34 can be programmed to review current information from the implantable sensor 32; to the extent the current information is not aligned with the determined likely position (e.g., it is determined that the patient is likely lying down and the current information from the implantable sensor 32 (e.g. vector information) does not directly implicate the patient is lying down), a calibration factor can be determined by the posture module 34 to be applied to information from the implantable sensor 32 based upon differences between the current information and expected.
In addition or alternatively, calibration performed by the posture module 34 can include determining an expected change in information from the implantable sensor 32 upon waking. Based upon information (current and/or tracked/historical) from the implantable sensor 32 and/or one or more additional sensors associated with the patient, it can be determined when the patient is likely asleep (and thus lying down) and when the patient is likely waking from sleep and changing to an upright posture (e.g., the patient gets out of bed in the morning following a night's sleep). Upon determining that the patient is currently likely changing posture upon waking from sleep, the posture module 34 can be programmed to review current information from the implantable sensor 32; to the extent the current information is not aligned with the determined likely position (e.g., it is determined that the patient is likely currently upright and the current information from the implantable sensor 32 (e.g., vector information) does not directly implicate the patient is upright), a calibration factor can be determined by the posture module 34 to be applied to information from the implantable sensor 32 based upon differences between the current information and expected.
In addition or alternatively, calibration performed by the posture module 34 can include reviewing current information from the implantable sensor 32 when the patient is likely asleep (and thus likely lying down). For example, the posture module 34 can incorporate, or received information from, an internal clock. With reference to information from the internal clock, the posture module 34 can be programmed to designate that the patient is likely lying down during certain hours of the day (e.g., 9:00 PM-7:00 AM, etc.). The “likely lying down” time frame can be pre-programmed to the posture module 34 and/or can be learned over time (based upon tracked/historical information). Upon determining that the patient is likely currently lying down, the posture module 34 can be programmed to review current information from the implantable sensor 32; to the extent the current information is not aligned with the determined likely position (e.g., it is determined that the patient is likely currently lying down and the current information from the implantable sensor 32 (e.g. vector information) does not directly implicate that the patient is lying down), a calibration factor can be determined by the posture module 34 to be applied to information from the implantable sensor 32 based upon differences between the current information and expected.
In addition or alternatively, calibration performed by the posture module 34 can include referencing information generated by a patient calibration program following implant. The patient calibration program can be implemented as part of a software application operated by the external device 36 (e.g., the external device 36 can be a smartphone or the like operating a software application programmed to effect patient calibration, a custom external programmer operating a patient calibration routine, a remote control, etc.), and walks the patient through a calibration sequence in which the patient is prompted to assume various postures or positions of interest; while the patient is in a particular posture or position, the posture module 34 is prompted to denote the current information from the implantable sensor 32 as corresponding to that particular posture or position. The results of this calibration sequence can be used to calibrate, adjust or correct information subsequently provided by the implantable sensor 32 and/or to “teach” the posture module 34 different orientations of the implantable sensor 32 relative to the patient. In some embodiments, the software application is programmed to prompt the patient to assume a vertical position and receive an indication that the patient is in the vertical position for establishing the predetermined vertical baseline gravity vector. Alternatively or in addition, the software application is programmed to prompt the patient to assume a horizontal supine position and receive an indication that the patient is in the horizontal supine position for establishing the predetermined horizontal supine baseline gravity vector. Other baseline vectors can be determined from the so-established predetermined horizontal supine baseline gravity vector (e.g., a predetermined horizontal prone baseline gravity vector, a predetermined horizontal left lateral decubitus baseline gravity vector, a predetermined horizontal right lateral decubitus baseline gravity vector, etc.). In yet other embodiments, the software application can be programmed to prompt the patent to assume one or more of a vertical position, a horizontal prone position, a horizontal left lateral decubitus position, and a horizontal right lateral decubitus position and receive a corresponding indication from the patient for establishing the predetermined vertical baseline gravity vector, the predetermined horizontal prone baseline gravity vector, the predetermined horizontal left lateral decubitus baseline gravity vector, and the predetermined horizontal right lateral decubitus baseline gravity vector.
In addition or alternatively, calibration performed by the posture module 34 can include a clinician programing at least one patient position to the posture module 34 while the patient is in the operating room (e.g., during the implantation procedure). For example, the clinician can program the posture module 34 that the patient is currently lying down position. Upon being information that the patient is currently lying down (or some other posture or position), the posture module 34 can be programmed to review current information from the implantable sensor 32; to the extent the current information is not aligned with a lying down positon (e.g., the current information from the implantable sensor 32 (e.g., vector information) does not directly implicate that the patient is lying down), a calibration factor can be determined by the posture module 34 to be applied to information from the implantable sensor 32 based upon differences between the current information and expected.
Operational Control
As alluded to above, in some non-limiting embodiments, the posture module 34 is programmed to control one or more operational features of the system 20 based upon a determined or designated posture (or communicates with another module or engine programmed to control an operational feature based upon posture as determined or designated by the posture module 34).
For example, the posture module 34 can be programmed (or communicates with another module or engine that is programmed) to select or implement a particular operational mode of the IMD 30 based upon the determined current posture. The “operational mode” of the IMD 30 can include one or more of stimulation parameters, sensing parameters, timing parameters, and diagnostic parameters. For example, the posture module 34 (or another module or engine provided with the system 20 and receiving posture information from the posture module 34) can be programmed with various, pre-determined stimulation therapy settings or modes appropriate for different sleeping positions of the patient (e.g., stimulation therapy settings or mode for one sleeping position (supine, prone, left lateral decubitus, right lateral decubitus, etc.) can differ from that of another sleeping position). When the posture module 34 determines that the patient is in a particular position, the IMD 30 is operated to implement the corresponding stimulation therapy settings or mode. With these and related embodiments, the posture module 34 (or another module or engine provided with the system 20 and receiving posture information from the posture module 34) can be programmed to automatically toggle operation of the IMD 30 between stimulation therapy settings in response to determined changes in the patient's posture. In yet other optional embodiments, the posture module 34 is programmed to determine a dot product value from vector information provided by the implantable sensor 32 as a threshold parameter for initiating (or suspending) delivery of therapy from the IMD 30. In yet other optional embodiments, when the posture module 34 determines that the patient is not in a particular posture or position, the IMD 30 is operated to implement a designated mode or stimulation therapy settings. With these and related embodiments, the posture module 34 (or another module or engine provided with the system 20 and receiving posture information from the posture module 34) can be programmed to automatically toggle operation of the IMD 30 between stimulation therapy settings in response to determination that the patient is not in a particular posture. In yet other optional embodiments, the systems and methods of the present disclosure include monitoring for the patient assuming various postures in a particular order, and then triggering a designated function when the ordering of postures is found to have occurred. With any of the examples of operational control described in the present disclosure, the particular control feature can be implemented upon determining or estimating that the patient is in a particular posture, or upon determining or estimating that the patient is not in a particular posture.
Additionally or alternatively, in some embodiments the posture module 34 can be programmed (or communicates with another module or engine of the system 20 that is programmed) to effect changes to a particular therapy being delivered to the patient by the IMD 30 based upon the determined posture and optionally other factors, akin to auto-titration. With these and related embodiments, the posture module 34 (or another module or engine of the system 20 communicating with the posture module 34) can, for example, automatically increase or decrease one or more parameters of a particular stimulation therapy mode, for example upon identifying that the patient is entering a different stage of sleep. In some examples, the posture module 34 (or another module or engine of the system 20 communicating with the posture module 34) incorporates algorithm(s) or programming to effect posture-based, automatic amplitude adjustments, providing a relatively consistent correlation between therapeutic amplitude and determined posture.
As a point of reference, stages of sleep are typically divided into non-rapid eye movement (non-REM) and rapid eye movement (REM). Non-REM sleep has three stages: N1, N2, and N3. N1 occurs right after falling asleep, and is typically characterized as “light sleep”. During sleep, a person usually progresses through the three stages of non-REM sleep before entering REM sleep or stage. Obstructive sleep apnea may be less prevalent in N1 than REM.
Additionally or alternatively, in some embodiments the posture module 34 can be programmed (or communicates with another module or engine of the system 20 that is programmed) to effect changes to a particular therapy being delivered to the patient by the IMD 30 under circumstances where the patient is likely in a light state of sleep (e.g., N1), as derived from information of the implantable sensor 32. For example, the posture module 34 can be programmed to identify when the patient is likely asleep or attempting to sleep, and track changes in the patient's posture or position during the time the patient is deemed to be sleeping or attempting to sleep. Under circumstances where the system 20 is programmed to deliver therapy to the patient when the patient is sleeping, the posture module 34 (or another module or engine of the system 20 communicating with the posture module 34) can further be programmed to alter the currently-delivered therapy when the patient is determined to be changing positions while likely sleeping. For example, where it is determined that the patient has changed positions, or changed positions two or more times over a pre-determined time period (e.g., 5 minutes, 15 minutes, 30 minutes, etc.), it is likely that the patient is in a light state of sleep and that if stimulation therapy were continued to be delivered at pre-determined levels, this stimulation may make it more difficult for the patient to enter a deeper state of sleep. With these and other examples, the posture module 34 (or another module or engine of the system 20 communicating with the posture module 34) can be programmed to prompt the IMD 30 to pause the stimulation therapy being delivered to the patient and/or ramp down an intensity of the stimulation therapy being delivered to the patient. A “pause” can be considered a rapid ramping down to no stimulation therapy being delivered in some embodiments. The pause or ramping down can be effected for a pre-determined period of time or some other parameter (e.g., respiratory cycles, determination of unchanged sleep posture), and the IMD 30 prompted to re-commence or ramp up the stimulation therapy delivered to the patient.
Additionally or alternatively, in some embodiments the posture module 34 can be programmed (or communicates with another module or engine of the system 20 that is programmed) to effect changes to a particular therapy being delivered to the patient by the IMD 30 under circumstances where the patient is likely temporarily exiting a state of sleep, as derived from information of the implantable sensor 32. For example, the posture module 34 can be programmed to identify when the patient is likely asleep or attempting to sleep, and track changes in the patient's posture or position during the time the patient is deemed to be sleeping or attempting to sleep. Under circumstances where the system 20 is programmed to deliver therapy to the patient when the patient is sleeping, the posture module 34 (or another module or engine of the system 20 communicating with the posture module 34) can further be programmed to alter the currently-delivered therapy when the patient is determined to be likely temporarily exiting a state of sleep. For example, during the time period when the patient is normally sleeping, the patient may wake up and move to go to the bathroom, get a drink of water, etc. If stimulation therapy were continued to be delivered at pre-determined levels during the temporary exit from sleep, this stimulation may be undesirable for the patient. Thus, in some embodiments, where it is determined that the patient has a substantive change in posture during the time period when the patient is expected to be asleep, the posture module 34 (or another module or engine of the system 20 communicating with the posture module 34) can be programmed to prompt the IMD 30 to pause the stimulation therapy being delivered to the patient and/or ramp down an intensity of the stimulation therapy being delivered to the patient. In related embodiments, the pause or ramping down can be effected for a pre-determined period of time, and the IMD 30 prompted to re-commence or ramp up the stimulation therapy delivered to the patient; alternatively or in addition, the delivery of stimulation therapy can be re-commenced or ramped up upon determining that the patient has returned to a lying down position, automatically following expiration of a predetermined time period, following expiration of a predetermined time period and a determination that the patient is not moving about (e.g., an “auto-extended” pause), etc.
With optional embodiments described above in which the posture module 34 operates to effect an automatic pause or ramp down in delivered therapy for a predetermined time period, the posture module 34 can further be programmed (or communicates with another module or engine of the system 20 that is programmed) to incorporate or implement a pause or ramp down extension at the end of the predetermined time period under circumstances where it is determined that the patient is not in a sleep posture, is moving about, etc. In other optional embodiments, the posture module 34 (or another module or engine of the system 20 communicating with the posture module 34) is programmed to provide an auto-pause feature coupled to an automatic start time feature. For example, the system 20 can be programmed to initiate delivery of therapy at a predetermined time of day (e.g., 10:30 PM), but at the predetermined time of day after which stimulation therapy is to be delivered, this automatic start time is automatically paused until it is estimated or determined (e.g., information from the implantable sensor 32 via the posture module 34) that the patient is, or is likely, asleep.
Additionally or alternatively, in some embodiments the posture module 34 can be programmed (or communicates with another module or engine of the system 20 that is programmed) to perform an alert-type operation or routine under circumstances where the patient is likely in a position of poor sleep quality (and thus more likely to experience sleep disordered breathing), as derived from information of the implantable sensor 32. For example, the posture module 34 can be programmed to identify when the patient is likely asleep or attempting to sleep, and when the patient is determined to be in a particular posture or position (e.g., supine) based upon information from the implantable sensor 32, the posture module 34 (or another module or engine provided with the system 20 and communicating with the posture module 34) is programmed to prompt delivery of an inconvenient output to the patient intended to cause or encourage the patient to re-orient. For example, the IMD 30 can be prompted to increase the level of a currently-delivered stimulation therapy, prompted to deliver rapid multi-pulse stimulation, etc. Alternatively or in addition, the IPG assembly 52 can be prompted to vibrate. Alternatively or in addition, an audio alert can be generated at one or both of the IPG assembly 52 and the external device 36.
Additionally or alternatively, in some embodiments the posture module 34 can be programmed (or communicates with another module or engine of the system 20 that is programmed) to one or more of initiate, resume or ramp up (e.g., increase intensity) of delivered stimulation therapy upon determining that the patient has entered, or is likely to have entered, a state of sleep. For example, the posture module 34 can estimate or determine a plurality of current postures of the patient over time. Based upon stored algorithms or other predetermined parameters, when the plurality of postures implicates that the patient has entered a state of sleep, the posture module 34 prompts the IPG assembly 52 to begin delivering stimulation therapy. In related embodiments in which the posture module 34 is programmed to affect an “auto-pause” in delivered stimulation therapy (e.g., in response to a determination that the patient is awake or in a state of light sleep), the posture module 34 is programmed to prompt resuming of the stimulation therapy upon determining that the patient has, or has likely, entered a state of sleep based, at least in part, upon the posture information. In other related embodiments in which the system 20 is programmed to ramp down currently-delivered stimulation therapy under one or more circumstances (e.g., in response a determination that the patient is awake or in a state of light sleep), the posture module 34 is programmed to prompt ramping up of the stimulation therapy upon determining that the patient has, or has likely, entered a state of deep or deeper sleep based, at least in part, upon the posture information.
Additionally or alternatively, in some embodiments the posture module 34 can be programmed (or communicates with another module or engine of the system 20 that is programmed) to effect changes to therapy protocols or modes or other therapy parameters based upon learned or detected tendencies (e.g., sleep tendencies) of the patient over time as derived, at least in part, from information of the implantable sensor 32. For example, the posture module 34 (or another module or engine of the system 20 communicating with the posture module 34) can be programmed to track or record posture (or other information) during times when the patient is deemed to likely be asleep; the tracked information can include, for example, time of day, day of week, and the like. From this information, the posture module 34 can determine, over time (e.g., one or more days, weeks, or months), the patient's sleeping tendencies, for example the time periods the patient typically sleeps. The learned sleep tendencies determined by the posture module 34 can further be segmented by day of the week or consecutive days of the week (e.g., sleep tendencies on weekends and sleep tendencies on weekdays). The posture module 34 (or another module or engine of the system 20) can further be programmed to review a current time of day, a current day of week, or other sleep tendency parameter along with a current designated posture of the patient with the learned sleep tendency information to prompt operation of the IMD 30 (e.g., to initiate or end the delivery of therapy, such as stimulation therapy). For example, a current time of day and determined current posture can be recorded as a data pair, and compared with previously recorded sleep tendency information to determine whether the current time of day and current posture implicates that the patient is likely entering a state of sleep or exiting a state of sleep. Based upon this comparison, the IMD 30 can be prompted to initiate delivery of therapy (where the patient is likely entering a state of sleep) or end delivery of therapy (where the patient is likely exiting a state of sleep). Alternatively or in addition, the current day of week, current time of day, and current posture can be recorded as a data set, and compared with previously recorded sleep tendency information to determine whether the current time of day, current day of week and current posture implicates that the patient is likely entering a state of sleep or exiting a state of sleep. Based upon this comparison, the IMD 30 can be prompted to initiate delivery of therapy (where the patient is likely entering a state of sleep) or end delivery of therapy (where the patient is likely exiting a state of sleep).
Additionally or alternatively, in some embodiments the posture module 34 can be programmed (or communicates with another module or engine of the system 20 that is programmed) to determine contextual information of the patient during periods when the patient is awake as derived, at least in part, from information of the implantable sensor 32. For example, contextual information such as activity level, pelvic floor pressure, etc., can be determined or estimated based upon posture related information alone or in combination with additional, non-posture information.
Diagnostic Data
As alluded to above, in some non-limiting embodiments, the posture module 34 is programmed to provide information to the patient and/or caregiver relating to the determined current posture or other information of possible interest implicated by information from the implantable sensor 32, for example via the external device 36. As a point of reference, the IMD 30 can be configured to interface (e.g., via telemetry) with a variety of external devices. For example, the external device 36 can include, but is not limited to, a patient remote, a physician remote, a clinician portal, a handheld device, a mobile phone, a smart phone, a desktop computer, a laptop computer, a tablet personal computer, etc. The external device 36 can include a smartphone or other type of handheld (or wearable) device that is retained and operated by the patient to whom the IMD 30 is implanted. In another example, the external device 36 can include a personal computer or the like that is operated by a medical caregiver for the patient. The external device 36 can include a computing device designed to remain at the home of the patient or at the office of the caregiver.
With the above in mind, the posture module 34 can be programmed (or communicates with another module or engine of the system 20 that is programmed) to identify information from the implantable sensor 32 indicative of the occurrence of twiddler's syndrome. “Twiddler's syndrome” refers to the patient's deliberate or subconscious spinning or other manipulation of the IPG assembly 52 within the skin pocket, and can lead to malfunction of the IMD 30. For example, logic (e.g., algorithm) of the posture module 34 can recognize a substantive change in information from the implantable sensor 32 at, for example, a designated time of day. By way of non-limiting example, a time of day can be designated as the patient likely being in a lying down position or posture (e.g., 1:00 AM); where the information from the implantable sensor 32 is found to have a certain vector direction on a previous day at the designated time of day (or over several consecutive previous days at the designated time of day) and a substantively different vector direction on the current day at the designated time of day (e.g., an approximately opposite vector direction), it can be deemed there is a likelihood that the implantable sensor 32 has been flipped. Where the implantable sensor 32 is carried in the housing of the IPG assembly 52, this same information can be deemed as implicating a likelihood that the IPG assembly 52 has been flipped. Under these and similar circumstance, the posture module 34 can be programmed to notify or alert a clinician (via the external device 36) of the likely occurrence of twiddler's syndrome.
Alternatively or in addition, the posture module 34 can be programmed (or communicates with another module or engine of the system 20 that is programmed) to identify information from the implantable sensor 32 indicative of the occurrence of device migration. As a point of reference, in some embodiments the sensor component of the implantable sensor 32 is implanted in the patient apart from the IPG assembly 52, whereas in other embodiments the implantable sensor 32 is carried in the housing of the IPG assembly 52 that in turn is implanted in the patient. Regardless, common implantation techniques can include use of suture or similar attachment device that secures the device in question (e.g., the sensor component or the IPG assembly 52) to anatomy of the patient; over time, attachment between the device and the anatomy in question may lessen or deteriorate, with the device then migrating away from the exact implant location and/or orientation. With this in mind, logic (e.g., algorithm) of the posture module 34 can recognize changes in information from the implantable sensor 32 at, for example, a designated time of day, as implicating possible device migration. By way of non-limiting example, a time of day can be designated as the patient likely being in a lying down position or posture (e.g., 1:00 AM); where the information from the implantable sensor 32 is found to have a certain vector direction that is changing over time, it can be deemed there is a likelihood that the implantable sensor 32 has migrated from an initial implant location. Where the implantable sensor 32 is carried in the housing of the IPG assembly 52, this same information can be deemed as implicating a likelihood that the IPG assembly 52 has been migrated. Under these and similar circumstance, the posture module 34 can be programmed to notify or alert a clinician (via the external device 36) of the likely occurrence of device migration.
Alternatively or in addition, the posture module 34 can be programmed (or communicates with another module or engine of the system 20 that is programmed) to record posture-related information during certain activities of the patient and report the same to a clinician and/or the patient via the external device 36. For example, the posture module 34 can record or determine one or more of the percent of time the patient spends in each position during a sleeping event; the efficacy of therapy delivered by the IMD 30 in each position during a sleeping event; auto-titrated therapy setting (e.g., amplitude, electrode configuration, pulse characteristics, etc.) in each position during a sleeping event; etc. In related embodiments, the posture module 34 can operate (or communicate with) a sleep stage determination engine by which sleep stages can be determined. In some embodiments, such determination is made according to the relative stability of respiratory rate throughout the treatment period (e.g., during expected sleeping hours). In some non-limiting examples, the sleep determination engine determines and tracks the number of minutes awake, minutes in bed, posture, sleep/wake cycle, and/or number and depth of REM periods. In some examples, the posture module 34 can operate (or communicate with) a sleep quality engine to determine sleep quality according to, for example, a combination of a sleep time parameter, a sleep stage parameter, and a severity index parameter (e.g., apnea-hypopnea index measurement). The sleep stage can be determined via at least one of activity information, posture information, respiratory information, respiratory rate variability (RRV) information, heart rate variability (HRV) information, and heart rate information in some non-limiting embodiments. Other information that can be tracked by the posture module 34 (or other module or engine of the system 20) and delivered to a clinician and/or the patient via the external device 36 can include one or more of apnea-hypopnea index, respiratory rate, sleep disordered breathing, peripheral capillary oxygen saturation (SpO2), heart rate, snoring, etc. In yet other embodiments, the posture module 34 can be programmed to generate posture notifications at the external device 36 when stimulation (or other therapy) is being provided by the IMD 30.
Alternative Operational Modes
In some non-limiting examples of the present disclosure, the posture module 34 is programmed to detect a change in posture, and need not necessarily detect or designate a current posture of the patient (under some circumstances or under all circumstances). For example, the posture module 34 can be programmed or configured (e.g., operating logic or algorithm) such that when the patient is deemed or known to be asleep, the posture module 34 does not detect or designate a current posture of the patient (nor does any other module or engine of the system 20), but detects changes in posture, such as gross changes in posture (e.g., moving from left lateral decubitus to supine, supine to prone, etc.).
In other embodiments, the posture module 34 does not detect or determine posture (nor does any other module or engine of the system 20), but tracks the gravity vector of the implantable sensor 32 over time. With these and related embodiments, the posture module 34 is programmed or configured to allow a user (e.g., patient, caregiver, etc.) to define certain gravity vector orientations relative to the implantable sensor 32 (or relative to the IPG assembly 52 where the implantable sensor 32 is carried in the housing of the IPG assembly 52) that can be associated with different operations modes. Any number of these defined vector/modes could be established with variable ranges of affect. By way of non-limiting example, the posture module 34 (or other module or engine of the system 20) can be programmed or configured to activate therapy delivery during a defined time period when no or minimal motion by the patient is detected, and the monitored gravity vector (or other monitored patient information related to posture) is within a predetermined range.
In addition or alternatively, changes in the monitored gravity vector of a certain or pre-determined magnitude can be used to reset a therapy ramp (e.g., therapy is being delivered at a predetermined level or intensity, and a detected change in the monitored gravity vector is sufficient to prompt the ramping down of the delivered therapy level; delivery of the ramped down or lower level therapy continues until the monitored gravity vector returns to the predetermined range (e.g., implicating that the “change” in the patient's status is complete) and the delivered therapy is ramped up to the predetermined level or intensity). In other embodiments, when monitoring the gravity vector over time, the system can be programmed to make therapy changes based on at least one of the current vector, a change in the vector (e.g., vector, cosine math), or repeating change in the vector (e.g., implicating walking, breathing, etc.).
As implicated by the above descriptions, one or both of the IMD 30 and the external device 36 includes a controller, control unit, or control portion that prompts performance of designated actions.
In general terms, the controller 302 of the control portion 300 comprises an electronics assembly 306 (e.g., at least one processor, microprocessor, integrated circuits and logic, etc.) and associated memories or storage devices. The controller 302 is electrically couplable to, and in communication with, the memory 304 to generate control signals to direct operation of at least some the devices, systems, assemblies, circuitry, managers, modules, engines, functions, parameters, sensors, electrodes, and/or methods, as represented throughout the present disclosure (e.g., the posture module 34 (
In response to or based upon commands received via a user interface (e.g. user interface 310 in
For purposes of the present disclosure, in reference to the controller 302, with embodiments in which the electronics assembly 306 comprises or includes at least one processor, the term “processor” shall mean a presently developed or future developed processor (or processing resources) or microprocessor that executes sequences of machine readable instructions contained in a memory. In some examples, execution of the sequences of machine readable instructions, such as those provided via the memory 304 of the control portion 300 cause the processor to perform actions, such as operating the controller 302 to implement sleep disordered breathing (SDS) therapy and related management and/or management and operation of designated physical action sensing, as generally described in (or consistent with) at least some examples of the present disclosure. The machine readable instructions may be loaded in a random access memory (RAM) for execution by the processor from their stored location in a read only memory (ROM), a mass storage device, or some other persistent storage (e.g., non-transitory tangible medium or non-volatile tangible medium, as represented by the memory 304. In some examples, the memory 304 comprises a computer readable tangible medium providing non-volatile storage of the machine readable instructions executable by a process of the controller 302. In other examples, hard wired circuitry may be used in place of or in combination with machine readable instructions to implement the functions described. For example, the electronics assembly 306 may be embodied as part of at least one application-specific integrated circuit (ASIC), at least one integrated circuit, a microprocessor and ASIC, etc. In at least some examples, the controller 302 is not limited to any specific combination of hardware circuitry and machine readable instructions, nor limited to any particular source for the machine readable instructions executed by the controller 302.
In some examples, in association with the control portion 300, the user interface (310 in
Returning to
Although specific examples have been illustrated and described herein, a variety of alternate and/or equivalent implementations may be substituted for the specific examples shown and described without departing from the scope of the present disclosure. This application is intended to cover any adaptations or variations of the specific examples discussed herein.
This Utility Patent Application claims priority under 35 U.S.C. § 371 to International Application Serial No. PCT/US20/043442, filed Jul. 24, 2020, which claims the benefit of U.S. Provisional Patent Application Ser. No. 62/878,531, filed Jul. 25, 2019, all of which are incorporated herein by reference.
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/US2020/043442 | 7/24/2020 | WO |
| Publishing Document | Publishing Date | Country | Kind |
|---|---|---|---|
| WO2021/016536 | 1/28/2021 | WO | A |
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