Evaluating and adjusting sensing efficacy

Description

Background

[0001] A significant portion of the population suffers from various forms of sleep disordered breathing (SDB). In some patients, external breathing therapy devices and / or mere anatomical surgical interventions may fail to treat the sleep disordered breathing behavior. Brief Description of the Drawings

[0002] FIG. 1A is a block diagram schematically representing an example arrangement including a programmer and an implantable medical device.

[0003] FIG. 1B is a block diagram illustrating one example of a device for detecting respiration and applying stimulation based on the sensed respiration.

[0004] FIG. 2A is a diagram schematically representing an example method and / or example device in relation to a target tissue.

[0005] FIG. 2B is a diagram including a front view schematically representing a patient’s body including example implantable components and example external elements of example methods and / or example devices.

[0006] FIG. 2C is a block diagram of a control portion.

[0007] FIG. 3A is a diagram schematically illustrating respiratory cycles in one example breathing pattern.

[0008] FIG. 3B is a diagram schematically illustrating an example stimulation protocol applied to the respiratory cycles of FIG. 3A according to some examples of the present disclosure.

[0009] FIG. 4 is a flow diagram illustrating one example of a method for evaluating and / or adjusting sensor efficacy via programming change(s) in accordance with principles of the present disclosure.

[0010] FIG. 5 is a diagram schematically illustrating an example of undesired timing of stimulation as applied to respiratory cycles of a patient.

[0011] FIG. 6 is a diagram schematically illustrating an example of undesired timing of stimulation as applied to respiratory cycles of a patient.

[0012] FIG. 7 is a diagram schematically illustrating an example of undesired timing of stimulation as applied to respiratory cycles of a patient.

[0013] FIG. 8 is a diagram schematically illustrating an example of undesired timing of stimulation as applied to respiratory cycles of a patient.

[0014] FIG. 9 is a flow diagram illustrating one example of a method for evaluating and / or adjusting sensor efficacy via programming change(s) in accordance with principles of the present disclosure.

[0015] FIG. 10A is a diagram schematically illustrating an example of applied stimulation not causing airflow changes in the respiratory cycles of a patient.

[0016] FIG. 10B is a diagram schematically illustrating an example of applied stimulation causing airflow changes in the respiratory cycles of a patient.

[0017] FIG. 11 is an example of documentation provided to a clinician in accordance with principles of the present disclosure.

[0018] FIG. 12A is a block diagram schematically representing an example control portion.

[0019] FIG. 12B is a diagram schematically illustrating at least some example arrangements of a control portion.

[0020] FIG. 12C is a block diagram schematically representing a user interface.

[0021] FIG. 13 is a block diagram which schematically represents some example implementations by which an IMD may communicate wirelessly with external devices outside the patient. Detailed Description

[0022] 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.

[0023] At least some examples of the present disclosure are directed to systems and methods for addressing potential sensor-based programming concerns of a medical device, for example an implantable medical device (IMD) including an implantable pulse generator (IPG)). In some such examples, methods may be based, at least in part, upon identifying a designated relationship between applied stimulation and a physiological characteristic of the patient and, when a particular designated relationship is identified, implementing one or more designated adjustments. In some examples, the methods and adjustment(s) of the present disclosure are useful with implantable stimulation systems programmed to control (e.g., synchronize, trigger, etc.) the delivery of stimulation or other therapy based upon, or with reference to, respiration information of the patient as implicated by one or more sensor signals, for example for applying electrical stimulation to the patient to treat sleep disordered breathing. With these and related embodiments, systems and methods of the present disclosure readily address potential efficacy concerns attributable to programmed interpretation and / or application of the respiration-related sensor signal(s). Via at least some of these example methods, a clinician may be guided to efficiently and effectively program (and / or evaluate) an IMD according to desired and / or recommended respiration-related sensor signal parameters without extensive training. Moreover, in some such examples, while the example methods help guide the clinician through the programming, the example methods still provide the clinician with appropriate autonomy in making medical decisions and / or using their discretion as appropriate regarding adjustment of parameters of a programmer, IMD, etc.

[0024] As shown in FIG. 1A, one example arrangement (e.g., system) 100 comprises an implantable medical device (IMD) 104 and a programmer 102. In some examples, the IMD 104 may comprise an implantable pulse generator (IPG), which in some examples may comprise an IPG for treating sleep disordered breathing (SDB) and / or other patient conditions (e.g., cardiac, pelvic disorders, etc.). The programmer 102 may communicate with the IMD 104 via a wireless communication protocol either directly or indirectly via an intermediary communication element. However, depending on the type and / or placement of the IMD 104, the programmer 102 may communicate with the IMD 104 via a wired connection. The programmer 102 may sometimes be referred to as a clinician programmer to the extent that the programmer 102 is expected to be employed via a clinician.

[0025] In some examples, the programmer 102 comprises a user interface 103, such as but not limited to a graphical user interface (GUI), to facilitate display and input relative to the example methods by which a clinician operates the programmer 102 and / or performs the example methods. It will be further understood that the programmer 102 may perform tasks or operations (relating to patient care, maintenance, etc.) other than programming stimulation-related aspects of the IMD 104. Moreover, in some examples, the programmer 102 may comprise a device dedicated solely for the purpose of communicating with, programming, etc., the IMD 104. In other examples, the programmer 102 may comprise a non-dedicated device which may be used for purposes (e.g., general communication, general computing, etc.) other than communicating with or programming the IMD 104 (e.g., a consumer device, such as a consumer tablet, smart phone, etc.).

[0026] FIG. 1B is a block diagram schematically representing an example IMD 130, which may comprise one example implementation of IMD 104. In some examples, the IMD 130 comprises a stimulation component 140 and a respiration-related sensing component 142. In some examples, the stimulation component 140 comprises a stimulation engine to generate a stimulation signal to be applied to a tissue (e.g., nerve, muscle, etc.). In the examples in which the IMD 130 comprises an implantable pulse generator (IPG), the tissue to be stimulated may comprise tissue to maintain or restore upper airway patency, such as but not limited to a hypoglossal nerve, infrahyoid muscles (e.g., infrahyoid strap, sternothyroid muscle (and sternohyoid, omohyoid secondarily), etc.), an infrahyoid muscle (IHM)-innervating nerve (e.g., which may include the ansa cervicalis nerve loop and / or its branches), and / or other nerves or muscles, etc.

[0027] At least some of the various examples throughout the present disclosure may be applied to treating central sleep apnea (CSA), such as via electrical stimulation of a phrenic nerve and / or diaphragm muscle.

[0028] In some examples, the stimulation component 140 also may comprise circuitry for generating and delivering the stimulation signal. In some examples, the stimulation component 140 of the I MD 130 also may comprise a stimulation element, such as an electrode configuration(s) through which the stimulation signal may be applied to the target tissue. In some examples, at least a portion of the stimulation element may be part of an implantable component / device (e.g., IMD or IMD portion), such as an implantable pulse generator (IPG). In some examples, the IPG may comprise a full sized IMD which is chronically implantable in a torso of the patient (e.g., pectoral region) but otherwise generally considered too large for implantation in a head-and-neck region. In some examples, the IPG may comprise a smaller sized IPG which is sized and shaped to be chronically implanted in the head-and-neck region or neck region alone, such as in locations, spaces, etc. in which a full sized IPG would not reasonably fit. In some examples in which the IMD (e.g., IPG) is generally chronically implanted in the neck region, a portion of the IPG or the entire IPG may be chronically implanted at a transition of a lower portion of the neck and an upper portion of the torso, such as (but not limited to) at or near a clavicle, manubrium, sternum, etc. In some examples, the “smaller sized” IPG may sometimes be referred to as a microstimulator. In some examples, a microstimulator of the present disclosure includes a housing that encapsulates at least power, control, sensing and / or stimulation circuitry. In some examples, at least a portion of the stimulation element may comprise part of an external component / device such as, but not limited to, the external component comprising a pulse generator (e.g., stimulation / control circuitry), power supply (e.g., rechargeable, non-rechargeable), and / other components. In some examples, a portion of the stimulation element may be implantable and a portion of the stimulation element may be external to the patient.

[0029] In some examples, the respiration-related sensing component 142 comprises a sensing engine to receive a sensing signal obtained relative to a tissue (e.g., muscle, organ, etc.) related to respiration. In some such examples, the respiration-related sensing component 142 also may comprise circuitry for receiving and processing the sensing signal. In some examples, the respiration-related sensing component 142 of the IMD 130 also may comprise a sensor or sensing element through which the sensing signal is obtained. The sensing element of the respiration-related sensing component 142 can assume various forms appropriate for sensing a physiologic parameter of the patient and from which patient respiration information (e.g., respiratory patterns such as inspiration, expiration, respiratory pause, etc.) can be determined. For example, the sensing element can be or include a pressure sensor, bio-impedance sensor, accelerometer, acoustic sensor, etc. It will be understood that information from the respiration-related sensing component 142 can, in some examples, be utilized for purposes other than determining patient respiration information. Further, the IMD 130 can include one or more additional sensing components utilized for purposes other than determining patient respiration information. In some examples, at least a sensing portion of the respiration-related sensing component 142 can be external the patient, for example as part of an external element. The external element may be implemented via a wide variety of formats such as, but not limited to, a patient support (e.g., bed, chair, sleep mat, other), wearable element (e.g., finger, wrist, head, neck, shirt), noncontact elements (e.g., watch, ring, chest band, camera, mobile device, bedside appliance, patient remote, other), and / or other elements.

[0030] In some examples, the stimulation component 140 and / or sensing component 142 may be on-board the IMD 130, which in some examples may comprise a microstimulator. In some examples, at least a portion of the stimulation component 140 and / or respiration-related sensing component 142 may be separate from, and independent of, a housing of the IMD 104, 130 with one or both components 140, 142 being in wired or wireless communication with the IMD 104, 130.

[0031] By way of further non-limiting example, FIG. 2A is a block diagram schematically representing an example arrangement 180 (an example device and / or example method) including an implantable medical device (IMD) 182 in operable relation to target tissue(s) 190. In some examples, the IMD 182 may comprise one example implementation of the IMD 104, 130, and may include a sensing element 184 (e.g., a respiration-related sensing element useful with or as the respiration-related sensing component 142 of FIG. 1B), a stimulation element 186, and / or other element 188 (or function), such that the IMD 182 may be in sensing relation, stimulating relation, and / or other relation with the target tissue(s) 190. In some examples, the IMD 182 may comprise multiple components with the sensing element 184 and the stimulation element 186 being present in a single component or being present in separate components, which are in communication with each other.

[0032] FIG. 2B is a block diagram schematically representing a patient’s body 200, including example target portions 210-234 at which at least some example sensing element(s), stimulation element(s), and / or other elements may be employed to implement at least some examples of the present disclosure. As shown in FIG. 3B, the patient’s body 200 includes a head-and-neck portion 210, including head 212 and a neck region 214, which includes an upper neck region, a mid neck region, and a lower neck region. The upper neck region (which sometimes may be called a head-and-neck transition region) may include a mandible region. The lower neck region (which sometimes may be called a neck-and-torso transition region) may include a clavicle region. The mid neck region extends between the upper neck region and the lower neck region. The head-and-neck portion 210 includes cranial tissue, nerves, etc., and upper airway 216 (e.g., nerves, muscles, tissues), etc. which primarily extends through and within the neck 214. As further shown in FIG. 2B, the patient’s body 200 includes a torso 220, which includes various organs, muscles, nerves, other tissues, such as but not limited to those in a pectoral region 222 (e.g., lungs 226, cardiac 227), abdomen 224, and / or pelvic region 229 (e.g., urinary / bladder, anal, reproductive, etc ). As further shown in FIG. 2B, the patient’s body 200 includes limbs 230, such as arms 232 and legs 234.

[0033] It will be understood that various sensing elements and / or stimulation elements as described throughout the various examples of the present disclosure may be deployed within the various regions of the patient’s body 200 to sense and / or otherwise diagnose, monitor, treat, etc., various physiologic conditions such as, but not limited to, the examples or the present disclosure. In some such examples, a stimulation element 217 may be located in or near the upper airway 216 for treating sleep disordered breathing and / or near other nerves / muscles in other locations (e.g., torso, other) for treating sleep disordered breathing. In some examples, a sensing element 228 (e.g., a respiration-related sensing element) may be located anywhere within the neck 214, head 212, and / or torso 220 (or other body regions) to sense physiologic information for providing patient care (e.g., SDB, other). Sleep disordered breathing (SDB) may comprise obstructive sleep apnea (OSA), central sleep apnea (CSA), mixed sleep apnea, and / or other conditions. Moreover, in some examples regardless of their location (e.g., the neck 214, torso 220, other), the stimulation element 217 and / or sensing element 228 may be used to provide patient care for other conditions, at least some of which are later identified below.

[0034] In some examples, at least a portion of the stimulation element 217 may include part of an implantable component / device (e.g., IMD or IMD portion), such as an implantable pulse generator (IPG). In some examples, the IPG may comprise a full-sized IMD which is chronically implantable in the torso 220 (e.g., the pectoral region 222) but otherwise generally considered too large for implantation in the head-and-neck region 210. In some examples, the IPG may comprise a smaller-sized IPG which is sized and shaped to be chronically implanted in the head-and-neck region 210 or neck region 214 alone (e.g., lower neck region, mid neck region, and / or upper neck region), such as in locations, spaces, etc. (e.g., near larynx) in which a full-sized IPG would not reasonably fit. In some examples in which the IMD (e.g., IPG) is generally chronically implanted in the neck region 214, a portion of the IPG or the entire IPG may be chronically implanted at a transition of a lower portion of the neck 214 and an upper portion of the torso 220, such as (but not limited to) at or near a clavicle, manubrium, sternum, etc. In some examples, the smaller-sized IPG may sometimes be referred to as a microstimulator.

[0035] In some examples, the neck 214 may comprise submandibular locations in an anterior cervical region and includes locations superior to the clavicle. However, as noted above, in some examples, the neck 214 may comprise locations at or near transitions of the lower portion of the neck 214 and the upper portion of the torso 220.

[0036] The implantable components (e.g., IPG, other) may include a stimulation / control circuit, a power supply (e.g., non-rechargeable, rechargeable), communication elements (e.g., receivers, transmitters, transceivers), and / or other components. In some examples, the stimulation element 217 may also include a stimulation electrode and / or stimulation lead connected to the implantable pulse generator.

[0037] Further details regarding the location, structure, operation, and / or use of the sensing element 228, external element(s) 250, and / or stimulation element 217 are described below in association with FIGS. 1B and 20-13.

[0038] In some examples, at least a portion of the stimulation element 217 may include part of an external component / device such as, but not limited to, the external component including a pulse generator (e.g., stimulation / control circuitry), power supply (e.g., rechargeable, non-rechargeable), and / or other components. In some examples, a portion of the stimulation element 217 may be implantable and a portion of the stimulation element 217 may be external to the patient. In some such examples, the implantable portion of the stimulation element 217 may sometimes be referred to as a passive stimulation element at least because such implantable portion does not store power and / or does not generate a stimulation signal (and / or related control signals), but instead wirelessly receives such power and / or stimulation signal from an external component located externally of the patient. However, in some examples, the passive stimulation element 217 may receive such power and / or stimulation signal from another implantable portion of the medical device.

[0039] Accordingly, as further shown in FIG. 2B, the various sensing element(s) 228 and / or stimulation element(s) 217 implanted in the patient’s body may be in wireless communication (e.g., connection 237) with at least one external element 250. For example, the sensing element 228 may include an acoustic sensor configured to wirelessly transmit the sensed acoustic signal to the external element 250 (e.g., to a control portion of external element 250) or may include an accelerometer sensor configured to wirelessly transmit the sensed accelerometer signal to external element 250. The external element 250 may then use the sensed acoustic signal (and / or sensed accelerometer signal) to wirelessly control the stimulation element 217. In some examples, a sensing portion 171 of the external element 250 may comprise an acoustic sensor (and / or an accelerometer sensor) instead of an implanted acoustic sensing element (and / or an implanted accelerometer sensor) 228. However, in some examples, an externally located acoustic (and / or accelerometer) sensor (e.g., 271 in FIG. 2B) may be provided in addition to an implanted acoustic (and / or accelerometer) sensor, whereby the externally-located acoustic (and / or accelerometer) sensor may operate in a complementary relation to the implanted acoustic (and / or accelerometer) sensor or independent of the implanted acoustic (and / or accelerometer) sensor.

[0040] As further shown in FIG. 2B, in some examples, the external element(s) 250 may be implemented via a wide variety of formats such as, but not limited to, at least one of the formats 251 including a patient support 252 (e.g., bed, chair, sleep mat, other), wearable elements 254 (e.g., finger, wrist, head, neck, shirt), noncontact elements 256 (e.g., watch, camera, mobile device, bedside appliance, other), and / or other elements 258.

[0041] As further shown in FIG. 2B, in some examples, the external element(s) 250 may include one or more different modalities 270 such as (but not limited to) a sensing portion 271, stimulation portion 272, power portion 274, communication portion 276, and / or other portion 278. The different portions 271, 272, 274, 276, 278 may be combined into a single physical structure (e.g., package, arrangement, assembly), may be implemented in multiple different physical structures, and / or with just some of the different portions 271,272, 274, 276, 278 combined together in a single physical structure.

[0042] In some examples, the external stimulation portion 272 and / or implantable portions of the stimulation element 217 may include at least some of substantially the same features and attributes of at least the stimulation arrangements, as further described below in association with FIGS. 1B and 2C-13.

[0043] In some examples, the external power portion 274 and / or power components associated with the stimulation element 217 (e.g., implantable portions) may include at least some of substantially the same features and attributes of at least the stimulation arrangements, as further described throughout the examples of the present disclosure. In some such examples, the respective power portion, components, etc. may include a rechargeable power element (e.g., supply, battery, circuitry elements) and / or non-rechargeable power elements (e.g., battery). In some examples, the external power portion 274 may include a power source by which a power component of the stimulation element 217 (e.g., implantable portions) may be recharged.

[0044] In some examples, the implantable components of (and / or associated with) the stimulation element 217 which comprise power elements may receive power from (or via) the external power portion 274 of the external element 250 but not store the received power. Instead, the received power may be used immediately (or with minor delay) as part of transmitting a stimulation signal (received from or via the stimulation portion 272) via the stimulation element 217 to target tissues within the patient’s body.

[0045] In some examples, the wireless communication portion 276 (e.g., the connection / link at 237) may be implemented via various forms of radio frequency communication and / or other forms of wireless communication, such as (but not limited to) magnetic induction telemetry, Bluetooth (BT), Bluetooth Low Energy (BLE), near infrared (NIE), near-field protocols, Wi-Fi, Ultra-Wideband (UWB), ultrasonic waves, and / or other short range or long range wireless communication protocols suitable for use in communicating between implanted components and external components in a medical device environment.

[0046] Examples are not so limited as expressed by the other portion 278 via which other aspects of implementing medical care may be embodied in the external element(s) 250 to relate to the various implanted and / or external components described above.

[0047] FIG. 2C schematically represents a control portion 290, which may include at least some of substantially the same features and attributes as the control portion 1000 in FIG. 12A described below. The control portion 290 may be used to implement at least some of the various example devices and / or example methods of the present disclosure as described herein. In some examples, the control portion 290 may form part of, and / or be in communication with, the sensing element 228 and / or the stimulation element 217 in FIG. 2B, the external element(s) 250, and / or other medical device (or portions thereof), as further described below.

[0048] Returning to FIG. 1A, the IMD 130 can be programmed to operate in various manners. In general terms, the IMD 130 includes a controller 150 and a memory 152. The controller 150 comprises one or more processing units. In response to or based upon commands received via an input and / or machine readable instructions (including software) contained in the memory 152, the controller 150 operates to generate control signals directing operation of the stimulation component 140 to selectively control stimulation of a target tissue. In this regard, the controller 150 can be programmed to operate, or can operate as part of, a care engine 160 that represents or entails various instructions or programming according to which stimulation will be delivered to the patient (including one or more therapeutic regimens) via the stimulation component 140, as well as other possible actions. In some examples, the care engine 160 can be viewed as operating one or more closed loop modes 162 that are programmed (e.g., instruction(s)) to prompt delivery of formatted stimulation cycles (e.g., formatted in terms of one or more of amplitude, pulse width, frequency, pulse train length, etc.) in response to and / or based on sensed patient respiratory information as determined from information signaled by the respiration-related sensing component 142. It will be understood that a number of other operational modes can be provided or operated by the care engine 160 that may or may not utilize or make reference to patient respiratory information, such as other closed loop modes or open loop modes.

[0049] Closed loop mode(s) 162 utilizing sensed patient respiratory information can be implemented using the sensed information to control the particular timing of the stimulation according to respiratory information, in which the stimulation periods (or respective stimulation cycles) are synchronized with (i.e., coincide with) specific portions (e.g., inspiratory phase or portions thereof) of the patient’s respiratory cycle(s). In some examples, stimulation can be provided or performed with each respiratory cycle (i.e., each breath); in other examples, stimulation can be provided or performed on every Nth breath, skipping (N-1) breaths in between (e.g., still synchronized, but not stimulating at each breath). In some examples, stimulation is delivered to a single target site. In other examples, multiple (i.e., two or more) target sites (e.g., hypoglossal nerve and an IHM-innervating nerve, etc.) may be stimulated in a manner that is synchronized with the specific portions of the patient’s respiratory cycle(s). With these and related embodiments, multiple target sites can be stimulated in an interleaved manner (e.g., a first target site is stimulated relative to a first respiratory cycle, and a second target site is stimulated relative to a subsequent, second respiratory cycle). In yet other examples, two (or more) devices can be deployed. In some embodiments, a first device is arranged and operated to apply stimulation to a first target site, and a second device is arranged and operated to sense a parameter at a second target site. In other embodiments, a first device is arranged and operated at a first site to apply stimulation and to sense a parameter, and a second device is arranged and operated at a second site to apply stimulation. Regardless, in some such examples, for each stimulation cycle, a stimulation period is started prior to an onset of the inspiratory phase and this stimulation period is stopped exactly at the end of the inspiratory phase or stopped just after the end of the inspiratory phase. In some examples, the sensed respiratory information provides a respiratory waveform (e.g., respiration morphology) that comprises a respiratory period, which includes an inspiratory phase, an expiratory active phase, and an expiratory pause phase. In one aspect, the respiratory period corresponds to a duration of a respiratory cycle, with this duration comprising a sum of a duration of the inspiratory phase, a duration of the expiratory active phase, and a duration of the expiratory pause phase.

[0050] In some examples of “synchronization,” synchronization of the stimulation relative to the inspiratory phase may extend to a pre-inspiratory period and / or a post-inspiratory phase. For instance, in some such examples, a beginning of the synchronization may occur at a point in each respiratory cycle which is just prior to an onset of the inspiratory phase. In some examples, this point may be about 200 milliseconds, or 300 milliseconds prior to an onset of the inspiratory phase. In some examples in which the stimulation (i.e., each stimulation period) is synchronous with at least a portion of the inspiratory phase, the upper airway muscles are contracted via the stimulation to ensure they are open at the time the respiratory drive controlled by the central nervous system initiates an inspiration (inhalation). In some such examples, in combination with the stimulation period of a stimulation cycle occurring during the inspiratory phase, example implementation of the above-noted pre-inspiratory stimulation helps to ensure that the upper airway is open before the negative pressure of inspiration within the respiratory system is applied via the diaphragm of the patient’s body. In one aspect, this example arrangement may minimize the chance of constriction or collapse of the upper airway, which might otherwise occur if flow of the upper airway flow were too limited prior to the full force of inspiration occurring. In some such examples, the stimulation of the upper airway patency-related nerve may be synchronized to occur with at least a portion of the expiratory period.

[0051] By way of non-limiting example, FIG. 3A represents an example of a respiratory waveform 300 of a normal breathing pattern. Each respiratory cycle 310 includes an inspiratory phase 320 and an expiratory phase 330. A transition from the inspiratory phase 320 to the expiratory phase 330 is generally labeled at 340; a transition from the expiratory phase 330 to the inspiratory phase 320 is generally labeled at 342. The inspiratory phase 320 thus initiates at the expiration-to-inspiration transition 342, continues to a peak portion (or inspiration peak portion) 322, then progresses to the inspiration-to-expiration transition 340; the expiratory phase 330 begins at the inspiration-to-expiration transition 340, continues to a trough portion (or expiration peak portion) 332, then progresses to the next expiration-to-inspiration transition 342. In this regard, the expiratory phase 330 is sometimes characterized by a pause 334 just prior to the expiration-to-inspiration transition 340.

[0052] As shown in FIG. 3B (that otherwise repeats the respiratory waveform 300 of FIG. 3A), with some embodiments in which the close loop mode(s) are implemented to deliver stimulation pulses that are triggered by or synchronized with the inspiratory phase 320, stimulation 350 is started just prior to an onset of the inspiratory phase 320 (i.e., just prior to the expiration-to-inspiration transition 342) and the stimulation is stopped exactly at the end of the inspiratory phase 320 or stopped just after the end of the inspiratory phase 320 (i.e., exactly at or just after the inspiration-to-expiration transition 340 or onset of the expiratory phase 330).

[0053] With additional reference to FIG. 1B, the closed loop mode(s) 162 intended to deliver stimulation cycles that are synchronized with the inspiratory phase 320 (or other respiratory phase) can operate various instructions that utilize identification of a designated parameter(s) or attribute(s) in the patient respiration information as provided by the respiration-related sensing component 142. With these and related embodiments, the designated parameter or attribute has an understood relationship to the patient’s expected respiratory waveform 300; thus, expected respiratory cycle timing can be determined or estimated based upon sensed occurrence of the designated parameter or attribute. For example, the closed loop mode(s) can be formatted to identify occurrence of a parameter or attribute in the sensed respiration information that is indicative of one or more of the expiration peak portion 332, the inspiration peak portion 322, the pause 334, the expiration-to-inspiration transition 340, the expiration-to-inspiration transition 342, etc. In some such examples, the identification of an occurrence of such parameters / attributes in the sensed respiration information (by which timing of a subsequent respiratory event of interest is determined) may be implemented according to at least some of substantially the same features and attributes as described in: US Application Publication No. 2024 / 0197200, published on June 20, 2024, titled RESPIRATION SENSING; US Patent No. 12,262,988, issued on April 1, 2025, titled “RESPIRATION DETECTION”; PCT Publication No. WO 2024 / 233290, published on November 14, 2024, titled RESPIRATION SENSING”, the entire teachings of each of which are incorporated herein by reference.

[0054] Once the designated parameter or attribute is identified or deemed to have occurred, expected or predicted timing of one or more respiratory cycle events of interest can be made relative to the point in time of the sensed occurrence. By way of non-limiting example, where the sensed respiration information is indicative of breathing pressure, a determination that the respiration information indicates a decrease in breathing pressure below a threshold or baseline (e.g., over a pre-determined time period) can be designated as occurrence of a “peak” of the expiration peak portion 332; predicted timing of a subsequent respiratory event of interest (e.g., the expiration-to-inspiration transition 342) can be determined from the point in time of the sensed occurrence, with delivery of a stimulation cycle being initiated relative to the predicted timing of the subsequent respiratory event of interest.

[0055] The closed loop mode(s) 162 can comprise one or more functions which may be used by a clinician (or patient) to adjust one or more variables in the corresponding instructions. For example, a “maximum stimulation time” function can be provided and which may be used by a clinician or patient to adjust a maximum time for the stimulation period of a given stimulation cycle, after which the non-stimulation period takes place. The “on period” may extend for a selectable, predetermined period of time. In some examples, the “on period” for stimulation is intended to coincide with (or at least partially coincide with) the inspiratory phase for at least some respiratory cycles. For example, where the closed loop mode operates to initiate the “on period” at a predetermined time following sensed occurrence of a designated parameter or attribute in the sensed respiration information that otherwise corresponds with a predicted start of the inspiratory phase and a length of the stimulation period is expected to coincide with a length of the inspiratory phase, it can be expected that the stimulation cycle will end approximately at the end of the inspiratory phase. In some such examples, once enabled by the user or clinician, the maximum stimulation time is implemented regardless of sensed or detected phases. With these and related embodiments, the instructions can be formatted to provide a default maximum stimulation time; the clinician (or patient) is afforded the ability to incrementally increase or decrease the maximum stimulation time, for example between a predetermined minimum and a predetermined maximum. Other stimulation-related functions can optionally be provided with the close loop mode(s) 162.

[0056] Sensing-related functions can also be provided with one or more of the closed loop modes 162. For example, the instructions of the closed loop mode 162 can be formatted to designate or identify occurrence of a parameter or attribute in the sensed respiration information when a signal (or a parameter thereof such as rate of change) from the respiration-related sensor meets a threshold value. With these and related embodiments, a “threshold” function can be provided and which may be used by a clinician (or patient) to adjust the threshold value. In some examples, the instructions can be formatted to provide a default threshold value; the clinician (or patient) is afforded the ability to incrementally increase or decrease the threshold value, for example between a predetermined minimum and a predetermined maximum. In other examples, a “sensitivity” function can be provided and which may be used by a clinician (or patient) to adjust a sensitivity of the respiration-related sensor. In some examples, the instructions can be formatted to provide a default sensitivity value; the clinician (or patient) is afforded the ability to incrementally increase or decrease the sensitivity value, for example between a predetermined minimum and a predetermined maximum. In other examples, an “invert” function can be provided and which may be used by a clinician (or patient) to invert the respiration-related sensor signal as reviewed by the closed loop mode 162 instructions. As a point of reference, with some implementations, depending on the particular angle at which the controller 150 and sensor are implanted in a particular patient, and / or depending on the particular sleeping position in which the patient is arranged, the sensor signal as may be inverted as interpreted by the closed loop mode instructions that is / are otherwise operating on the controller 150. With these and related embodiments, the “invert” function can afford the clinician the ability to cause the closed loop mode instructions to consider / review an inverted form of the received sensor signal. Other sensing-related functions can optionally be provided with the close loop mode(s).

[0057] With the above explanations in mind, it can be useful to evaluate and / or adjust the efficacy of the closed loop mode(s) 162 as described above (e.g., formatted to utilize or reference sensed patient respiration-related information for the timed delivery of stimulation cycles) in view of potentially undesired timing of delivered stimulation relative to the patient’s respiratory cycle. One example method 400 for evaluating and / or adjusting sensor efficacy via programming change(s) in accordance with principles of the present disclosure is shown in FIG. 4. The method 400 can be employed with an implantable medical device (e.g., the I MD 102, 130, 182 described above) operating a closed loop mode that is programmed or intended to prompt delivery of a stimulation cycle synchronized with the patient’s inspiratory phase in the treatment of sleep disordered breathing based upon respiration information provided by one or more sensors. At 410, while the IMD is operating to deliver stimulation pursuant to instructions of a closed loop mode that otherwise references sensed respiration-related information, a delivered stimulation cycle(s) is observed in the patient. This observation can, in some examples, be performed by a clinician as part of an inclinic patient review. By way of non-limiting example, during an in-clinic patient review (e.g., initial calibration following implant, follow-up visit, annual review, sleep study, etc.), the clinician can employ various techniques or devices to assist in visually observing stimulation being delivered to the patient such as electromyography (EMG). With these and related embodiments, an EMG sensor can be applied to the patient (e.g., the patient’s chin); as stimulation is being delivered, the EMG sensor will sense or detect stimulation artifact(s) that is / are displayed to the clinician. Other techniques for observing delivered stimulation are also acceptable. Along these same lines, subsequent steps of the method 400 include various comparisons of the observed stimulation cycle(s) relative to an observed aspect of the corresponding patient respiratory cycle(s) as described in greater detail below. The respiratory cycle(s) can be observed or monitored in various fashions. In some examples, a clinician can simply watch the patient as s / he breathes for the respiratory aspect in question. In other examples, the clinician can employ various techniques or devices to assist in visually understanding the patient’s respiratory cycles such as via a nasal cannula pressure transducer that measures the pressure differences between inhalation and exhalation. This measurement may sometimes be referred to as a pressure transducer air flow (PTAF) measurement. An output signal of the PTAF represents airflow changes or flow effect, and can be viewed as the patient’s respiratory waveform from which the respiratory aspect of interest can readily be determined.

[0058] At least one observed stimulation cycle is compared with the corresponding respiration cycle(s) of the patient (e.g., a visual comparison performed by the clinician) to determine whether or not stimulation stops when the patient’s exhalation starts at 412. As a point of reference, a representation of stimulation continuing to be applied after the patient’s exhalation has started is shown in FIG. 5. In particular, a stimulation signal 500 relative to a patient’s respiratory waveform 502 is shown. The stimulation signal 500 comprises a series of stimulation cycles 503, with each stimulation cycle 503 comprising a stimulation period 504 and a non-stimulation period 505. For one of the respiration cycles of the waveform 502, onset of inhalation is identified at 506 and onset of exhalation is identified at 508. With the example of FIG. 5, suboptimal sensor-related sensing can result in one or more of the stimulation cycles 503 continuing to be applied following the onset of exhalation 508.

[0059] Returning to FIG. 4, if it is determined that stimulation does not stop when exhalation starts (i.e., “NO” at 412), one or more sensor-related settings associated with the closed loop mode are changed or confirmed at 414. In some examples, the sensor-related setting(s) associated with 414 can affect or dictate the manner in which sensor-generated information is considered by the closed loop mode in sensing or predicting an occurrence of at least a portion of the patient’s exhalation or expiratory phase (i.e., the expiratory phase 330 of FIG. 3A), for example the expiration peak portion (i.e., the expiration peak portion 332 of FIG. 3A). For example, one or more of a sensitivity setting, a threshold value, etc., utilized by the closed loop mode can be changed or confirmed. In some embodiments, a recommended setting(s) can be provided to the clinician at 414. For example, one or more of a specific sensitivity value or setting, a specific threshold value or setting, etc., can be recommended and implemented at 414 (that may otherwise differ from current or default settings). A variety of other sensor-related setting can be confirmed or changed at 414. With examples in which the clinician is advised at 414 to confirm or change one or more sensor-related settings, the clinician can implement the change(s) via the clinician programmer 102 (FIG. 1A).

[0060] Once the setting(s) have been changed (or confirmed) at 414, operation of the I MD to deliver stimulation pursuant to the updated instructions of the closed loop mode continues over a wait period 416 before additional observations or comparisons are made (thereby allowing the change(s) at 414 to take effect). The wait period 416 can have a wide variety of predetermined durations, and in some examples can be on the order of 10 minutes.

[0061] Following the wait period 416, at least one observed stimulation cycle is compared with the corresponding respiration cycle(s) of the patient (e.g., a visual comparison performed by the clinician) to again determine whether or not stimulation stops when the patient’s exhalation starts at 412. If it is determined that stimulation does not stop when exhalation starts (i.e., “NO” at 412), one or more sensor-related settings associated with the closed loop mode are changed or confirmed at 418. The setting(s) considered at 418 can be the same setting(s) as considered at 414 and / or can entail other sensor-related settings. Similar to the descriptions above, in some embodiments a recommended setting(s) can be provided to the clinician at 418. For example, one or more of a specific sensitivity value, threshold value, etc. can be implemented at 418 (that may otherwise differ from current settings). A variety of other sensor-related settings can be confirmed or changed at 418. With examples in which the clinician is advised at 418 to change or confirm one or more sensor-related settings, the clinician can implement the change(s) via the clinician programmer 102 (FIG. 1A).

[0062] Once the setting(s) have been changed (or confirmed) at 418, operation of the I MD to deliver stimulation pursuant to the updated instructions of the closed loop mode continues over a wait period 420 before additional observations or comparisons are made (thereby allowing the change(s) at 418 to take effect). The wait period 420 can have a wide variety of predetermined durations, and in some examples can be on the order of 10 minutes.

[0063] Following the wait period 420 and / or if it is determined at 412 that stimulation does stop when exhalation starts, at least one observed stimulation cycle is compared with the corresponding respiration cycle(s) of the patient (e.g., a visual comparison performed by the clinician) to determine whether or not stimulation starts when the patient’s exhalation starts at 422. As a point of reference, a representation of stimulation starting when the patient’s exhalation starts is shown in FIG. 6. In particular, a stimulation signal 520 relative to a patient’s respiratory waveform 522 is shown. The stimulation signal 520 comprises a series of stimulation cycles 523, with each stimulation cycle 523 comprising a stimulation period 524 and a non-stimulation period 525. For one of the respiration cycles of the waveform 522, onset of inhalation is identified at 526 and onset of exhalation is identified at 528. With the example of FIG. 6, suboptimal sensor-related sensing can result in one or more of the stimulation periods 524 starting at the onset of exhalation 528. Moreover, it could be observed or concluded from the information of FIG. 6 that each stimulation period 524 is nearly completely missing the inspiratory phase and instead coinciding with the expiratory phase.

[0064] Returning to FIG. 4, if it is determined that stimulation does start when exhalation starts (i.e., “YES” at 422), one or more sensor-related settings associated with the closed loop mode are changed at 424. In some examples, the sensor-related setting(s) associated with 424 can affect or dictate the manner in which sensor-generated information is considered by the closed loop mode in sensing or predicting an occurrence of at least a portion of the patient’s exhalation or expiratory phase (i.e., the expiratory phase 330 of FIG. 3A), for example the expiration peak portion (i.e., the expiration peak portion 332 of FIG. 3A). For example, an invert setting utilized by the closed loop mode can be changed or confirmed. In some embodiments, a recommended invert status setting can be provided to the clinician at 424. With these and related embodiments, the clinician can be instructed at 424 to change the invert status setting from “OFF” to “ON” (or otherwise cause the closed loop mode instructions to consider / review an inverted form of the received sensor signal). With examples in which the clinician is advised at 424 to change the invert setting, the clinician can implement the change via the clinician programmer 102 (FIG. 1A).

[0065] Once the setting(s) have been changed (or confirmed) at 424, operation of the I MD to deliver stimulation pursuant to the updated instructions of the closed loop mode continues over a wait period 426 before additional observations or comparisons are made (thereby allowing the change(s) at 424 to take effect). The wait period 426 can have a wide variety of predetermined durations, and in some examples can be on the order of 10 minutes.

[0066] Following the wait period 426 and / or if it is determined at 422 that stimulation does not start when exhalation starts, at least one observed stimulation cycle is compared with the corresponding respiration cycle(s) of the patient (e.g., a visual comparison performed by the clinician) to determine whether or not stimulation stops before the patient’s inhalation ends at 428. As a point of reference, a representation of stimulation stopping before the patient’s inhalation ends is shown in FIG. 7. In particular, a stimulation signal 540 relative to a patient’s respiratory waveform 542 is shown. The stimulation signal 540 comprises a series of stimulation cycles 543, with each stimulation cycle 543 comprising a stimulation period 544 and a non-stimulation period 545. For one of the respiration cycles of the waveform 542, onset of inhalation is identified at 546 and onset of exhalation is identified at 548. With the example of FIG. 7, suboptimal sensor-related sensing can result in one or more of the stimulation periods 544 stopping before inhalation ends (e.g., stimulation ends before the onset of exhalation 548).

[0067] Returning to FIG. 4, if it is determined that stimulation does stop before inhalation finishes (i.e., “YES” at 428), one or more stimulation-related settings associated with the closed loop mode are changed or confirmed at 430. In some examples, the stimulation-related setting(s) associated with 430 can relate to a time setting for the “on period” of stimulation of a given stimulation cycle. For example, a maximum stimulation time setting utilized by the closed loop mode can be changed or confirmed. In some embodiments, a recommended setting(s) (e.g., a maximum stimulation time setting) can be provided to the clinician at 430. For example, a specific maximum time setting value can be implemented at 430 (that may otherwise differ from a current or default setting). A variety of other stimulation-related settings can be confirmed or changed at 430. With examples in which the clinician is advised at 430 to confirm or change one or more stimulation-related settings, the clinician can implement the change(s) via the clinician programmer 102 (FIG. 1A).

[0068] Once the setting(s) have been changed (or confirmed) at 430, operation of the I MD to deliver stimulation pursuant to the updated instructions of the closed loop mode continues over a wait period 432 before additional observations or comparisons are made (thereby allowing the change(s) at 430 to take effect). The wait period 432 can have a wide variety of predetermined durations, and in some examples can be on the order of 10 minutes.

[0069] Following the wait period 432 and / or if it is determined at 428 that stimulation does not stop before inhalation ends, at least one observed stimulation cycle is compared with the corresponding respiration cycle(s) of the patient (e.g., a visual comparison performed by the clinician) to determine whether or not stimulation stops when the patient’s exhalation starts at 434. As a point of reference, a representation of stimulation not stopping when the patient’s exhalation starts is shown in FIG. 8. In particular, a stimulation signal 560 relative to a patient’s respiratory waveform 562 is shown. The stimulation signal 560 comprises a series of stimulation cycles 563, with each stimulation cycle 563 comprising a stimulation period 564 and a non-stimulation period 565. For one of the respiration cycles of the waveform 562, onset of inhalation is identified at 566 and onset of exhalation is identified at 568. With the example of FIG. 8, suboptimal sensor-related sensing can result in one or more of the stimulation periods 564 not stopping at the onset of exhalation 568.

[0070] Returning to FIG. 4, if it is determined that stimulation does not stop when exhalation starts (i.e.., “NO” at 434), one or more stimulation-related settings associated with the closed loop mode are changed or confirmed at 436. In some examples, the stimulation-related setting(s) associated with 436 can relate to a time setting for the “on period” of stimulation of a given stimulation cycle. For example, a maximum stimulation time setting utilized by the closed loop mode can be changed or confirmed. In some embodiments, a recommended setting(s) can be provided to the clinician at 436. For example, a specific maximum time setting value can be recommended to, and implemented by, the clinician at 436 (that may otherwise differ from a current or default setting). A variety of other stimulation-related settings can be confirmed or changed at 336. With examples in which the clinician is advised at 436 to confirm or change one or more stimulation-related settings, the clinician can implement the change(s) via the clinician programmer 102 (FIG. 1A).

[0071] Once the setting(s) have been changed (or confirmed) at 436, operation of the I MD to deliver stimulation pursuant to the updated instructions of the closed loop mode continues over a wait period 438 before additional observations or comparisons are made (thereby allowing the change(s) at 436 to take effect). The wait period 438 can have a wide variety of predetermined durations, and in some examples can be on the order of 10 minutes.

[0072] In some embodiments, methods of the present disclosure can be formatted for use with a medical device, such as an implantable medical device (e.g., the IMD 102, 130, 180 described above) operating a closed loop mode intended to prompt delivery of stimulation pulses synchronized with the patient’s inspiratory phase in the treatment of sleep disordered breathing based upon respiration information provided by one or more sensors, with the close loop mode instructions programmed to include at least a sensor sensitivity value, an exhalation threshold value, a sensor signal invert status, and a maximum stimulation time setting. Each of the sensor sensitivity value, the exhalation threshold value, the sensor signal invert status, and the maximum stimulation time setting can be changed or altered, and each are assigned an initial or default value or setting. In some such examples, one or more of the sensor sensitivity value and the exhalation threshold value can be designated or expressed as an integer, and can be increased or decreased in integer steps. With these and related embodiments, a particular integer may or may not directly implicate a qualitative value or scale (e.g., the sensor sensitivity value could be an integer of -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6; with this example scalar approach, a sensitivity value of “0” need not represent or entail that sensor sensitivity has been turned “off”, but rather a sensitivity mid-way between a highest and lowest available sensitivity setting). Other formats are also acceptable, including any desired form of measurement, units, parameters according to a desired scale, etc. With this in mind, another method 600 in accordance with principles of the present disclosure for evaluating and / or adjusting sensor efficacy via programming change(s) and useful with these and similar arrangements is shown in FIG. 9. In general terms, the method 600 is akin to the method 400 (FIG. 4) described above and includes more specific recommendations as described below.

[0073] At 610, while the IMD is operating to deliver stimulation pursuant to instructions of the closed loop mode, delivered stimulation cycles are observed in the patient. These observations can assume any of the forms described above. Along these same lines, subsequent steps of the method 600 include various comparisons of the observed stimulation cycle(s) relative to an observed aspect of the corresponding patient respiratory cycle(s) as described in greater detail below. The respiratory cycle(s) observations can be made using any of the techniques described above.

[0074] At least one observed stimulation cycle is compared with the corresponding respiration cycle(s) of the patient (e.g., a visual comparison performed by the clinician) to determine whether or not stimulation stops when the patient’s exhalation starts at 612. If it is determined that stimulation does not stop when exhalation starts (i.e., “NO” at 612), one or more sensor-related settings associated with the closed loop mode are changed or confirmed at 614. In some embodiments, recommended settings can be provided to the clinician at 614. In particular, a specific sensitivity value or setting and a specific threshold value or setting can be recommended and implemented at 614 (that may otherwise differ from current or default settings). With examples in which the closed loop mode instructions utilize a sensor sensitivity value, the clinician can be advised at 614 to select a sensor sensitivity value of “-2”. As a point of reference, in some non-limiting embodiments, the closed loop mode instructions can implement a default sensor sensitivity value of “-4”; under these circumstances, one possible action at 614 will entail changing the sensor sensitivity value to “-2”. Additionally, with examples in which the closed loop mode instructions utilize a sensor threshold value (e.g., exhalation threshold value), the clinician can be advised at 614 to select or confirm a sensor threshold value of 1”. As a point of reference, in some non-limiting embodiments, the closed loop mode instructions can implement a default sensor threshold value of “-1”; under these circumstances, one possible action at 614 would entail confirming that the sensor threshold value is set to “-1” (and if not, then changing the sensor threshold value to “-1”). A variety of other sensor-related settings can be confirmed or changed at 614. With examples in which the clinician is advised at 614 to confirm or change sensor-related settings, the clinician can implement the change(s) via the clinician programmer 102 (FIG. 1A).

[0075] Once the setting(s) have been changed (or confirmed) at 614, operation of the I MD to deliver stimulation pursuant to the updated instructions of the closed loop mode continues over a wait period of 10 minutes at 616 before additional observations or comparisons are made (thereby allowing the change(s) at 614 to take effect). The wait period 616 can have a wide variety of other predetermined durations.

[0076] Following the wait period 616, at least one observed stimulation cycle is compared with the corresponding respiration cycle(s) of the patient (e.g., a visual comparison performed by the clinician) to again determine whether or not stimulation stops when the patient’s exhalation starts at 612. If it is determined that stimulation does not stop when exhalation starts (i.e., “NO” at 612), one or more sensor-related settings associated with the closed loop mode are changed or confirmed at 618. The setting(s) considered at 618 can be the same setting(s) as considered at 614 and / or can entail other sensor-related settings. Similar to the descriptions above, in some embodiments a recommended setting(s) can be provided to the clinician at 618. For example, one or more of a specific sensitivity value, threshold value, etc. can be implemented at 618 (that may otherwise differ from current settings). With examples in which the closed loop mode instructions utilize a sensor sensitivity value, the clinician can be advised at 618 to select a sensor sensitivity value of “0”. Continuing the non-limiting example above with respect to step 614, one possible action at 618 could entail changing the sensor sensitivity value from “-2” to “0”. Additionally, with examples in which the closed loop mode instructions utilize a sensor threshold value (e.g., exhalation threshold value), the clinician can be advised at 618 to select a sensor threshold value of “0”. Continuing the non-limiting example above with respect to step 614, one possible action at 618 could entail changing the sensor threshold value from “-1” to “0”. With examples in which the clinician is advised at 618 to change or confirm one or more sensor-related settings, the clinician can implement the change(s) via the clinician programmer 102 (FIG. 1A).

[0077] Once the setting(s) have been changed (or confirmed) at 618, operation of the I MD to deliver stimulation pursuant to the updated instructions of the closed loop mode continues over a wait period of 10 minutes at 620 before additional observations or comparisons are made (thereby allowing the change(s) at 618 to take effect). The wait period 620 can have a wide variety of other predetermined durations.

[0078] Following the wait period 620 and / or if it is determined at 612 that stimulation does stop when exhalation starts, at least one observed stimulation cycle is compared with the corresponding respiration cycle(s) of the patient (e.g., a visual comparison performed by the clinician) to determine whether or not stimulation starts when the patient’s exhalation starts at 622. If it is determined that stimulation does start when exhalation starts (i.e., “YES” at 622), the invert setting utilized by the closed loop mode is changed or confirmed. In some embodiments, a recommended invert status setting can be provided to the clinician at 624. With these and related embodiments, the clinician is instructed at 624 to change the invert status setting from “OFF” to “ON” (or otherwise cause the closed loop mode instructions to consider / review an inverted form of the received sensor signal). With examples in which the clinician is advised at 624 to change the invert setting, the clinician can implement the change via the clinician programmer 102 (FIG. 1A).

[0079] Once the invert setting has been changed (or confirmed) at 624, operation of the I MD to deliver stimulation pursuant to the updated instructions of the closed loop mode continues over a wait period of 10 minutes at 626 before additional observations or comparisons are made (thereby allowing the change at 624 to take effect). The wait period 626 can have a wide variety of other predetermined durations.

[0080] Following the wait period 626 and / or if it is determined at 622 that stimulation does not start when exhalation starts, at least one observed stimulation cycle is compared with the corresponding respiration cycle(s) of the patient (e.g., a visual comparison performed by the clinician) to determine whether or not stimulation stops before the patient’s inhalation ends at 628. If it is determined that stimulation does stop before inhalation finishes (i.e., “YES” at 628), the maximum stimulation time setting utilized by the closed loop mode is changed or confirmed at 630. In some embodiments, a recommended setting can be provided to the clinician at 630. For example, a specific maximum time setting value can be implemented at 630 (that may otherwise differ from a current or default setting). With examples in which the closed loop mode instructions utilize a maximum stimulation time value, the clinician can be advised at 630 to select a maximum stimulation time value of 5 seconds. As a point of reference, in some non-limiting embodiments, the closed loop mode instructions can implement a default maximum stimulation time value of 4 seconds; under these circumstances, one possible action at 630 could entail changing the maximum stimulation time value from 4 seconds to 5 seconds. With examples in which the clinician is advised at 630 to confirm or change the maximum stimulation time value or setting, the clinician can implement the change via the clinician programmer 102 (FIG. 1A).

[0081] Once the maximum stimulation time setting or value has been changed (or confirmed) at 630, operation of the IMD to deliver stimulation pursuant to the updated instructions of the closed loop mode continues over a wait period of 10 minutes at 632 before additional observations or comparisons are made (thereby allowing the change at 630 to take effect). The wait period 632 can have a wide variety of other predetermined durations.

[0082] Following the wait period 632 and / or if it is determined at 628 that stimulation does not stop before inhalation ends, at least one observed stimulation cycle is compared with the corresponding respiration cycle(s) of the patient (e.g., a visual comparison performed by the clinician) to determine whether or not stimulation stops when the patient’s exhalation starts at 634. If it is determined that stimulation does not stop when exhalation starts (i.e.., “NO” at 634), the maximum stimulation time setting utilized by the closed loop mode is changed or confirmed at 636. In some embodiments, a recommended maximum stimulation time setting or value can be provided to the clinician at 636. With examples in which the closed loop mode instructions utilize a maximum stimulation time value, the clinician can be advised at 536 to select a maximum stimulation time value of 3 seconds. As a point of reference, in some non-limiting embodiments, the closed loop mode instructions can implement a default maximum stimulation time value of 4 seconds; under these circumstances, one possible action at 636 could entail changing the maximum stimulation time value to 3 seconds. With examples in which the clinician is advised at 636 to confirm or change the maximum stimulation time value or setting, the clinician can implement the change via the clinician programmer 102 (FIG. 1A).

[0083] Once the maximum stimulation time setting or value has been changed (or confirmed) at 636, operation of the IMD to deliver stimulation pursuant to the updated instructions of the closed loop mode continues over a wait period of 10 minutes at 638 before additional observations or comparisons are made (thereby allowing the change at 636 to take effect). The wait period 638 can have a wide variety of other predetermined durations.

[0084] Some methods of the present disclosure (e.g., the methods of FIGS. 4 and 9) can further include determining or identifying whether a currently-operating closed loop mode (otherwise intended to prompt delivery of stimulation pulses synchronized with the patient’s inspiratory phase based upon respiration information provided by one or more sensors) is causing undesired patient respiratory events due to undesired stimulation timing and thus could benefit from one or more programming changes. In other words, prior to step 410 of the method 400 of FIG. 4 or prior to step 610 of the method 600 of FIG. 9, a determination is made as to whether or not stimulation timing-related concerns exist. If the closed loop mode is exhibiting acceptable efficacy in terms of the timing of delivered stimulation, the programming methods of the present disclosure are not implicated and need not be performed. If, however, the currently-operating closed loop mode is determined to have potential stimulation timing concerns, the programming methods of the present disclosure are implicated and can be performed.

[0085] The identification or determination that a currently-operating closed loop mode is exhibiting stimulation timing concerns can be made or performed in various fashions. In some examples, a clinician can observe and compare stimulation applied to the patient contemporaneously with the patient’s respiration. If an immediate change in the patient’s respiration when stimulation turns on or off is observed, it can be determined that respiratory events may be caused by undesired stimulation timing. The comparison of applied stimulation with patient respiration can be performed in various manners. In some nonlimiting examples, a clinician can employ one or more devices to assist in visually understanding a relationship between applied stimulation and the patient’s respiration, for example the PTAF (for obtaining the patient’s respiratory waveform) and the chin EMG (for obtaining stimulation artifact) techniques described above. As a point of reference, FIG. 10A is a representative comparison of applied stimulation 660 relative to a contemporaneous patient respiratory waveform 662 obtained via PTAF. Under the circumstances of FIG. 10A, there is no evidence that the applied stimulation 660 is causing airflow changes (as the respiratory waveform 662 does deviate from a normal or expected respiration pattern when the stimulation 660 is applied). Conversely, FIG. 10B is another representative comparison of applied stimulation 670 relative to a contemporaneous patient respiratory waveform 672 obtained via PTAF. Under the circumstances of FIG. 10B, there is distinct evidence that the applied stimulation 670 is causing airflow changes in the patient. The respiratory waveform 672 substantively deviates from a normal or expected respiration pattern when the stimulation 670 is applied; changes in a shape of the respiratory waveform 672 corresponding to stimulation 670 being turned ON and OFF are readily apparent.

[0086] As implicated by the explanations above, in some embodiments, methods of the present disclosure (e.g., the methods of FIGS. 4 and 9) can be performed by a clinician utilizing the clinician programmer 102 (FIG. 1A). In other embodiments, the methods of the present disclosure can be implemented by instructions or programming provided, for example, with the controller 150 (FIG. 1B), for example as part of an auto-titration operation or other automated fashion. With these and related embodiments, automated analysis of one or more signals (e.g., airflow, stimulation artifacts, etc.) can be employed to find or identify the characteristics or parameters noted in FIGS. 4 and 9 and / or that will otherwise suggest a need or desire for reprogramming. In this regard, useful signals / information can be provided from a variety of sources, such as a polysomnography (PSG) sensor, home sleep apnea testing (HST) device, medical imaging (e.g., drug-induced sleep endoscopy (DISE) system, magnetic resonance imaging (MRI)), etc. In other examples, methods of the present disclosure (e.g., the methods of FIGS. 4 and 9) can be utilized for evaluating and / or adjusting sensing efficacy under other circumstances, for example in the context of sensing or determining disease burden such as an apnea-hypopnea index (AHI) associated with at least obstructive sleep apnea (OSA). In some examples, disease burden (e.g., AHI) can be used as a criterion to determine whether or not to adjust setting(s), for example via the methods of the present disclosure (e.g., the methods of FIGS. 4 and 9).

[0087] With non-limiting examples in which a clinician performs or implements the programming methods of the present disclosure (such as the methods of FIGS. 4 and 9), some methods of the present disclosure can further include providing the clinician with visual documentation or instructions for evaluating and / or adjusting sensor efficacy via programming change(s). One non-limiting example of visual documentation 700 in accordance with principles of the present disclosure is shown in FIG. 11. The documentation 700 can be provided to the clinician in paper or electronic form (e.g., displayed on a screen of a computerlike device available to the clinician) and generally includes instructions 710 (referenced generally) in a flowchart-like format that provides step-by-step explanations to guide the clinician through review and recommended programming changes. With the non-limiting example of FIG. 11, the instructions 710 can be akin to the method 600 described above with respect to FIG. 9, although other instructions can alternatively be employed. The visual documentation 700 can further include an examples section 720 (referenced generally) that illustrates examples of suboptimal sensing conditions for enhancing the clinician’s understanding of the conditions that might otherwise implicate a need for programming change(s). The visual documentation 700 can optionally further include a warning statement 730 advising the clinician of circumstances under which the instructions 710 should be performed. For example, the warning statement 730 can remind or advise the clinician that the programming review and change(s) should only be performed when the clinician has concluded that delivered stimulation is resulting in undesired patient respiratory events due to undesired or incorrect stimulation timing. Other warning statements or formats are also acceptable.

[0088] The sense optimization clinical workflows of the present disclosure (e.g., the methods of FIGS. 4 and 9) can be implemented or performed in various settings. For example, methods of the present disclosure can be performed as part on an in-clinic patient visit, such as a sleep study. With these and related embodiments, the workflow or methods of the present disclosure can be optionally be automated by leveraging other signals available during the study (e.g., electrocardiogram (ECG), electromyogram (EMG), peripheral blood oxygen saturation (SpO2), etc.). As the patient is undergoing the sleep study (or other study), adjustments are automatically made via methods of the present disclosure using the other additional signals. Alternatively or in addition, methods of the present disclosure can be performed in an in-home setting. For example, a patient can be provided with one or more appropriate, wearable or nearable sensors that can be utilized by the patient at home. Under these and similar circumstances, the patient can be directed, or can elect, to undergo the workflow analyses of the present disclosure in their home environment, with the sensor(s) being set-up and initiated by the patient. Throughout the night, utilizing signals or data from the IMD 130 (FIG. 1B), 180 (FIG. 2A) and the in-home, external sensor(s), workflows or methods of the present disclosure are automatically executed to optimize the patient’s sense / stimulation settings. In other examples, the patient can be directed, or can elect, to undergo an at home sleep waveform study. Under these and similar circumstances, the patient’s respiratory waveform data is obtained and delivered (e.g., streamed) to a programmer or other computing device (e.g., a patient remote, a server in electronic communication with the IMD 130, 180 such as via the cloud, etc.). Processing of the waveform data is performed on the computing device (e.g., via programming instructions), and updated settings are downloaded (e.g., automatically downloaded) to the IMD 130, 180.

[0089] While the foregoing addresses evaluating and adjusting sensing efficacy primarily in relation to closed loop stimulation therapy including synchronizing stimulation periods to specific respiratory phases (e.g., inspiratory phase), it will be understood that in some examples the sensed respiratory information may be used with or without other sensed physiological information to initiate, maintain, pause and / or terminate stimulation therapy within a treatment period, such as a nightly sleep treatment period.

[0090] In addition, or an as alternative, to the techniques or algorithms implicated by FIGS. 4 and 9, the systems and methods of the present disclosure can utilize other data and / or analyses for optimizing setting(s) of one or more sensors utilized with an IMD, for example in the delivery of stimulation to a patient to treat sleep disordered breathing. In some examples, systems and methods of the present disclosure can entail automated inspiratory phase overlap fraction (IPOF) improvement following a polysomnography (PSG) study, home sleep study test (HST), or similar study. With these and related embodiments, the patient’s respiratory waveform, stimulation timings, and other sensor data obtained during the study is extracted along with the study data. The data from these two sources are aligned time-wise (or can be aligned in other manners, for example based on extracted chin artifact obtained during the study). Machine learning, parametric sweeps, or the like is then employed to optimize IPOF for the patient. In this regard, sensor settings can be optimized using one or more metrics, such as mean or median, improving the lowest percent of breaths or respiratory cycles (e.g., reduce amount of breaths 10% or less), reducing amount of breaths with less than 50-75% IPOF to minimize inversion, maximizing the amount of time stimulation occurs at start of a breath, a weighted combination of any or all of the above metrics, etc. In some examples, the machine learning or parametric sweeps can be delivered or sent (e.g., wirelessly) to a dedicated patient management platform (e.g., cloud based) or a programmer (e.g., the clinician programmer 102 (FIG. 1A)) that in turn is programmed to determine or calculate new sensor settings.

[0091] Regardless of how determined, the new sensor setting(s) can be implemented in various fashions. For example, a clinician can re-program the controller otherwise operating to control operations of the patient’s IMD (e.g., the controller 150 (FIG. 1B), the care engine 160 (FIG. 1B), etc.); the new setting(s) can also be saved in a dedicated patient management platform associated with the patient. In other examples, the patient’s IMD can be automatically reprogrammed with the new sensor setting(s) (e.g., the controller 150 (FIG. 1B), the care engine 160 (FIG. 1B), etc., can be re-programmed) through a dedicated device or remote control (e.g., a dedicated remote control, a dedicated software application operating on a computing device such as a smart phone) in wireless communication with the IMD via data delivered to the dedicated device though a patient management platform associated with the patient (e.g., a cloud-based platform). In other examples, the patient’s IMD can be automatically reprogrammed with the new sensor setting(s) (e.g., the controller 150 (FIG. 1B), the care engine 160 (FIG. 1B), etc., can be re-programmed) through a programmer (e.g., the clinician programmer 102 (FIG. 1A) as calculated or determined by the programmer or implementing new sensor setting(s) provided by a separate resource (e.g., a dedicated patient management platform associated with the patient).

[0092] In other examples, methods of the present disclosure can facilitate automated sensing improvement during a polysomnography (PSG) study, home sleep study test (HST), or similar study. With these and related embodiments, the patient’s respiratory waveform during the study is extracted along with the study data. This information, along with other sensor signals or data available during the study (e.g., electrocardiogram (ECG), electromyogram (EMG), peripheral blood oxygen saturation (SpO2), nasal pressure transducer (PTAF), etc.) can be employed to determine, for example, stimulation timing effect on one of these signals (or data extracted from that signal such as AHI, hypoxic burden, sleep stage, etc.) This determination or assessment can be made, for example, by calculating the extracted data point or reviewing signals over a determined period of sleep (e.g., 5-120 minutes of sleep). Changes in a sensing setting are then automatically or manually implemented, and the signals or extracted data are then re-assessed to determine the effect of the setting change. These steps can be repeated as necessary.

[0093] In related examples, automated sensing improvement during a PSG study, HST study, or similar study can be provided by matching stimulation timings to inspiration during the study, likely with some delay to calculate inspiration timings and either time align the extracted respiratory waveform and study signals or to calculating stimulation timings from an extracted chin artifact obtained during the study). Machine logic, parametric sweeps, a programmed flow chart, etc., is then employed to determine what sensor setting(s) should be changed. After implementing the determined change(s) (either automatically or manually), an assessment is made to determine the effect of the setting change(s), for example by allowing the new sense settings to run over a determined period of sleep (e.g., 5-120 minutes of sleep). These steps can be repeated as necessary.

[0094] In other examples, methods of the present disclosure provide for automated optimizing setting(s) of one or more sensors utilized with an IMD, for example in the delivery of stimulation to a patient to treat sleep disordered breathing, without referencing external signals. For example, non-real-time sensor setting adjustment algorithms of the present disclosure can make reference to previously-obtained and recorded sensor signals associated with operation of the IMD (e.g., auditory, accelerometer, etc.), and need not necessarily rely upon or reference a real-time patient respiratory waveform. With these and related embodiments, a high power machine learning or digital signal processing (DSP) respiration sensing algorithm can periodically operate to rerun collected sensor data and determine sensor setting improvements. In some examples, automated inspiratory phase overlap fraction (IPOF) improvements or optimization can be determined, for example via machine learning, parametric sweeps, or the like. In this regard, sensor settings can be optimized using one or more metrics, such as mean or median, improving the lowest percent of breaths or respiratory cycles (e.g., reduce amount of breaths 10% or less), reducing amount of breaths with less than 50-75% IPOF to minimize inversion, maximizing the amount of time stimulation occurs at start of a breath, a weighted combination of any or all of the above metrics, etc. In some examples, the algorithm can be formatted to run acausally to remove filtering distortion and improve understanding of the algorithm. In some examples, parametricsweeps are run on stored data to optimize IPOF as described above.

[0095] In other examples, non-real-time sensor setting adjustments are determined, and optionally automatically implemented, with reference to the results of other algorithms or programming associated with operation of the IMD (e.g., programming provided with the clinician programmer 102 (FIG. 1A), programming provided with the IMD’s on-board controller 150 (FIG. 1B), etc.). In the context of an IMD operating to treat sleep disordered breathing, algorithms or programming associated operation of the IMD can be formatted to determine or predict various parameters of the patient, such as apnea-hypopnea index (AHI), hypoxic burden, sleep stage, etc. These and / or other determined parameters can be utilized as data points by some methods or algorithms of the present disclosure to optimize sensor settings. For example, sensor setting changes can be algorithmically determined based on the data points provided by the other parameter-determining algorithms. After implementing the determined change(s) (either automatically or manually), an assessment is made to determine the effect of the setting change(s), for example by allowing the new sense settings to run over a determined period of sleep (e.g., 5-120 minutes of sleep). These steps can be repeated as necessary.

[0096] Any of the automated sensor setting evaluation and adjustment methods or algorithms of the present disclosure can be performed or implemented at various times following implant of the IMD. In some examples, one or more of the methods or algorithms of the present disclosure can be performed or implemented shortly after initial activation, and subsequently at various intervals (e.g., every 1 - 12 months) as “maintenance”. In this regard, the methods or algorithms of the present disclosure can be performed or implemented on consecutive nights if, for example, a sensor setting adjustment seems less than optimal or incomplete.

[0097] FIG. 12A is a block diagram schematically representing an example control portion 1000. In some examples, control portion 1000 provides one example implementation of a control portion forming a part of, implementing, and / or generally managing example methods (including sensor setting adjustments, patient care paths / workflows, etc.), data models (e.g. training, operation), patient information, implantable medical devices (IMDs), sensing (e.g. portions, element(s)), stimulation (e.g. portion, elements), power / control elements (e.g. pulse generators), communication elements / pathways, devices, user interfaces, instructions, information, engines, elements, functions, and / or actions, etc., as described throughout examples of the present disclosure.

[0098] In some examples, control portion 1000 includes a controller 1002 and a memory 1010. In general terms, controller 1002 of control portion 1000 comprises at least one processor 1004 and associated memories. The controller 1002 is electrically couplable to, and in communication with, memory 1010 to generate control signals to direct operation of at least some of the example methods (including sensor setting adjustments, patient care paths / workflows, etc.), data models (e.g. training, operation), patient information, implantable medical devices (IMDs), sensing (e g. portions, element(s)), stimulation (e.g. portion, elements), power / control elements (e.g., pulse generator), communication elements / pathways, devices, user interfaces, instructions, information, engines, elements, functions, and / or actions, etc., as described throughout examples of the present disclosure. In some examples, these generated control signals include, but are not limited to, employing instructions 1011 and / or information 1012 stored in memory 1010 to implement the example methods and / or devices according to the various examples of the present disclosure which generally relate to SDB patient care. In some instances, the controller 1002 or control portion 1000 may sometimes be referred to as being programmed to perform the above-identified actions, functions, etc. such that the controller 1002, control portion 1000 and any associated processors may sometimes be referred to as being a special purpose computer, control portion, controller, or processor. In some examples, at least some of the stored instructions 1011 and / or information 1012 may form at least part of, and / or may be referred to as, an engine.

[0099] In response to or based upon commands received via a user interface (e.g., user interface 1040 in FIG. 12C) and / or via machine readable instructions, the controller 1002 generates control signals as described above in accordance with at least some of the examples of the present disclosure. In some examples, the controller 1002 is embodied in a general purpose computing device while in some examples, the controller 1002 is incorporated into or associated with at least some of the example methods (including patient sensor setting adjustments, care paths / workflows, etc.), data models (e.g. training, operation), patient information, implantable medical devices (IMDs), sensing (e.g. portions, element(s)), stimulation (e.g. portion, elements), power / control elements (e.g., pulse generator), communication elements / pathways, devices, user interfaces, instructions, information, engines, elements, functions, and / or actions, etc., as described throughout examples of the present disclosure.

[0100] For purposes of this application, in reference to the controller 1002, the term “processor” shall mean a presently developed or future developed processor (or processing resources) that executes machine readable instructions contained in a memory. In some examples, execution of the machine readable instructions, such as those provided via the memory 1010 of the control portion 1000 cause the processor to perform the various I MD operations and / or related operations, as generally described in (or consistent with) at least some of the various 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 nonvolatile tangible medium), as represented by the memory 1010. In some examples, the machine readable instructions may comprise a sequence of instructions, a processor-executable machine learning model, or the like. In some examples, the memory 1010 comprises a computer readable tangible medium providing non-volatile storage of the machine readable instructions executable by a process of the controller 1002. In some examples, the computer readable tangible medium may sometimes be referred to as, and / or comprise at least a portion of, a computer program product. 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 controller 1002 may be embodied as part of at least one application-specific integrated circuit (ASIC), at least one field-programmable gate array (FPGA), and / or the like. In at least some examples, the controller 1002 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 1002.

[0101] In some examples, the control portion 1000 may be entirely implemented within or by a stand-alone device.

[0102] In some examples, the control portion 4500 may be partially implemented in or via one of the example methods (including sensor setting adjustments, patient care paths / workflows), data models (e.g. training, operation), patient information, implantable medical devices (IMDs), sensing (e.g. portions, element(s)), stimulation (e.g. portion, elements), power / control elements (e.g., pulse generator), communication elements / pathways, devices, user interfaces, instructions, information, engines, elements, functions, and / or actions, etc. and partially implemented in a computing resource (e.g., at least one external resource) separate from, and independent of, the treatment devices (or portions thereof) but in communication with the treatment devices (or portions thereof). For instance, in some examples the control portion 1000 may be implemented via a server accessible via the cloud and / or other network pathways. In some examples, the control portion 1000 may be distributed or apportioned among multiple devices or resources such as among a server, a treatment device (or portion thereof), and / or a user interface.

[0103] In some examples, the control portion 1000 includes, and / or is in communication with, a user interface 1040 as shown in FIG. 12C.

[0104] FIG. 12B is a diagram schematically illustrating at least some example arrangements of a control portion 1020 by which the control portion 1000 (FIG. 12A) can be implemented, according to one example of the present disclosure. In some examples, the control portion 1020 is entirely implemented within or by an IMD 1025, which has at least some of substantially the same features and attributes as an IMD (e.g., 104, 150, 180) as previously described throughout the present disclosure. In some examples, the control portion 1020 is entirely implemented within or by a remote control 1030 (e.g., a programmer) external to the patient’s body, such as a patient control 1032 and / or a physician control 1034. In some examples, the control portion 1020 is partially implemented in the IMD 1025 and partially implemented in the remote control 1030 (at least one of the patient control 1032 and the physician control 1034). In some examples, the control portion 1020 in FIG. 12B is at least partially implemented via a clinician portal (e.g., 1162 in FIG. 13), which may or may not be in complementary relation with elements 1025 and 1030.

[0105] FIG. 12C is a block diagram schematically representing a user interface 1040, according to one example of the present disclosure. In some examples, the user interface 1040 forms part of and / or is accessible via a device external to the patient and by which the therapy system may be at least partially controlled and / or monitored. The external device which hosts the user interface 1040 may be a patient remote (e.g., 1032 in FIG. 12B), a physician remote (e.g., 1034 in FIG. 12B) and / or a clinician portal (e.g., 1162 in FIG. 13). In some examples, the user interface 1040 comprises a user interface or other display that provides for the simultaneous display, activation, and / or operation of at least some of the example methods (including sensor setting adjustments, patient care paths / workflows), data models (e.g. training, operation), patient information, implantable medical devices (IMDs), sensing (e.g. portions, element(s)), stimulation (e.g. portion, elements), power / control elements (e.g., pulse generator), communication elements / pathways, devices, user interfaces, instructions, information, engines, elements, functions, and / or actions, etc. In some examples, at least some portions or aspects of the user interface 1040 are provided via a graphical user interface (GUI), and may comprise an input 1042 and a display 1044.

[0106] FIG. 13 is a diagram 1100 which schematically represents some example implementations by which a medical device 1110 may communicate wirelessly with devices outside the patient. In some examples, the medical device 1110 may comprise at least some implantable components and / or at least some external components.

[0107] As shown in FIG. 13, in some examples, the medical device 1110 may communicate with at least one of patient app 1130 on a mobile device 1120, a patient remote control 1140, a clinician programmer 1150, and a patient management tool 1160. The patient management tool 1160 may be implemented via a cloud-based portal 1162, the patient app 1130, and / or the patient remote control 1140, each of which may comprise a user interface (e.g., having a display, input) such as the user interface 1040 in FIG. 12C.

[0108] Among other types of data, these communication arrangements enable the medical device 1110 to communicate, display, adjust, manage, etc. any of the example methods (e.g., sensor setting adjustments, SDB patient care paths / workflows, decisions, actions, etc.), data models (e.g., training, operation, etc.), commands, etc. in association with any of the various examples of the present disclosure. 41

[0109] 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.

Claims

1. A method for adjusting programming of a closed loop mode operated by a medical device to deliver stimulation to a patient based upon sensed patient respiration-related information, the method comprising:operating the medical device to deliver stimulation cycles to the patient pursuant to the close loop mode; andchanging at least one sensing-related setting of the closed loop mode when a delivered stimulation cycle is determined to not stop when patient exhalation starts.

2. The method of claim 1, wherein the at least one sensing-related setting is selected from the group consisting of a sensitivity setting and a threshold setting.

3. The method of claim 1, further comprising:changing a sensor signal invert status of the closed loop mode when a delivered stimulation cycle is determined to start when patient exhalation starts.

4. The method of claim 3, further comprising:changing a stimulation-related setting of the closed loop mode when a delivered stimulation cycle is determined to stop before patient inhalation ends.

5. The method of claim 4, wherein the stimulation-related setting is a maximum stimulation time period.

6. The method of claim 4, further comprising:changing a stimulation-related setting of the closed loop mode when a delivered stimulation cycle is determined to not stop when patient exhalation starts.

7. The method of claim 6, wherein the stimulation-related setting is a maximum stimulation time period.

8. The method of claim 1, wherein the medical device is arranged and configured to treat sleep disordered breathing.

9. The method of claim 8, wherein the medical device includes a first stimulation element arranged to apply stimulation to a first target site of the patient, and further wherein the delivered stimulation cycle is applied to the first target site.

10. The method of claim 9, wherein the medical device includes a second stimulation element arranged to apply stimulation to a second target site of the patient apart from the first target site, the method further comprising delivering a stimulation cycle to the second target site and changing a stimulation-related setting of the closed loop mode when the stimulation cycle delivered to the second target site is determined to have a designated relationship with a physiological characteristic of the patient.

11. The method of claim 1, wherein the step of changing at least one sensing-related setting of the closed loop mode is performed automatically.

12. The method of claim 1, wherein the step of changing is based upon a respiratory waveform of the patient.13, The method of claim 1, wherein the step of changing is based upon a signal generated by at least one sensor associated with the patient.

14. The method of claim 13, wherein the at least one sensor includes an electromyography sensor.

15. The method of claim 14, wherein the signal generated by the electromyography sensor is indicative of the stimulation cycle being applied to patient.

16. The method of claim 13, wherein the at least one sensor includes a sensor positioned external the patient.

17. The method of claim 1, wherein the medical device includes a microstimulator.

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