Improved evaluation of medical device related data

Abstract

A method including executing an automatic evaluation of data residing on a computing system pertaining to a specific medical device. The method comprising obtaining access to a computing system, and via the computing system, obtaining access to data based on medical device settings and / or phenomena recorded in association with the medical device and executing an automated evaluation of the accessed data and gauging efficacy of the medical device based on results of the automated evaluation.

Description

Atty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCI IMPROVED EVALUATION OF MEDICAL DEVICE RELATED DATA CROSS-REFERENCE TO RELATED APPLICATIONS[oooi] This application claims priority to U.S. Provisional Application No. 63 / 763,471, entitled IMPROVED EVALUATION OF MEDICAL DEVICE RELATED DATA, filed on February 26, 2025, naming Ben Zalm FERNEE as an inventor, the entire contents of that application being incorporated herein by reference in its entirety.BACKGROUND

[0002] Medical devices have provided a wide range of therapeutic benefits to recipients over recent decades. Medical devices can include internal or implantable components / devices, external or wearable components / devices, or combinations thereof (e.g., a device having an external component communicating with an implantable component). Medical devices, such as traditional hearing aids, partially or fully-implantable hearing prostheses (e.g., bone conduction devices, mechanical stimulators, cochlear implants, etc.), pacemakers, defibrillators, functional electrical stimulation devices, and other medical devices, have been successful in performing lifesaving and / or lifestyle enhancement functions and / or recipient monitoring for a number of years.

[0003] The types of medical devices and the ranges of functions performed thereby have increased over the years. For example, many medical devices, sometimes referred to as “implantable medical devices,” now often include one or more instruments, apparatus, sensors, processors, controllers or other functional mechanical or electrical components that are permanently or temporarily implanted in a recipient. These functional devices are typically used to diagnose, prevent, monitor, treat, or manage a disease / injury or symptom thereof, or to investigate, replace or modify the anatomy or a physiological process. Many of these functional devices utilize power and / or data received from external devices that are part of, or operate in conjunction with, implantable components.SUMMARY

[0004] In an exemplary embodiment, there is a method comprising obtaining access to a computing system, and via the computing system, obtaining access to data based on data based on medical device settings and / or phenomena recorded in association with the medical device and executing an automated evaluation of the accessed data and gauging gauging efficacy of the medical device based on results of the automated evaluation.Atty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCI BRIEF DESCRIPTION OF THE DRAWINGS

[0005] Embodiments are described below with reference to the attached drawings, in which:

[0006] FIG. l is a perspective view of an exemplary hearing prosthesis;

[0007] FIG. 2 presents a functional block diagram of an exemplary cochlear implant;

[0008] FIG. 3 presents an exemplary system of communication between devices;

[0009] FIG. 4 presents an exemplary retinal prosthesis;

[0010] FIGs. 5, 13 and 14 show exemplary systems;

[0011] FIGs. 6-7, 12, 19, and 22 show flowcharts for exemplary methods; and

[0012] FIGs. 8-11, 15-18, 20-21, 23-28, show exemplary data presentations.DETAILED DESCRIPTION

[0013] Merely for ease of description, the techniques presented herein are described herein with reference by way of background to an illustrative medical device, namely a cochlear implant. However, the techniques presented herein can be used with other medical devices that, while providing a wide range of therapeutic benefits to recipients, patients, or other users, may benefit from setting changes based on the location of the medical device. For example, the techniques presented herein may be used to determine the viability of various types of prostheses, such as, for example, a vestibular implant and / or a retinal implant, with respect to a particular human being. The techniques presented herein are described with reference by way of background to another illustrative medical device, namely a retinal implant. The techniques presented herein are also applicable to the technology of vestibular devices (e.g., vestibular implants), visual devices (i.e., bionic eyes), sensors, pacemakers, drug delivery systems, defibrillators, functional electrical stimulation devices, catheters, seizure devices (e.g., devices for monitoring and / or treating epileptic events), sleep apnea devices, electroporation, etc.

[0014] Also, embodiments are directed to other types of hearing prostheses, such as middle ear implants, bone conduction devices (active transcutaneous, passive transcutaneous, percutaneous), and conventional hearing aids. Thus, embodiments are directed to devices that include implantable portions and embodiments that do not include implantable portions.Atty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCI

[0015] Any reference to one of the above-noted sensory prostheses corresponds to an alternate disclosure using one of the other above-noted sensory prostheses unless otherwise noted, providing that the art enables such.

[0016] FIG. 1 shows a cochlear implant 10, that includes an implantable portion 100, implanted in a recipient, to which some embodiments detailed herein and / or variations thereof are applicable. Note that there are aspects of a cochlear implant that are utilized with respect to a vestibular implant, and thus there is utility in describing features of the cochlear implant for purposes of understanding a vestibular implant. The cochlear implant 10 can include external components. The disclosure herein can be applicable to other types of hearing prostheses, such as, by way of example only and not by way of limitation, bone conduction devices (percutaneous, active transcutaneous and / or passive transcutaneous), direct acoustic cochlear stimulators, middle ear implants, and conventional hearing aids, etc., and / or so-called multi-mode devices. In an exemplary embodiment, these multi-mode devices apply both electrical stimulation and acoustic stimulation to the recipient. In an exemplary embodiment, these multi-mode devices evoke a hearing percept via electrical hearing and bone conduction hearing.

[0017] At least some embodiments detailed herein and / or variations thereof are directed towards a body -worn sensory supplement medical device (e.g., the hearing prosthesis of FIG.1, which supplements the hearing sense, even in instances when there are no natural hearing capabilities, for example, due to degeneration of previous natural hearing capability or to the lack of any natural hearing capability, for example, from birth). At least some exemplary embodiments of some sensory supplement medical devices are directed towards devices such as conventional hearing aids, which supplement the hearing sense in instances where some natural hearing capabilities have been retained, and visual prostheses (both those that are applicable to recipients having some natural vision capabilities and to recipients having no natural vision capabilities). Accordingly, the teachings detailed herein are applicable to any type of sensory supplement medical device to which the teachings detailed herein are enabled for use therein in a utilitarian manner. In this regard, the phrase sensory supplement medical device refers to any device that functions to provide sensation to a recipient irrespective of whether the applicable natural sense is only partially impaired or completely impaired, or indeed never existed.

[0018] The recipient has an outer ear 101, a middle ear 105, and an inner ear 107. In a fully functional ear, outer ear 101 comprises an auricle 110 and an ear canal 102. An acousticAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIpressure or sound wave 103 is collected by auricle 110 and channeled into and through ear canal 102. Disposed across the distal end of ear channel 102 is a tympanic membrane 104 which vibrates in response to sound wave 103. This vibration is coupled to oval window or fenestra ovalis 112 through three bones of middle ear 105, collectively referred to as the ossicles 106 and comprising the malleus 108, the incus 109, and the stapes 111. Bones 108, 109, and 111 of middle ear 105 serve to filter and amplify sound wave 103, causing oval window 112 to articulate, or vibrate in response to vibration of tympanic membrane 104. This vibration sets up waves of fluid motion of the perilymph within cochlea 140. Such fluid motion, in turn, activates tiny hair cells (not shown) inside of cochlea 140, resulting in nerve impulses being generated and transferred through the auditory nerve 114 to the brain where they are perceived as sound.

[0019] As shown, cochlear implant 10 comprises one or more components which are temporarily or permanently implanted in the recipient. Cochlear implant 10 is shown in FIG.1 with an external device 142, which is configured to provide power to the cochlear implant, where the implanted cochlear implant includes a battery that is recharged by the power provided from the external device 142.

[0020] In the illustrative arrangement of FIG. 1, external device 142 can comprise a power source (not shown) disposed in a Behind-The-Ear (BTE) unit 126. External device 142 also includes components of a transcutaneous energy transfer link, referred to as an external energy transfer assembly. The transcutaneous energy transfer link is used to transfer power and / or data to the implantable portion 100. Various types of energy transfer, such as infrared (IR), electromagnetic, capacitive and inductive transfer, may be used to transfer the power and / or data from external device 142 to the implanted portion. The external energy transfer assembly comprises an external coil 130 that forms part of an inductive radio frequency (RF) communication link. External coil 130 is a wire antenna coil comprised of multiple turns of electrically insulated single-strand metal wire. External device 142 also includes a magnet positioned within the turns of wire of external coil 130. Other external devices may be used with other embodiments.

[0021] The implantable portion 100 comprises an internal energy transfer assembly adjacent auricle 110 of the recipient. Internal energy transfer assembly 132 is a component of the transcutaneous energy transfer link and receives power and / or data from external device 142. The energy transfer link comprises an inductive RF link, and internal energy transferAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIassembly 132 comprises a primary internal coil 136. Internal coil 136 can have one or more of the features of the external coil.

[0022] The implantable portion 100 comprises main implantable component 120 and an elongate electrode assembly 118. Internal energy transfer assembly 132 and main implantable component 120 can be hermetically sealed within a biocompatible housing. Main implantable component 120 can include an implantable microphone assembly (not shown) and a sound processing unit (not shown) to convert the sound signals received by the implantable microphone in internal energy transfer assembly 132 to data signals. The implantable microphone assembly can be located in a separate implantable component (e.g., that has its own housing assembly, etc.) that is in signal communication with the main implantable component 120 (e.g., via leads or the like between the separate implantable component and the main implantable component 120). Any microphone arrangement can be used if enabled.

[0023] Main implantable component 120 further includes a stimulator unit (not shown) which generates electrical stimulation signals based on the data signals. The electrical stimulation signals are delivered to the recipient via elongate electrode assembly 118.

[0024] Elongate electrode assembly 118 has a proximal end connected to main implantable component 120, and a distal end implanted in cochlea 140. Electrode assembly 118 extends from main implantable component 120 to cochlea 140 through mastoid bone 119. In some embodiments electrode assembly 118 may be implanted at least in basal region 116, and sometimes further. Electrode assembly 118 may extend towards apical end of cochlea 140, referred to as cochlea apex 134. In certain circumstances, electrode assembly 118 may be inserted into cochlea 140 via a cochleostomy 122. In other circumstances, a cochleostomy may be formed through round window 121, oval window 112, the promontory 123 or through an apical turn 147 of cochlea 140.

[0025] Electrode assembly 118 comprises a longitudinally aligned and distally extending array 146 of electrodes 148, disposed along a length thereof. As noted, a stimulator unit generates stimulation signals which are applied by electrodes 148 to cochlea 140, thereby stimulating auditory nerve 114.

[0026] Accordingly, one variety of implanted devices depends on an external component to provide certain functionality and / or power. For example, the recipient of the implanted device can wear an external component that provides power and / or data (e.g., a signalAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIrepresentative of sound) to the implanted portion that allows the implanted device to function. In particular, the implanted device can lack a battery (but can have such in other embodiments) and can instead be totally dependent on an external power source providing continuous power for the implanted device to function. Although the external power source can continuously provide power, characteristics of the provided power can fluctuate. The implanted device can lack its own sound input device (e.g., a microphone). It is sometimes utilitarian to remove the external component (e.g., when sleeping). Doing so can result in loss of function of the implanted portion of the prosthesis, which can make it impossible for recipient to hear ambient sound.

[0027] FIG. 2 is a functional block diagram of a cochlear implant 200 to which the teaching herein can be applicable. The cochlear implant 200 includes an implantable component 201 (e.g., implantable component 100 of FIG. 1) configured to be implanted beneath a recipient’s skin or other tissue 249, and an external device 240 (e.g., the external device 142 of FIG. 1).

[0028] Implantable component 201 can include a transceiver unit 208, electronics module 213, which module can be a stimulator assembly of a cochlear implant, and an electrode assembly 254 (which can include an array of electrode contacts disposed on lead 118 of FIG.1). The electronics module can include a stimulator unit 214.

[0029] In some embodiments, the implantable component 201 receives operational power from the external device 240 and the implantable component 201 does not include an internal power source (e.g., a battery) / internal power storage device. In other embodiments, such as in the case of a totally implantable hearing prosthesis (e.g., one that has an implanted microphone and implanted battery), operational power is received from an implanted battery or other power storage device, which is recharged from time to time as desired by an external charger (which can be the external component).

[0030] In the example system 200 depicted in FIG. 2, the external device 240 includes a sound input unit 242, a sound processor 244, a transceiver unit 246, a coil 247, and a power source 248.

[0031] The processor 244 is a processor configured to control one or more aspects of the system 200, including converting sound signals received from sound input unit 242 into data signals and causing the transceiver unit 246 to transmit power and / or data signals.Atty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCI

[0032] It is noted that the teachings detailed herein can be implemented with a non-totally implantable prosthesis or a totally implantable prosthesis (analogous to such for cochlear implants).

[0033] FIG. 3 depicts an exemplary system 2110 according to an exemplary arrangement, including device 100, which can be a hearing prosthesis, or a tinnitus treatment device such as that disclosed below, or any device configured to provide stimulation to a recipient that can treat tinnitus in accordance with the teachings herein. In an exemplary arrangement, device 100 corresponds to the prosthesis of FIG. 1, or to any of the systems detailed below, etc. Also seen in the system is a portable body carried device (e.g. a portable handheld device as seen in FIG. 2 A, a watch, a pocket device, etc.) 2140 in the form of a mobile computer (e.g., a smart phone) having a display 2142. The system includes a wireless link 2130 between the portable handheld device 2140 and the hearing prosthesis 100 (often, 100 is referred to as a hearing prosthesis, and such reference corresponds to a disclosure of an alternate arrangement where such is one of the other devices herein). In an arrangement, the prosthesis 100 is a totally implantable prosthesis, such as where there is a processor and / or an internal power storage device (e.g., a battery), and where, for example, the implant can operate for at least 1, 2, 3, 4, 5, 6, 7, 8, 9 or 10 hours or more without signal communication from an external device, and in other arrangements, it includes an implanted portion implanted in recipient 99 (as represented functionally by the dashed lines of box 100 in FIG.3).

[0034] In an exemplary arrangement, the system 2110 is configured such that the hearing prosthesis 100 or other device and the portable handheld device 2140 have a symbiotic relationship.

[0035] As noted above, in an exemplary arrangement, the portable handheld device 2140 comprises a mobile computer and a display 2142. In an exemplary arrangement, the display 2142 is a touchscreen display. In an exemplary arrangement, the portable handheld device 2140 also has the functionality of a portable cellular telephone and can be a smartphone.

[0036] FIG. 4 presents an exemplary embodiment of a neural prosthesis in general, and a retinal prosthesis and an environment of use thereof, in particular, the components of which can be used in whole or in part, in some of the teachings herein. In some embodiments of a retinal prosthesis, a retinal prosthesis sensor-stimulator 10801 is positioned proximate the retina 11001. In an exemplary embodiment, photons entering the eye are absorbed by aAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCImicroelectronic array of the sensor-stimulator 10801 that is hybridized to a glass piece 11201 containing, for example, an embedded array of microwires. The glass can have a curved surface that conforms to the inner radius of the retina. The sensor-stimulator 108 can include a microelectronic imaging device that can be made of thin silicon containing integrated circuitry that convert the incident photons to an electronic charge.

[0037] An image processor 10201 is in signal communication with the sensor-stimulator 10801 via cable 10401 which extends through surgical incision 00601 through the eye wall (although in other embodiments, the image processor 10201 is in wireless communication with the sensor-stimulator 10801). The image processor 10201 processes the input into the sensor-stimulator 10801 and provides control signals back to the sensor-stimulator 10801 so the device can provide processed output to the optic nerve. That said, in an alternate embodiment, the processing is executed by a component proximate with or integrated with the sensor-stimulator 10801. The electric charge resulting from the conversion of the incident photons is converted to a proportional amount of electronic current which is input to a nearby retinal cell layer. The cells fire and a signal is sent to the optic nerve, thus inducing a sight perception.

[0038] The retinal prosthesis can include an external device disposed in a Behind-The-Ear (BTE) unit or in a pair of eyeglasses, or any other type of component that can have utilitarian value. The retinal prosthesis can include an external light / image capture device (e.g., located in / on a BTE device or a pair of glasses, etc.), while, as noted above, in some embodiments, the sensor-stimulator 10801 captures light / images, which sensor-stimulator is implanted in the recipient.

[0039] In the interests of compact disclosure, any disclosure herein of a microphone or sound capture device corresponds to an analogous disclosure of a light / image capture device, such as a charge-coupled device. Corollary to this is that any disclosure herein of a stimulator unit which generates electrical stimulation signals or otherwise imparts energy to tissue to evoke a hearing percept corresponds to an analogous disclosure of a stimulator device for a retinal prosthesis. Any disclosure herein of a sound processor or processing of captured sounds or the like corresponds to an analogous disclosure of a light processor / image processor that has analogous functionality for a retinal prosthesis, and the processing of captured images in an analogous manner. Indeed, any disclosure herein of a device for a hearing prosthesis corresponds to a disclosure of a device for a retinal prosthesis having analogous functionality for a retinal prosthesis. Any disclosure herein of fitting a hearing prosthesis corresponds to aAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIdisclosure of fitting a retinal prosthesis using analogous actions. Any disclosure herein of a method of using or operating or otherwise working with a hearing prosthesis herein corresponds to a disclosure of using or operating or otherwise working with a retinal prosthesis in an analogous manner.

[0040] FIG. 5 is a functional schematic of an embodiment, where there is an input and / or output system 555 that is in signal communication via link 575 with a processing system 565, which can process input received from system 555, and then provide the processed results back to system 565 for output to the user. The system 565 can execute any one or more of the checks herein.

[0041] Embodiments include evaluating features related to a medical device, including features of a map or of control data / control settings for the device and / or fitting related data (e.g., settings or phenomena related to fitting), or a personalized map / profile that is generated in a fitting session, including the finalized settings. In some embodiments, the map is a set of control parameters that are uploaded to the device. In other embodiments, the map constitutes individual settings that are stored in the device that are adjusted one by one.

[0042] Some embodiments can be characterized as a map check tool or otherwise a process of checking a map of the medical device. Some can be characterized as a tool for checking clinician-configurable deice settings and / or adjustable device settings. Embodiments enable a healthcare professional, etc., to access and / or evaluate information about a patient in general, and features related to the medical device. Embodiments can be implemented using a webbased system and / or a closed-circuit system that supports access to information and / or evaluation software associated with a recipient of a medical device’s map, or other related data. Embodiments can extract information from a specific file or otherwise a sub-base of a database and can check the information against one or more rules / predetermined features.

[0043] FIG. 6 presents an exemplary flowchart of an exemplary method, method 600, that includes method action 610, which includes obtaining access to a computing system. This can be done through the use of a laptop computer upon which the database and the software associated with the teachings herein rely. In an embodiment, this can entail turning on the computer, and accessing the pertinent applications on the computer, such as by way of example, by accessing executable files on the computer, etc. This can also be accomplished by way of example, through the use of a computer having access to the Internet or the like, where a web browser is utilized to access a remote server where the database and / or theAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIsoftware resides, or what server can access such. But note that a database is not necessarily involved in some embodiments.

[0044] Method 600 further includes method action 620, which includes, via the computing system, obtaining access to data based on data based on medical device settings and / or phenomena recorded in association with the medical device. By data based on data based on a given feature, it is meant raw data, such as, for example, the current level for a threshold setting at 2000 Hz, which would be data based on a given feature, as well as a proxy or a summation of such, which can be for example, an established classification of such, which can be, for example, “stimulation regime 87,” which can correspond to the just noted current level at that frequency. Data based on data based on a given feature thus includes the underlying data as well as the proxy data. As long as the data is based somehow on the underlying feature, the data corresponds to such. Method 600 further includes method action 630, which includes executing an automated evaluation of the accessed data. Some exemplary features associated with the execution of the automated evaluation of the access data will be described below. But briefly, in an embodiment, the automatic evaluation access data entails an evaluation of whether certain parameters of control settings of the medical device comply with various requirements or goals of a management regime of the medical device. In an embodiment, power scenarios associated with the specific medical device are the subject of the automatic evaluation.

[0045] Figure 7 shows an exemplary method, method 700, that includes method action 710 and method action 720, which includes the action of gauging efficacy of the medical device based on results of the automated evaluation. This can be executed automatically in an exemplary embodiment.

[0046] In an embodiment, the action executing the automated evaluation of the accessed data includes an automated check of the access data based on predetermined rules. In an embodiment, there are at least and / or equal to and / or no more than 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 40, 45, 50, 55 or 60 or more or any value or range of values therebetween in one increment rules (e.g., 38, 52, 31 to 44, etc.). In an exemplary embodiment, the action of automatically evaluating the accessed data automatically executes an evaluation that includes an automated check against any one or more of the aforementioned number of predetermined rules. In an embodiment, any one or more of the aforementioned number of rules had been predeterminedAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIdays or weeks or months or even years prior to the execution of one or more of the method actions detailed herein.

[0047] In an embodiment, the automated evaluation of the accessed data is a check of the medical device map. Note that this does not mean that the check is exclusively such. It just means that a check of the medical device map is executed when the method action is executed.

[0048] As noted above, there are various checks of various features associated with the medical device that are executed in the automated evaluation. By way of example, there is the low medical device power check. In an embodiment, this is a low implant power check. This check can be based on a power rule that checks if parameters of the voltage of the medical device power supply are within a given range or above a threshold or below the threshold, etc. In a particular embodiment, voltage of the power supply as it changes over time is evaluated, and if the change over time has a rate that is greater than a threshold value during a specific period of time, the power supply is deemed to be adequate and otherwise the power supply / power system of the medical device or a portion thereof (the implantable portion and / or the external portion, such as may be the case for a cochlear implant or hearing prostheses implant) is sufficient to power the functionality of the medical device, or otherwise the power supply is not defective. Figure 8 shows an exemplary change of voltage in calibrated counts over time for a given medical device for tests / data collections taken on various days over the course of a five-year period. In an exemplary embodiment, the check can determine whether a voltage in calibrated counts is below or at or above a threshold, such as, for example, below 300 calibrated counts corresponding to a particular voltage level (calibrated counts can correspond to the data from the telemetry of the implant - this is not voltage per se but an indicator of such - this can be based on a linear scale relative to voltage, or a non-linear scale - in an embodiment, a rate of change of any voltage that is deemed to be something that should be flagged can be set based on the units used - for example, the slope of the values seen in FIG. 8 would change if a different Y axis unit set was used - thus, if slope is used as a trigger, the trigger will be different depending on the slope. The rule can be that any medical device power supply that experiences a voltage in calibrated counts or whatever value is desired over a specific period of time that is below and / or at a certain value, such as here, 350 CVs or below, is flagged as a feature that should be or is of concern, or at least further analysis should be undertaken. Alternatively, and / or in addition to this, the rate of change of the voltage over time can be evaluated. By way of example, there can be a ruleAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIwhere if the slope (rate of change on average) is greater than 1.5, 2, 2.5, 3, 3.5, 4, 4.5 or 5 or any value or range of values therebetween in 0.1 increments over certain period of time, such as, for example, between and inclusive of 10 to 40 ms, 15 to 60 ms, 5 to 45 ms, 15-50 ms, such medical device / dataset is flagged. In an embodiment, this can be indicative that there could be a power supply problem with the medical device. In an embodiment, the temporal periods of the data collection values are between 0 ms and 100 ms or any value or range of values therebetween in 0.1 ms increments, and the thresholds or triggers of a given rule can be a CV that goes below or equal to and / or has a reduction over the time or any utilitarian portion of the time of 20, 25, 30, 40, 50, 100, 150, 175, 200, 250, 300, 350 or 400 or any value or range of values therebetween in 1 CV increments, or a rate of change as noted above, and flagged when the automatic evaluation is executed, and this is deemed to “not pass” or otherwise is of a value that is a concern. Power supply measurements can be taken at any intervals over the period of time just noted, and there can be less than, greater than and / or equal to 1 (in which case there is no less than) to 100 or more or any value or range of values therebetween in one increment data points / power supply measurements over a given temporal period. There can be less than, greater than and / or equal to 1 (in which case there is no less than), 2, 3, 4, 5 to 100 or more or any value or range of values therebetween in one increment temporal periods / testing periods / data collection periods in the database / that are evaluated. It could be that the rate of change or the overall change from one test to another or over a series of tests are evaluated and checked against a medical device power rule. Here, the rule would attempt to identify a low medical device power scenario or otherwise an implant or medical device that has a low power scenario in the past or in the present.

[0049] The voltage testing / data collection therefore can be done transparently to the recipient. The medical device collects data during use and thus logs the data.

[0050] In an embodiment, if a check fails, the data is flagged for follow-up or otherwise closer attention in the future is to be paid to the recipient. In an embodiment, the recipient can be requested to provide feedback. It can be that the recipient reports intermittent sound and / or not being able to experience the utilitarian value of the medical device (such as not being able to hear with respect to a hearing prosthesis). In an embodiment, upon such flagging of a potential power supply issue, it can be that the power supply is interrogated with advanced telemetry tests by way of example. The point is that as a result of the execution of the automated evaluation of the access data, the action of gauging efficacy of the medical device based on the results can be executed, and, based on that gauging, it can be deemed thatAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIadditional follow-up steps should be taken. It also can be deemed that no further follow-up steps should be taken, other than routine future evaluations.

[0051] Embodiments include checking whether datasets include data related to implant power in the first instance. That can be the automated evaluation of the accessed data. It can also be that the data, if present, can be of varying quality. Thus, method action 630 can include evaluating the quality of power data. It can be that insufficient data is present to make a determination regarding the implant power performance or otherwise to make a confident determination of such. All of this can be executed automatically, and presented to the user of the computer system or the entity executing the method.

[0052] As will be described in greater detail below, in an exemplary embodiment, data can be displayed on a computer screen for example for further evaluation by the healthcare professional or otherwise the entity executing method 600 or method 700. Figure 9 shows an exemplary graph that can be presented via a GUI of the computer system relating to power status of the medical device (here, an implantable portion of a cochlear implant). The results of the graph would be the execution of the automated evaluation. The evaluation can also include the rate of change. It also can be that it is the entity that executes a method that evaluates the rate of change. This can entail gauging the efficacy of the medical device based on the result of the automated evaluation. A skilled or otherwise trained professional or the like can visually inspect the chart shown on figure 9 and determine whether the power supply should be investigated. Here, if the units on the Y axis are scaled (using voltage vs. calibrated units), the visual inspection can be relied upon because it is the “shape” of the curve that be visually evaluated, as opposed to the specific slope. Indeed, the cause can be normalized so that the “slope” means the same thing regardless of the units used - it is the image that is evaluated in some embodiments. Artificial intelligence can be used to evaluate the image to determine if the settings should be flagged.

[0053] It is noted that the exemplary datasets just described and otherwise the exemplary “triggers” for flagging a rule violation / that a dataset contains data that violates rule or meets a rule for that matter (the rule can be to flag power related issues if the dataset indicates values that are below a certain threshold for example) are one of many exemplary datasets that can be utilized to implement the teachings herein. Any physical phenomenon that can be tested or recorded that can be utilized in an evaluation process to determine whether or not a medical device should be subject to further evaluation or otherwise further monitoring beyond that which would normally be the case can be utilized, providing that the art enablesAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIsuch unless otherwise noted. Latent variables can be utilized by way of example only and not by way of limitation, if such can be evaluated to have utilitarian value in accordance with the teachings herein.

[0054] Another exemplary check that can be executed is a medical device identification functionality, or more accurately, whether such exists and / or whether or not such is activated for the given medical device under evaluation. Medical devices, including implantable medical devices, can include a so-called medical device ID / implant ID functionality. This can be a functionality used in a protocol where a device communicating with the medical device or an intended “audience” such as the implant, goes through a verification process (or the portion of the medical device goes through the verification process, or both) to ensure that the recipient of the communication is the correct medical device or the correct portion of the medical device, or vice versa for that matter. With respect to a hearing prostheses that includes an implantable portion, for example, this can have utilitarian value with respect to ensuring that an external device that can be located on either side of the head is utilized on the correct side of the head where, for example, the recipient has two implants, one on either side of the head for each ear. Because it is likely that the external components will have different maps saved therein, the implant ID functionality can be utilized to reduce the likelihood that the wrong external component will be utilized with the implant or vice versa. Accordingly, some medical devices have an automatic identification regime, such as an implant ID functionality. It can be that this is disabled. The dataset obtained can have data indicative of whether the implant ID functionality is enabled and / or disabled. In some embodiments, it is desirable that the medical device ID functionality is enabled for safety reasons. Accordingly, a check can be to determine whether ID functionality is enabled or disabled based on the data from the dataset. The rule can be that if the implant ID is disabled, this is flagged for the user. An indication can be provided on the GUI that the implant ID is disabled. That said, it can be that status of implant ID is always presented to the user as a matter of course with respect to the implementation of method 700 or method 600. It is also noted that this can be something that can be selected or otherwise further investigated by the user. That is, even though the status may not have been flagged to be presented to the user or the entity implementing the method, the user entity can still investigate the dataset and determine the status. This can be by, for example, clicking an icon or typing in a request into the GUI, where the computer system can evaluate the request and present the data to the user or entity. This is also the case with respect to the power related information and any the otherAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIportions of the dataset or otherwise information contained in the dataset unless otherwise noted.

[0055] Here again, gauging the efficacy of the medical device based on the results of the automated evaluation can be done by the user executing the method or can be done by the computer system itself in an automated manner. For example, a rule can be set that efficacy of the medical device is deemed to be below that which otherwise can be the case if the implant ID or medical device ID functionality has been disabled or vice versa.

[0056] Note also that the action of executing the automated evaluation of the accessed data can also include determining whether medical device ID status is even present within the dataset or otherwise whether the medical device even has the identification functionality in the first instance.

[0057] Another exemplary check can be an auto power level and / or manual power level functionality of the medical device. Embodiments can include medical devices that have automated features that control or otherwise manage power optimization. This can improve battery life. This can also be something that has utilitarian value with respect to ensuring or at least improving the likelihood that one or more output channels of the device, such as the channels of a cochlear implant or the single-channel of a pacemaker for example, etc., are in compliance. This can have use in ensuring that the medical device can deliver enough voltage to generate the “requested” / “required” current level. This can have the effect of maximizing or otherwise extending battery life for a given charge and / or in totality relative to that which would otherwise be the case. This can also allow for a widening range of map parameters to be utilized relative to that which would otherwise be the case. In any event, there is a functionality that can enable such in some embodiments, and if the functionality is set to manual and / or the auto power feature has been disabled, such can override the automated power optimization calculation or otherwise the power management regimes. This can result in a device that is out of compliance. This in and of itself may not necessarily be forbidden or otherwise be something that should not be done. Indeed, the ability to override indicates the opposite. However, if manual power level adjustments are made, there can be utilitarian value with respect to making new measurements for compliance or otherwise adjusting other features of the medical device so that the medical device will be in compliance or otherwise closer to compliance. This also can require the selection of a battery type that will support the new power level, such as where, for example, a power level is manually increased above and optimize power level or otherwise the power level that is setAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIvia the auto power functionality. And in this regard, it can be that even if manual power settings are being utilized, this may not affect compliance. It can be only if a given power setting that is manually set is sufficiently deviant from that which would result from the utilization of the auto power functionality. Accordingly, in an embodiment, if the auto power functionality has been disabled or otherwise a manual power setting is being used for medical device at the time that the data collection takes place or otherwise during a time precedent the time that the data collection takes place (it can be that the recipient of the medical device switches back and forth or otherwise does not utilize the auto power functionality all the time or otherwise utilizes manual power setting for a significant amount of time or an amount time that should be flagged according to the rules), this is flagged and presented to the entity executing the method. Again, this may not necessarily be flagged in that this can be a default that is presented to the entity executing the method, where the default is to simply indicate whether the auto power functionality is enabled or whether manual power control is enabled, etc. And it can be that this is always presented, but an indication can be provided if the manual power control has been or is enabled (and not provided otherwise). Auto power can be a function of the medical device that optimizes the power level at which the implant is effectively powered. This can automatically calculate an optimum power level setting during a fitting or programming session. In some embodiments, this can be overridden (and in some embodiments this is not present in the medical device). For the embodiment shown in FIG.15 A, the auto power level is set at 72%.

[0058] In some embodiments, the presence and / or absence of data relating to automatic power management and / or manual power management can also be included in the evaluation of the dataset and / or the quality. With respect to the latter, it can be that there is insufficient frequency data or temporal data to make a determination as to whether the utilization of manual power control is sufficiently impacting the clinical nature of the medical device to warrant an intervention. Here, the insufficiency of the data can warrant further follow-up, but might not be sufficient to indicate an out of compliance scenario for example or otherwise that such is likely to have occurred or be occurring. The flagging can be that not enough information is present.

[0059] The automated evaluation of the access data evaluates whether auto power has ever been disabled and / or vice versa, and / or the amount of time that such has occurred (in total and / or for one or more episodes) and / or the frequency of such, and / or the average (mean, median and / or mode - hereinafter, any reference to average ) amount of time that such hasAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIbeen disabled and / or enabled and / or vice versa, etc. Any one or more temporal thresholds and / or frequency thresholds can be utilized to trigger the flagging of this occurrence or otherwise the existence of this and the dataset. As with other checks, the action of gauging the efficacy of the medical device can be automated or can be done by the entity executing the method. What is done about such can be to interrogate if compliance was remeasured upon or subsequent to the auto power functionality being disabled and / or the manual power being enabled. In an embodiment, what is done about such can be to perform an analysis of the available data to determine whether or not the changes to the power settings resulting from the use of the manual functionality had a significant impact or otherwise met or exceeded threshold values that would warrant further evaluation or further action. Embodiments include providing an automated recommendation / direction as a result of one or more of the method actions.

[0060] Another check is a telemetry data check. In an embodiment, the dataset / the access data is evaluated to determine whether there exist telemetry data. This can be any type of telemetry or can be a specific type of telemetry, such as by way of example, neural response telemetry data. The temporal status of that data can also be evaluated, such as, for example, whether or not this is post operative or operative data, or a specific date or range of dates or time periods or some other temporal feature that is associated with the telemetry data. Thus, a check can be made of the age of the data (if it falls within acceptable timeframes). Neural telemetry response threshold data can be utilitarian for post-implantation (e.g., of a cochlear implant) evaluation, including post operative threshold data. This can be used for comparison purposes, etc. This can also be utilized as technology develops or otherwise to evaluates whether an upgrade to the medical device can be utilitarian or otherwise worth the expense thereof. This can also be utilized as a reference for purposes of evaluating the current map or one or more the control settings. In some embodiments, the correlation (or lack thereof) between a profile shape of NRT based measurement data and / or behavioral measurements can be utilized such as, for troubleshooting and / or assessing if threshold level and / or comfort levels or otherwise the profile shape thereof differ significantly to the NRT profile. Regardless of what for such is used, the action of executing an automated evaluation of the accessed data includes assessing the presence and / or absence and / or quality of telemetry data. And note that any of the checks noted herein can also be checks of the quality of the data as well. It can be that there is data that is present, but the quality can be such that further attention might be warranted or not warranted, depending on the circumstances.Atty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCI

[0061] The source of the telemetry or otherwise data can be evaluated. In some instances, the source may rule out the utilitarian value of the telemetry data for whatever reason. An automated recommendation to rule out can be provided. It can be that the evaluation ignores this or otherwise indicates that the source is insufficient or the purposes of the goal of running the method for example. That can be a rule where certain sources are deemed to be insufficient or otherwise result in an indication that the telemetry data is not present or otherwise should be used. It can be that only some data portions from only certain types of medical devices is flagged or otherwise will be evaluated (other types can use all data obtained). Here, it can be that certain medical devices provide sufficient quality telemetry data for utilitarian analysis, while other medical devices provide telemetry data that is more speculative or otherwise the quality is questionable, and sufficiently questionable that on the statistical basis, the data should not be relied upon to make decisions.

[0062] The presence and / or absence of control setting data (or certain portions thereof) in the dataset can also be evaluated. (Control setting data can be map data.) For example, a cochlear implant includes threshold and / or comfort level settings. This can be a current level or a unit of measurement applied by the device to result in an output that corresponds to a threshold of hearing for example and / or a maximum comfort level of hearing. This data can be useful for evaluating the efficacy of a medical device or otherwise evaluating phenomena related thereto. Again, the quality of such can be evaluated, such as, for example, whether levels for all or a majority of channels or a working number of channels to be useful is present in the data. It also can be an evaluation of when this data was collected. Threshold and / or comfort levels that are collected long in the past (relatively) may not be as useful as current data or otherwise more current data. There is also utilitarian value with respect to tracking or otherwise evaluating the change of these values over time, and comparing the change over time. Thus, data that is temporally too close to other data or too far away from other data can be less useful than that which would otherwise be the case. Threshold levels and / or comfort levels will change over time. If values change by a certain amount over years, that can be much less of a concern that if values changed by that amount over the course of weeks or months. Accordingly, quality checks can be made on the data in the dataset / judgements can be made automatically, and taken into account when flagging (rules can have different triggers for different temporal scenarios of the data).

[0063] Also, changes in the data or otherwise the values of the threshold and / or comfort levels over time can be evaluated as part of the check. For example, a rule can flag a scenarioAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIwhere a change in a value exceeds or meets a certain threshold within a given period of time. Changes in individual and / or average threshold and / or comfort levels from a baseline or from a comparison dataset can be evaluated and if the change meets or exceeds a predetermined value, that would be flagged. By way of example only and not by way of limitation, a baseline map and the latest map can be compared to one another, and the average changes in threshold and / or comfort levels can be determined. If the average exceeds a value, this is flagged.

[0064] In an exemplary embodiment, with respect to for example a cochlear implant where there are less than, greater than and / or equal to 5, 10, 15, 20, 21, 22, 23, 24, 25, 30, 35, 40 or 60 channels or any value or range of values therebetween in one increment, if greater than and / or equal to 2, 3, 4, 5, 10, 15, 20, 35, 55, 75, 95 or 100% value or range of values therebetween in 1% increments rounded up and / or rounded down as desired of those channels are identified (automatically by the system for example) as experiencing a change from a baseline within the predetermined timeframe that corresponds to a utilitarian time frame for the evaluation, that meets and / or exceeds and / or falls below (or above) a threshold or otherwise falls inside or outside of a range, such is flagged. In an embodiment, it can be that if the average of any of these percentages meets and / or exceeds and / or falls below a threshold or otherwise inside or outside a range, such as flagged. It can be that the change relates only to threshold levels or only two comfort levels, or the change applies to both, where, with respect to the latter, if there is a change in threshold level that meets the criteria but there is not a change in comfort level that meets the criteria, such would not be flagged. In an exemplary embodiment, the change is an absolute value, e.g., a change that equals and / or exceeds 3, 4, 5, 10, 15, 20, 30, 40 or 50 or any value or range of values therebetween in one increment current levels. In an embodiment, the change is a percentage of the lower number or the highest number for a threshold and / or comfort level for a given channel, such as a change of greater than and / or equal to 4, 5, 6, 7, 8, 9, 10, 15, 25, 40, 55 or 70 %or more or value or range of values therebetween in 1% increments. In an exemplary embodiment, these changes occur over a period that is less than, greater than and / or equal to 30, 40, 50, 90, 100, 125, 250, 450, 900, 1500 or 2000 or more days or any value or range of values therebetween in one day increments. Note also that a rate of change over any of the noted temporal periods for any of the features / phenomena herein can be evaluated and utilized as a trigger for flagging, etc.Atty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCI

[0065] Figure 10 shows by way of example only and not by way of limitation, a graphical representation of map settings (non-ghosted circles (comfort levels) and ovals (threshold levels)) for a 22 channel cochlear implant that is identified in the database by way of example as the map that is currently being used by the cochlear implant that is the subject of the method. Also shown is a prior map for that cochlear implant (the ghosted data points). That is, the ghosted circles show baseline settings for each channel. And the solid non-ghosted circles are the current settings. The horizontal bars show the compliance limits for each channel. The comparison between the data points for the settings can be made automatically, and if one or more of the above criteria is met, this can be flagged. Evaluation can include determining that none of the criteria are met, or otherwise that no rule for flagging changes in setting values has been triggered or otherwise met, and thus changes in levels of the threshold and comfort (the settings are proxies for the threshold and comfort levels - a threshold current level setting corresponds to the current level for that frequency required to evoke a hearing percept, and thus is the threshold of hearing at that frequency) would not be flagged or otherwise indicated to the user or the entity executing the method as something that should be investigated or otherwise indicative of a change that warrants further attention. Of course, it can be indicated to the user that there are no significant changes in threshold and / or comfort levels.

[0066] Also seen in figure 10 are values for NRT measurements for a given recipient of the given cochlear implant. Here, these are taken post operatively. This is in accordance with the above embodiment. The measurements need not be displayed with the settings for threshold and comfort levels. These can be displayed separately for the various channels. And with regard to displaying data, it is noted that the graphic presented in figure 10 is not necessarily a result of the action of evaluating the data that is accessed. Moreover, this may not be utilized with respect to the action of gauging efficacy of the medical device, etc., determining if specific rules are met or not met, or otherwise if the criteria being met or not met corresponds to such. Conversely, some embodiments include the ability of the entity executing the method to further evaluate the data and otherwise explore the data. Accordingly, in an embodiment, it can be that the computer system flags the medical device related data as including data indicative of a change in threshold and / or comfort levels that warrants further scrutiny. The user can click on an icon or otherwise utilize the computing system to access additional data, which data can be presented in a manner analogous to or otherwise corresponding to that seen in figure 10.Atty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCI

[0067] As will be described further below, embodiments include the ability of the user to obtain additional data utilizing the computer system detailed herein. In an exemplary embodiment, upon a finding that a rule associated with telemetry has been violated for example, a user can be prompted to click an icon to obtain additional details. The screen shown in figure 10A can be provided to the user for visual inspection. This can be based on data extracted from the database or from a given file.

[0068] Embodiments have focused on a comparison between baseline map settings and the current map settings, where the baseline is the baseline set at the first fitting or the original fitting, or that which corresponds to adjustments thereto made shortly thereafter, and the current map being the map that exists or otherwise is being used, or otherwise to which the recipient has access (a medical device can have two or more maps and a recipient can select between the two), which exist in reality. But note that it can be that the database does not include the current map, in which case the latter map would be a map that was previously used. Embodiments include the comparison of maps where such does not include the first map / original map and / or the current map or latest map. Because of the evaluated nature of the teachings detailed herein, there can be utilitarian value with respect to retroactively evaluating older maps even if one or more of these maps are not being used. This can have utilitarian value with respect to evaluating trends with respect to the recipient and / or a given medical device. Accordingly, any map can be evaluated or otherwise serve as the baseline or the map under evaluation that can have utilitarian value. This can be indicated to the user of the method or the like. Thus, embodiments can include evaluating two or more maps and determining whether the criteria for flagging has occurred between any two maps. By way of example only and not by way limitation, say that every year, a new map was developed for a given recipient over the course of five years. There would be thus six maps. Map 1 would be the year zero or otherwise the initial fitting, map 2 would be the map developed one year after the initial fitting, map 3 would be the map developed two years after initial fitting, and so on. In an embodiment, the action of evaluating the accessed data can include comparing each map to each other. It can be that maps 2 and 4, or more accurately, the comparison between the two, meet the criteria, and this is flagged. It can be that none of the other maps, or more accurately, the comparison between the maps, meet the criteria, for whatever reason (e.g., the differences between map 1 and map 6 are less than the differences between maps 2 and 4, using the given rules / criteria). The details of this can be further explained or otherwiseAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIprovided to the user, with the flagging or as a subset of data that can be accessed if further investigation is desired by the user.

[0069] Also seen in FIG. 10 are the current setting, along with ticks (horizontal lines) for each channel / electrode. The ticks correspond to maximum current output for a given channel that a given medical device can output based on impedance measurements and / or voltage characteristics of the medical device. Additional details of this will be described below.

[0070] Another exemplary check can be compliance of a given map or various control settings of a medical device. For example, a check can be executed to determine whether a given map will be out of compliance at a maximum possible power level of 100% based on impedance measurements taken when the map was created or at a later date. That is, the impedance measurements (more on this below) can be temporally linked to a given map. By way of background, voltage compliance is the ability of the implant to deliver enough voltage to generate the requested current level or otherwise to generate a current level that will fall within (inclusive) the range of threshold and comfort levels (in practice, it will be to meet the highest comfort level because that will be the highest current required). That is, the maximum voltage available for the medical device, such as the implant of the medical device, is insufficient to generate the desired current level on one or more of the channels. When this occurs, the recipient of the medical device, e.g., a recipient of a cochlear implant, does not perceive loudness growth when stimulation is increased. The recipient might perceive an unbalanced hearing and / or sound quality issues associated with the hearing prosthesis. Embodiments include medical devices, such as cochlear implants, that automatically detect “out of compliance” electrodes or channels. This can be done by the use of compliance telemetry, where the implant is self-evaluating or the external device evaluates performance of the implant, whether that be the implanted portion or the external portion or both, or a remote device, such as a smart phone or the like, performs the evaluation or otherwise the data collection, or a geographically located device performs the analysis when provided the data obtained by the medical device or the smart phone or other assistant device, etc. In an embodiment, the data that is accessed can include indicators as to whether or not a given map or otherwise control settings contain one or more channels that are out of compliance. In an embodiment, a check can be made as to whether or not self-compliance or self-evaluation of the medical device is occurring or whether or not such has utilitarian value (it can be thatAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIthere is a malfunction or insufficient data or Band-Aid is being utilized by the medical device, thus resulting in bad self-evaluations).

[0071] Figure 11 presents a graphic indicating an exemplary scenario where electrodes 1, 2 and 3 are out of compliance. Here, the maximum amount of current output for each channel / electrode, taking into account impedance (more on this below) that can be outputted by the medical device, has been calculated / determined, and is represented by the horizontal ticks. The maximum amount of current output for channels 1, 2 and 3 is below the setting for comfort level for those channels / electrodes. In this exemplary scenario, if a check was run on electrode compliance / channel compliance, this medical device, or more accurately, this dataset for this map for this medical device would be flagged and brought to the attention of the user. It can be that the flagging simply indicates that one or more channels are out of compliance. It can be that the flagging indicates the exact number of channels and / or the exact channels. It can also be that the flagging indicates the percentage by which one or more channels is out of compliance. This can be part of the evaluation process of method 600 are method 700. Note also that it can be that not all out of compliance channels are flagged or otherwise not all datasets that have out of compliance channels are flagged. For example, it can be that the amount that a given channel is out of compliance is de minimus. The rule set that is utilized in the method can flag a dataset where the channels are more than 3% or 5% or 10% out of compliance. The percentage can be based on the difference between the threshold level and comfort level for that channel. It can be based on an absolute value, or can be based on utilizing the comfort level for example as the denominator in the percentage calculation. In an exemplary embodiment, the evaluation can result in flagging a dataset only if one or more channels are out of compliance by a predetermined amount. It also can be that the percentage of channels that are out of compliance can be a basis for a rule to flag a dataset or a medical device. For example, in the embodiment of figure 11, if the rule required more than three channels to be out of compliance for the dataset to be flagged, this dataset would not be flagged. If the rule was that two or more channels are required to be out of compliance for the dataset to be flagged, this dataset would be flagged. The average amount that the out of compliance channels are out of compliance can be calculated and that can be a basis for flagging the dataset. A combination of these can be utilized to establish rules for when a dataset is or is not flagged.

[0072] Reference is now made to figure 12, which presents an exemplary flowchart for an exemplary method, method 1200, that includes method action 1210, which entails executingAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCImethod 600 or 700. Method 1200 further includes method action 1220, which includes the action of automatically presenting, via the computing system, based on result(s) of the evaluation, one or more portions of the accessed data and / or determinations about the accessed data that warrant further analysis according to predetermined rules. The one or more portions of the accessed data can be the status of the manual power control and / or enablement of auto power control. This can be the presence or absence of telemetry response data. With respect to determinations about the accessed data, this can be, for example, that the rate of change of the voltage over time has a value above a certain predetermined level. This can be the presence or absence of a significant change in threshold and / or comfort levels. This can also be the amount that has changed over a given period of time.

[0073] In some embodiments, the action of automatically presenting excludes one or more portions of the accessed data and / or determinations about the access data that do not warrant further analysis according to the predetermined rules. Here, this can be the status of the manual power control and / or enablement of auto power control, depending on the rule. This can be the rate of change of voltage over time and / or the presence or absence of a significant change in the threshold or comfort levels, etc. All of this depends on the given rule.

[0074] Embodiments include systems, such as a computer system, that implements at least some of the methods / functions disclosed herein. In an embodiment, there is a computer system that includes an input subsystem (e.g., including any input component of a device herein, a GUI, which can be a touch screen, a keyboard, a microphone, an LCD of a computer or CRT of a computer, a mouse and the accompanying computer screen, a USB port or an internet connection or a Bluetooth connection and the associated hardware and software) configured to receive input based on data based on medical device settings and / or phenomena recorded in association with the medical device. The computer system further includes an output subsystem (e.g., including the output component(s) of any device disclosed herein, a GUI, a touch screen, a keyboard, a microphone, a mouse and the accompanying computer screen, an LCD of a computer or CRT of a computer, a printer, a USB port or an internet connection or a Bluetooth connection and the associated hardware and software). Any device, system, and / or method that can enable the input of any part or all of the data that is utilized by the teachings detailed herein that has utilitarian value can be utilized in at least some exemplary embodiments, and the same is the case with respect to any device system and / or method that can enable the output of any part or all of the information that is disclosed herein and / or variations thereof that has utilitarian value can be utilized in atAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIleast some exemplary embodiments. In embodiments, there is a processing subsystem interposed between the input subsystem and the output subsystem, wherein the processing subsystem is configured to identify data of the received input that is aberrant from and / or compliant with one or more rules applied to the processing subsystem.

[0075] The processing subsystem can be an artificial intelligence system, that can be a neural network that is at least a partially taught neural network (which means that it can be a fully taught neural network). In an embodiment, the artificial intelligence system is a neural network that is a partially taught neural network that is trainable with feedback provided through the input subsystem or another subsystem of the system. In an embodiment, the system is configured to automatically transform the input into numerical form. This can be executed using a computer chip or a logic circuit or electronics or software or a processor, that is programmed to take the input and transform the input. In some embodiments, the input subsystem is configured to execute this functionality. Thus, the input subsystem can be more than just a mouse and computer screen and keyboard, etc. Embodiments include an input subsystem that includes a processor and / or software and / or firmware and / or hardware and / or a computer chip or a logic circuit otherwise electronics that is specifically designed and configured to execute one or more of the functionalities of the input subsystem detailed herein. The processing subsystem is configured to, using the numerical form, automatically execute one or more of the actions herein using, for example, and if, then else logic algorithm, or using a spreadsheet concept where for a range of possible inputs, there are corresponding data portions, and processing subsystem can match the input with the corresponding data portions, and then provide such to the output subsystem. Mathematical algorithms can also be utilized, such as, for example, formulas to calculate the results from the input.

[0076] Fig. 13 presents a functional schematic of a system with which some of the teachings detailed herein and / or variations thereof can be implemented. In this regard, FIG. 13 is a schematic diagram illustrating one exemplary arrangement in which a system 1206 can be used to execute one or more of any of the method actions detailed herein, in the interests of textual economy. The system of FIG. 13 can be representative of any system or part of a system that executes any one or more of the method actions herein.

[0077] System 1206 will be described, at least in part, in terms of interaction with a clinician and / or healthcare professional, although these terms are used as a proxy for any pertinent subject to which the system is applicable. In an exemplary embodiment, system 1206 is aAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIclinician controlled / used system, or a medical device manufacturer or supporter controlled system, while in other embodiments it is an independent system separate from an entity that designed / manufactured the medical device at issue, while in other embodiments, it is a remote controlled system. In an exemplary embodiment.

[0078] System 1206 can be a system having additional functionality according to the method actions detailed herein. In the embodiment illustrated, a remote device can be connected to system 1206 to establish a data communication link between a remote device, such as a remote computer and / or a smart phone, etc., and system 1206. System 1206 is thereafter bidirectionally coupled by a data communication link with a remote device in some embodiments. Any communications link that will enable the teachings detailed herein that will communicably couple the implant and system can be utilized in at least some embodiments.

[0079] System 1206 can comprise a system controller 1212 (a processor or chip(s) or any of the teachings herein) as well as a user interface 1214. Controller 1212 can be any type of device capable of executing instructions such as, for example, a general or special purpose computer, a handheld computer (e.g., personal digital assistant (PDA)), digital electronic circuitry, integrated circuitry, specially designed ASICs (application specific integrated circuits), firmware, software, and / or combinations thereof. As will be detailed below, in an exemplary embodiment, controller 1212 is a processor or a chip or a chipset, or circuitry specialized to execute one or more of the actions / functionalities herein. Controller 1212 can further comprise an interface for establishing the data communications link with a remote device (again, which is a proxy for any device that can enable the methods herein). Controller can be the processing subsystem. In embodiments in which controller 1212 comprises a computer, this interface may be, for example, internal or external to the computer. The remote device can be the medical device. However, in an embodiment, the remote device can be a remote server that provides input to an input subsystem 1310 (this can be an internet link, or any of the systems herein or others that can enable system 1206 to receive input based on data based on medical device settings and / or phenomena, etc.). For example, in an exemplary embodiment, controller 1206 and cochlear implant may each comprise a USB, FireWire, Bluetooth, Wi-Fi, or other communications interface through which data communications link may be established, but in an embodiment, the cochlear implant will communicate with a local computer, and communicate data thereto, and then the local computer will communicate with the system 1206 via the internet, thus transferring dataAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIfrom the cochlear implant. That said, in an embodiment, system 1206 communicates with a fitting device or a computer that is utilized to fit a medical device, such as a cochlear implant, to a recipient. The data at issue can be located on the fitting device or fitting computer, and then transferred via the Internet to the system 1206. In an exemplary embodiment, the medical device does not necessarily communicate with any component that communicates with the system or the system itself. In an exemplary embodiment, an entity remote from system 1206 can access the system 1206, or at least a portal therefore, to input data into the input subsystem 1310, which data corresponds to the data relating to the medical device. System 1212 can further comprise a storage device for use in storing information. This storage device can be, for example, volatile or non-volatile storage, such as, for example, random access memory, solid state storage, magnetic storage, holographic storage, etc., and can store any one or more of the data elements / information pieces detailed herein.

[0080] User interface 1214 can correspond to the output subsystem and can comprise a display 1222 and an input interface 1224 (which, in the case of a touchscreen of the portable device, can be the same). Display 1222 can be, for example, any type of display device, such as, for example, those commonly used with computer systems. In an exemplary embodiment, element 1222 corresponds to a device configured to visually display a plurality of words to the candidate and / or professional.

[0081] Input interface 1224 can be any type of interface capable of receiving information from a professional, such as, for example, a computer keyboard, mouse, voice-responsive software, touchscreen (e.g., integrated with display 1222), microphone (e.g. optionally coupled with voice recognition software or the like) or any other data entry or data presentation formats now or later developed. It is noted that in an exemplary embodiment, display 1222 and input interface 1224 can be the same component, e.g., in the case of a touch screen). In an exemplary embodiment, input interface 1224 is a device configured to receive input that can enable the teachings herein (more on this in a moment).

[0082] It is noted that in at least some exemplary embodiments, the system 1206 is configured to execute one or more or all of the method actions detailed herein, where the various sub-components of the system 1206 are utilized in their traditional manner relative to the given method actions detailed herein.Atty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCI

[0083] In an exemplary embodiment, the system 1206, detailed above, can execute one or more of the actions detailed herein and / or variations thereof automatically, at least those that do not require the actions of a candidate and / or professional.

[0084] In this vein, it is again noted that the schematic of FIG. 13 is functional. In some embodiments, a system 1206 is a self-contained device (e.g., a laptop computer, a smart phone, etc.) that is configured to execute one or more or all of the method actions detailed herein and / or variations thereof. In an alternative embodiment, system 1206 is a system having components located at various geographical locations. By way of example only and not by way of limitation, user interface 1214 can be located with the clinician / remotely (e.g., it can be the portable handheld device) and the system controller (e.g., processor) 1212 can be located remote from the professional. By way of example only and not by way of limitation, the system controller 1212 can communicate with the user interface 1214, via the Internet and / or via cellular communication technology or the like. Again, in an exemplary embodiment, the user interface 1214 can be a portable communications device, such as, by way of example only and not by way of limitation, a cell phone and / or a so-called smart phone. Indeed, user interface 1214 can be utilized as part of a laptop computer or the like. Any arrangement that can enable system 1206 to be practiced and / or that can enable a system that can enable the teachings detailed herein and / or variations thereof to be practiced can be utilized in at least some embodiments.

[0085] Thus, in an embodiment, there is a computer system, comprising an input subsystem configured to receive input based on data based on medical device settings and / or phenomena recorded in association with the medical device; and an output subsystem; and processing subsystem interposed between the input subsystem and the output subsystem, wherein the processing subsystem is configured to identify data of the received input that is aberrant from and / or compliant with one or more rules applied to the processing subsystem. The input subsystem and the output subsystem can be part of an integrated subsystem of the computer system. Indeed, the same USB port can receive input and can provide the output. An Internet connection can provide the input into the system, and this in a net connection can provide the output. Note that the input and the output would be directed to two different locations in some embodiments. The input can come from a clinician who has fit or who is fitting a medical device to a patient or otherwise working on a medical device associated with a patient a recipient. The output can go to a professional or the like who is evaluating theAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIwork of the clinician or otherwise evaluating the results of the fitting or otherwise evaluating overall efficacy of the device over any of the periods of time detailed herein.

[0086] With respect to the identification of data, this regard, as noted above, the rules can be set to identify and / or ignore any one or more features associated with medical device as detailed above, and as further detail below. In at least some exemplary embodiments, the system is configured to bring to the attention of the user of the system certain facts and issues and / or certain data portions relative to other data portions and / or other facts and / or issues. In an exemplary embodiment, the computer system is utilized as part of the method to triage a habilitation and / or rehabilitation regime resulting from use of a medical device such as a cochlear implant. This can be part of a method to triage the efficacy of the medical device over a period of time, such as any of the periods of time detailed herein. In an exemplary embodiment, the triage in total or at least in part, can be executed automatically. In an embodiment, the features and / or datasets or portions of data verified by the system for triage can be flagged automatically in accordance with the above. Note also that the overall triage can be executed in an automated fashion. This can be the case with respect to the utilization of artificial intelligence and / or big data or otherwise sufficiently robust algorithms. It can be that the user of the system ratifies and / or provides a “sanity check” to the results of the system.

[0087] In an embodiment, the computer system is configured to be accessed remotely, such as by the internet. The computer system can be a medical device (e.g., a hearing prosthesis, a cochlear implant, an active transcutaneous bone conduction device, etc.) map check tool.

[0088] In an embodiment, the processing subsystem is also configured to output data based on received input based on criteria that are unrelated to aberrance and / or compliance with one or more rules. By way of example only and not by way limitation, this can be a default output. This can be the model number and / or the design of the medical device. This can be whether or not the medical device has an identification functionality. This can be the battery type that is utilized power medical device. This can be the time since the last checkup. This output can be automatic, and thus for example presented to the user when the user accesses the system or otherwise executes one or more the method actions detailed above with respect to evaluating the medical device with respect to the criteria. This can also be a feature where the user of the system “asks” or “commands” the system to provide him data on certain topics, and the system delivers such. These are not rules based data portions, or otherwise are not presented according to rules or manipulated or evaluated according to rules in at leastAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIsome exemplary embodiments. For example, if the system outputs an indication that the medical device has one or more out of compliance channels, the user can assess that the recipient of the medical device has met with a health care professional to adjust the device (and recommend that the recipient meet with a professional to make additional adjustments). Where for example the rule is a binary rule, such as one or more channels are or are not in compliance, the user can request or command the system to provide him or her with the amount of time that those channels have been out of compliance, or the average time, etc.

[0089] Figure 14 provides an exemplary functional schematic of system where various subsystems thereof are potentially located remotely and / or otherwise are parts of different devices. Here, there is an input device or input subsystem 1410. This can be the server at the medical device manufacturing entity facility. This could alternatively be a computer at an audiologist center or an audiologist office or a field rep of the manufacturer for example or some other healthcare professional or trained professional that is working directly with the medical device. Here, the data related to the medical device and use thereof can be provided to the server 1410 or can be inputted or otherwise uploaded to the audiologists or healthcare professionals computer 1410 (a file can be uploaded to 1410). The input device / sub system is in signal communication with the processing device or subsystem 1420 via link 1490. This can be an Internet link or some other link (wired or wireless). Device 1410 can be part of an overall apparatus that includes device 1420. Processing device 1420 is in signal communication with output subsystem / output device 1430 via link 1495. This can be wired or wireless. In an embodiment, the output device could be the server of the system (note that the input subsystem and the output subsystem could be part of an overall subsystem). In an embodiment the output device 1430 could be a computer remote from device 1420 at a user who is utilizing the system or otherwise executing some of the methods detailed herein.

[0090] There can be a dynamic range channel deviation rule. Criteria can be developed against which a check of the dataset can be made to determine if the variability in a dynamic range in one or more channels and / or across the entire map is more than a certain value. Figure 15 presents an exemplary graphic showing threshold and comfort levels for a given map that is saved in the database or memory of the system (if only temporarily - any reference to a database herein corresponds to a memory and / or a system without database functionality). In an embodiment, the dynamic range is a difference between current levels between the threshold level and the comfort level in a given channel. The dynamic range can vary across the channels of a multichannel device, and thus will vary across the electrodes ofAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIthe electrode array. In an embodiment, there is a rule of the system that flags a dataset or a data portion if there is no variation in dynamic range across the electrodes and / or if there is a dynamic range variation that does not exceed a certain amount between channels and / or between groups of channels, etc. It could be, that an average can be utilized to trigger the rule or otherwise to act as a trigger for the flagging. Alternatively, it could be that the differences in the dynamic range exceed a certain value, and such is triggered.

[0091] In an exemplary embodiment, the rule applied by the system triggers a flagging if the variability in dynamic range between less than, greater than and / or equal to 2, 3, 4, 5, 10, 20, 40, or 60 channels or any value or range of values therebetween in one increments meets a given criteria. The criteria can be that the dynamic range variability is less than, greater than and / or equal to 0.25, 0.5, 0.75, 1, 1.25, 1.5, 1.75, 2, 2.5, 3, 4, 5.5, 8, 9 or 10 CLs or more or any value or range of values therebetween in 0.05 CL increments. The criteria can be that the dynamic range variability is less than, greater than and / or equal to 0.5, 0.75, 1, 1.25, 1.5, 2, 2.5, 3, 4, 6, 8 or 9% or more or any value or range of values therebetween in 0.05% increments of one or more ranges (e.g., of the lowest dynamic range of a channel, or the highest or a mean, median and / or mode of the channels, etc.). Also, channels can be grouped. For example, the dynamic range of electrode channel 3 could vary more from that of electrode channel 20 than from channel 1, because it is likely that the phenomena associated with the recipient close to electrode 3 will be more similar than such remote from electrode 3. The criteria could have a sliding scale for example. For example, a rule for flagging a dataset could be that for every channel that is away from the base channel, the variability in the dynamic range that is not flag or otherwise does not trigger a flagging action can be increased by a certain amount or certain percentage. Thus, for example, with respect to channel 1, channel 2 could have a dynamic range that is less than and / or equal to 1.0 current levels different than that of channel 1, channel 3 could have a dynamic range that is less than and / or equal to 1.05 current levels different than that of channel 1, channel 4 could be 1.08 CLs, channel 5 could be 1.1 CLs, etc. without triggering a flagging action. Channel 2, 3, 4, 5 could be all less than or equal to 1 CL, and channels 6, 7, 8, 9, 10 could be all less than or equal to 1.1 CLs, etc., without triggering a flagging action.

[0092] FIG. 15 shows data of an exemplary map where the dynamic range is not uniform (according to some criteria) across the map, and thus would likely be flagged in some embodiments. FIG. 16 shows an example of data for a map that is uniform and would not be flagged in some embodiments (the distance between the T level and C level are the same.Atty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIFIGs. 15 and 16 are exemplary data portions that could be displayed to the user upon request / command by clicking an icon, such as the “dynamic range too large” icon (or the “dynamic range too small” icon).

[0093] Embodiments include evaluation of the overall dynamic range, or at least the dynamic range within large portions of the overall map, and / or criteria associated with the dynamic range of a given channel irrespective of other channels. In an embodiment, there is a dynamic range channel rule that checks if the dynamic range is between a certain amount. In an embodiment, the system checks a difference in current levels between the threshold level in the comfort level for one or more or all channels of the system or more accurately, the data for such. In an embodiment, when an audiologist or the like creates a new map utilizing a map generation system or fitting system, including an automatic fitting system or semiautomatic sensing system, there is often a default dynamic range, which can be between 30, 35, 40, 45 or 50 CLs by way of example. In an embodiment, a dynamic range outside of an expected range could lead to less than utilitarian performance or otherwise be deemed as a medical device providing poor performance for the given recipient. A dynamic range that is too large could be an indication that threshold levels are set to low and / or comfort levels are set too high. Conversely, a narrow dynamic range could result in a loss of intensity difference, such as, by way of example with respect to a hearing prostheses, between different sounds which can be a utilitarian cue for processing speech. The systems herein could indicate such to the user (the system can provide an explanation of a result of a check (as a warning or to reinforce why the check was utilitarian or what should be considered now that the check has been executed).

[0094] In an embodiment, there is criteria that includes a rule that flags a dataset, such as a map of a cochlear implant, that includes one or more channels (any number detailed above in the interest of textual economy - it could be that the flag is executed if there are 4 channels but not 3 channels, or an average, etc.) have a dynamic range that is less than, greater than and / or equal to 5, 10, 15, 20, 30, 45, 60, 75 or 80 CLs or any value or range of values therebetween in 1 CL increments and / or that is less than, greater than and / or equal to 5, 6, 7, 10, 15, 20, 30, 45, 65, 70 or 75% or more or any value or range of values therebetween in 1% increments of the threshold level and / or the comfort level, etc. In some embodiments, a flag can be triggered based on whether or not one channel is different from an average of all the channels or channels immediately adjacent to the channel under investigation (by the system and the automated process). In an embodiment, there is an exemplary criteria that flags aAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIdataset when the dynamic range of any given channel is less than 8 current levels and greater than 60 current levels. The map of figure 16 would be considered to not meet this rule, and thus that map would not be flagged. Conversely, the map of figure 17 would be flagged because the high frequency channels have a dynamic range that exceeds 60 current levels. The map of figure 18 would be flagged because the high frequency channels have a dynamic range that is less than eight current levels. In an exemplary embodiment, the system would indicate that there exists a dynamic range channel rule violation, and this can be provided on the computer screen. The user can click the icon associated with this indication so as to see the specifics associated with the given dataset. By way of example, the graphic in figure 18 can be presented. Additional details could be provided if the user seeks to investigate further. By way of example, the user can click on, for example, the line that indicates channel 2, and the computer system could automatically provide the dynamic range for that channel or could also provide the exact threshold and / or comfort level values.

[0095] Embodiments can also include checks with criteria associated with maximus. In an exemplary embodiment, there can be a number of maxima rule. The system would check the number of maxima, and flag the data if there are less than and / or greater than and / or equal to a certain number of maxima associated with the strategy that is utilized by the medical device. In some embodiments, maxima settings specify the number of channels that are stimulated in response to a stimulation event, such as, for example, a captured sound that is to be a basis of a hearing percept to be evoked in a recipient of a cochlear implant. In an embodiment, channel selection can be based on the maximum amount of energy that is in the sound on a frequency basis. For example, speech processing strategies can utilize 8, 9 or 10 channels, where the incoming sound is evaluated, and the frequency bands that have the eight highest energy levels are selected for stimulation. Some processing strategies or otherwise stimulation strategies have defaults. In an embodiment, a maxima selection of 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 or 15 frequency bands can be utilized for a given processing strategy. These values specify the number of maxima that will be selected for any given signal by way of example. It can be that a recipient of a medical device or a healthcare professional has changed the default. This change would be recorded in the medical device, and thus in at least some embodiments should be also saved is data in the database that is evaluated or analyzed according to at least some exemplary embodiments. Accordingly, there could be a criteria that checks to see if the maxima selection corresponds to a default for a given strategy, and thus could also identify the strategy in the database and thus “know” what theAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIdefault should be, and determine whether or not the medical device is operating by setting in a manner that deviates from the default. Alternatively, the system could simply check to determine the number of maxima and if the maxima fall within a predetermined range, regardless of the strategy, such is not flagged or alternatively if the value is outside or range or is different from a predetermined number, the dataset is flagged. In an exemplary embodiment, if the dataset indicates that a maxima selection setting is such that less than greater than and / or equal to 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 or 12 or any value or range of values therebetween in one increment maxima is being implemented for a given signal (e.g., a maxima that is not 5 and / or 6 and / or 8, a maxima that is outside the range of 6 to 8 (inclusive), etc.), the dataset is flagged as having a low maxima and / or a high maxima or otherwise a violation of a maxima rule. Again, an embodiment can “know” the default maxima for a given strategy or otherwise for a given medical device, and flag the dataset if there is an aberrant maxima setting.

[0096] The concept of default can be extended in some embodiments to an evaluation as to whether or not certain control settings in general, and / or an overall map in particular, corresponds to a standardized control strategy. Standardized settings and / or default settings tend to be settings that provide or otherwise are statistically most likely to provide the best outcome for a given recipient, or at least for a cohort of recipients. By way of example, there can be default stimulation strategies, which strategies can stimulate at a given rate, such as, for example, 500, 600, 700, 850, 900, 950, 1000, 1110, 1400 Hz or any value or range of values therebetween in 1 Hz increments, with a given pulse width of, for example 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 40, 45 or 50 or more microseconds or any value or range of values therebetween in 1 ps increments, a maxima as described above, etc. Thus, in an embodiment, a criteria for flagging could be whether a given medical device has used or currently uses a nonstandard / standardized group of settings and / or map or a standard / standardized group of settings and / or map. The rule could be that if a nonstandard map for example is being utilized, such as flag. (And note that any of the checks can be present or past features / occurrences or settings, even if superseded by later things, and can be a present / nonsuperseded feature / setting, etc. (based on the data - in real life, it could be that a map has been changed, but the database does not reflect such -it could also be that the database is updated in real time, or near real time or every day or every two days).Atty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCI

[0097] In an embodiment, there can be a rule that flags a dataset if the stimulation strategy has changed from the original strategy or a default strategy and / or if a pulse width and / or a stimulation rate and / or a maxima has changed from a default and / or is out of any predetermined range, such as any of the range is just detailed above. Pulse width can be an example of data that can be provided to the user upon demand. For example, if the stimulation strategy is the cause of a flag, the user could be prompted to select an icon and click such for their information, whereupon such clicking the icon, the schematic seen in figure 15A is presented to the user on a computer screen.

[0098] Embodiments include non-transitory computer readable medium having recorded thereon, a computer program for executing at least a portion of a method according to any one or more of those detailed herein. An exemplary medium will now be described, but it is noted that this also corresponds to a disclosure of a method that is executed in part or in whole by the medium. In an embodiment, the computer program includes code for adjusting and / or setting and / or accepting (e.g., receiving and storing) predetermined medical device technology data features. Here, in this embodiment, the code could be code for fitting a hearing prosthesis. That said, in an embodiment, the code could be for receiving data features of for example, a stimulation strategy, or performance requirements or desired performance results of a medical device. For example, that the electrode channels are in compliance with respect to voltage, or that no C level requires a voltage that is higher than 80, 85, 90, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105 or 110% or more or any value or range of values therebetween in 0.25% increments of a maximum voltage that the implant can generate. The code for accepting can accept any one or more of the rules and / or criteria detailed herein. Indeed, in an embodiment, the code can enable a healthcare professional or an entity executing any one or more the method actions detailed herein, or another entity for that matter, to create the rules and / or criteria or otherwise to input the rules and criteria in accordance with the teachings detailed herein. The rules can be inputted via the GUI of the system or some other arrangement. The rules can be uploaded via a USB port or via the Internet or the like. The code could also be self-executing. For example, a stimulation strategy having parameters could be uploaded to the system utilizing the code, and the system utilizing the code can automatically analyze the properties of that stimulation strategy, increase its own rules. This could be done with, for example, artificial intelligence for example or a sufficiently robust algorithm. And because this has method connotations, referring to figure 19 is an exemplary flowchart for an exemplary method, method 1900, thatAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIincludes method action 1910, that includes the action of adjusting and / or setting and / or accepting predetermined medical device technology data features.

[0099] Consistent with the database concepts detailed herein, the medium can include code for managing data related to a specific medical device. By data related to a specific medical device, this includes for example settings and / or map data and / or usage history for example, but also can include performance features or data that is associated with the recipient of the medical device, as that is data related to a specific medical device, albeit in this instance, indirectly. Any data that is related to a medical device directly or indirectly that can be utilized in at least some exemplary embodiments can be included in the database. There is thus code for such in some embodiments. In method form, referring to figure 19, there is method action 1920, which includes the action of managing data related to a specific medical device. Note that in an embodiment, there can also be the action of accepting or receiving data related to a specific medical device. In an exemplary embodiment, the systems detailed herein have data related less than and / or equal to and / or greater than 1, 2, 3, 4, 5, 6, 7, 8, 9, 500, 1000, 3000, 10,000, 50000, 100,000, 500,000 or 1,000,000 or more or any value or range of values therebetween in one increments medical devices. The medium under discussion also includes code for analyzing the managed data in congruence with the features to flag one or more features related to the specific medical device. But note also that this code for managing data related to a specific medical device can also be code that manipulates a single data file, such as where for example the computer readable medium is stored on a computer system that does not include a database of data related to specific medical devices, but instead, such as uploaded to the computer for an individual evaluation for example. In method form, this can be seen with respect to method action 1930. Method action 1930 can include any of the actions of analyzing data detailed herein and variations thereof.[ooioo] As noted above, the systems detailed herein can be such that information regarding compliance with or violation of rules is not the only thing that is provided to the user. In an embodiment, a user can obtain additional details regarding the flagged features. Thus, in an embodiment, the medium includes code for elaborating on one or more of the flagged features. This could entail for example showing the T levels with the C levels or both or showing why a certain dataset does not meet certain rules or why a certain dataset does meet certain rules, and this can be done automatically or upon a request for an indication by the user that such is desired. The code for analyzing includes code for evaluating data related to the medical device and presenting a result of the evaluation as part of the flagging and / or asAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIan additional user initiated action. The code for evaluating evaluates the data related to a phenomenon impacting performance of the medical device. This could be impedance for example. In an embodiment, the code for evaluating evaluates data related to performance of the medical device. Here, this could be how often the device is utilized and at what volumes for example with respect to a hearing prostheses and proxy data indicating how frequently adjustments are manually made to the prostheses or medical device by the recipient, which could be a proxy indicating that the medical device is not performing as desired.[ooioi] In an embodiment, the code for evaluating the data related to settings of the medical device and / or data related to a state of the medical device. In an embodiment, the code for evaluating evaluates data relating to a temporally changing state of the medical device and / or temporally changing phenomenon associated with the medical device.

[0102] In an embodiment, for any given medical device, there are less than greater than and / or equal to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 60, 70, 100, 150, 200, 250 or 300 or more or any value or range of values therebetween in one increments temporally discrete data portions (in that one can identify a range of dates relative to another range of dates for example, such as for example the above noted scenario where every year the device was refitted or otherwise the map was adjusted, each of those yearly adjustments, or more accurately, each of the dataset associated with those yearly adjustments being a temporally discrete data portion) in the database or in a file (any reference to something in a database is an alternate disclosure of such in a single file) or otherwise accessible when executing any one or more the methods detailed herein.

[0103] Another exemplary check that can be executed in some of the methods detailed herein includes an impedance related data check. In an embodiment, there are methods of checking change in impedance over time. In an embodiment, a check can be made of impedances over time against a rule where the data will be flagged if there has been a decrease in impedance related to one or more electrodes relative to a baseline dataset, which can be a baseline measurement. This can be an impedance low flat low rule for example. In an exemplary embodiment, the baseline dataset is a baseline measurement that is executed at least 10, 30, 60, 70, 80, 125 or 175 days or any value or range of values therebetween in one day increments after an implanted medical device is implanted (after surgery) or otherwise after first use (switch-on) of the medical device. For one or more electrodes, a calculation can be executed where average impedance values of 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 or 12 or more or any value or range of values therebetween in 1 increment surrounding electrodes in an existingAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCImap (some electrodes are disabled or otherwise deactivated in some maps) are compared to the aforementioned baseline measurement or otherwise baseline dataset. In an exemplary embodiment, if there has been a decrease that meets a certain threshold, and indication will be provided to the user and otherwise the dataset will be flagged. Additionally, in some embodiments, the system could also recommend or otherwise advise the user of the system to refer to a “baseline and most recent common ground impedance graph,” an example of which is seen in figure 20, where the channels indicated as flat lows have an impedance change that meets the criteria for flagging this dataset, (the 2007 data being the baseline measurements). This is an example of data that can be further accessed upon the flagging of a dataset, which can be accessed by for example, excepting yes on a prompt to an automated query of “would you like to see the baseline and most recent common ground impedance graph?” If decrease in impedance is below a threshold or otherwise does not correspond to a criteria for flagging the dataset, the dataset would not be flagged. Note also that in some embodiments, if the aforementioned baseline dataset is not available, or otherwise because the comparisons cannot be made, this check would not be executed or otherwise would not be flagged for an excessive or aberrant change in impedance over time. Note that alternatively, it could be that a flag is prompted because the baseline dataset is not available (and thus there is no evaluation of the data).

[0104] Checks of the impedance values can be executed according to a given criteria related to the variance of the values as compared to other electrodes, such as for example, immediately adjacent electrodes or neighboring electrodes or otherwise electrodes that are not sufficiently distant that there is diminishing utilitarian value for comparison purposes. In embodiments, there is a rule that flags a dataset if the variance in impedance values as compared to the reference electrodes is greater than a certain value. In an embodiment, there is an impedance zigzag rule that will cause data to be flagged or not flagged depending on how the rules are structured. In an embodiment, there is a rule that flags the dataset if the change in impedance is more than and / or equal to a certain value such as, by way of example, 1.05, 1.1, 1.15, 1.2, 1.25, 1.3, 1.35, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2, 2.1, 2.2, 2.3, 2.4, 2.5, 2.75, 3, 3.5 or 4 or more or any value or range of values therebetween in 0.05 increments times between immediately adjacent electrodes, and / or neighboring electrodes, across less than, greater than and / or equal to 2, 3, 4, 5, 6, 7, 8, 9 or 10 or more or any value or range of values therebetween in one increment spike. And in an embodiment, if an indication is provided to the user or otherwise that an impedance rule has been violated, the system could also adviseAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIthe user to refer to the “all common ground impedance graph” (e.g., FIG. 21) if excessive variation is detected / variation that meets a given rule (one or more of channels 22-12 could violate the zig-zag rule for example).

[0105] Figure 22 provides an exemplary flowchart for an exemplary method, method 2200, which includes method action 2210, which includes the action of providing access to a computer database having respective datasets related to respective medical devices used by respective humans. In an embodiment, action 2210 entails providing access to a computer system that has access to a database having respective datasets related to respective medical devices used by respective humans and / or is configured to receive one or more datasets related to respective medical devices uses by respective humans. With respect to the latter, this can entail the ability of the system to accept an uploaded dataset as will be described in greater detail below. In this regard, the system may not necessarily have a database per se, but instead is a tool that is configured to receive individual data. Also, the system could have access to a database, but this database could be outside the system per se. The user could move data from this external database or otherwise database in a separate system into the system for evaluation in accordance with the teachings detailed herein. This movement could be on an individual medical device basis, or as a batch. Method action 2210 can be executed with any of the systems detailed herein or otherwise the methods detailed herein. In an embodiment, this can be executed via the Internet for example. Method 2200 further includes method action 2220, which includes the action of at least one of (i) receiving input that is indicative of a selection of one of the respective datasets of the database or (ii) receiving input that includes a dataset related to a specific medical device used by a specific human. This can be done as a result of the user selecting a name from a list of names on a computer screen or typing in a name into a computer that is in signal communication with the database or as part of the system that includes the database, etc. This could be done as a result of a user inputting a reference number for a medical device or a recipient or a patient. This could also be done by the user moving a file as noted above from a remote database. This can also be a file that resides on a user’s own computing system, and is uploaded via the Internet for example. The file could be created from data from a medical device. The file could be an audiologist’s file that results from “saving” or “memorializing” data associated with a clinical visit (whether remote or in person). Method 2200 also includes method action 2230, which includes the action of automatically evaluating the selected one of the respective datasets and / or receive dataset. This can be done according to any one or more of the actions detailedAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIherein. In an embodiment, the evaluation of the received input (e.g., the dataset at issue) evaluates the dataset against any one or more rules, such as, for example, a low medical device power rule (low implant power rule), a medical device ID enabled or disabled rule (implant ID disabled or enabled rule), a manual power level rule or order power level rule, a telemetry data available, a significant change to threshold and / or comfort level settings rule, and electrode voltage channel rule, a dynamic range channel deviation rule, a dynamic range channel rule, a deviant maxima rule and / or a low maxima rule, a nonstandard strategy rule or nonstandard map rule, and impedance low flat low rule and / or in impedance zigzag rule.

[0106] Methd 2200 also includes method action 2240, which includes automatically presenting one or more of the results of the evaluation. In an embodiment, one or more results are always presented (e.g., as an indication of status), and others are only presented (flagged) if a rule has been violated (or met, depending on the nature of the rule) and / or if investigation is warranted / recommended (based on the given rules). For example, in an embodiment, results of evaluation based on the power rule, the change to T or C rule, the dynamic range channel rule and / or one or both of the impedance rules are only displayed if a rule is not met (or met), and others just noted can always be displayed, or some can be always displayed. That said, it could be that it no rule was violated (or every rule is met), the display could simply be an indication that all is in compliance. Queries can be presented to the user asking if he or she would like to see additional details, such as the always presented results, etc. Any format of presenting the results can be implemented providing such has utilitarian value.

[0107] FIG. 23 shows an exemplary data conveyance to a user by the system, which can be automatically presented to the user when an evaluation / analysis is executed or can be presented upon request, which shows four parameters being displayed for visual comparison. Here, the map identification number (94), the processing strategy (ACE), the frequency of stimulation, the maxima selection (8), the date of implementation of the map, power level data, etc., is displayed for immediate reference by the user. In an embodiment, additional details, such as which of the channels has a feature that violates one or more of the rules etc., can be applied to the screen for quick visual inspection by the user.

[0108] In an embodiment, the evaluation of the input includes automatically checking the dataset for the presence and / or absence of one or more predetermined features. In some embodiments, at least one of (i) the action of receiving input results in automatic presentation of one or more data of the dataset or (ii) the method further comprises receiving inputAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIindicative of a request for presentation of one or more data of the dataset and automatically presenting one or more data of the dataset based on the received input indicative of the request for presentation. In some embodiments, the one or more data include a status of a medical device identification and / or pairing feature, the action of automatically evaluating the selected one of the respective datasets includes evaluating a change in impedance values impacted by tissue of the respective human, the action of automatically evaluating the selected one of the respective datasets includes evaluating a variation in impedance across neighboring electrodes of the medical device. In some embodiments, the action of automatically evaluating the selected one of the respective datasets includes checking for any map parameters of the medical device that are different from default parameters. The action of automatically evaluating the selected one of the respective datasets can include checking for a number of maxima and / or whether a feature of a maxima application of the medical device is different from a baseline. The action of automatically evaluating the selected one of the respective datasets can include checking a dynamic range feature of the medical device. The action of automatically evaluating the selected one of the respective datasets can include checking for a change in settings of the medical device that have occurred over a predetermined temporal period.

[0109] As noted above, the computer system of some embodiments can also allow the user to obtain additional data or otherwise access to data or otherwise view data that is not associated with an evaluation per se or otherwise a rule. An example of such is the ability to view data logging history. The computer system could present an icon to the user that when selected, presents a graphic on the computer screen of the system as shown in figure 24, which would provide various metrics associated with data logging for easy visual inspection. Additional details could be provided.[oono] In an embodiment, the methods and devices and / or systems detailed herein can be considered the use of a system for and / or an embodiment of a map check or the like. This can be a web-based software that supports access to information contained in a patient file and / or a file related to a medical device. This can be by way of example only and not by way of limitation, a computer readable file. This can contain settings and parameters of the recipients map by way of example, and / or other settings or parameters related to control settings or other features related to the recipient, whether or not such is physically identifiable by evaluating the device to the exclusion of a human recipient or patient. That is, the file could contain data related to physical phenomenon associated with the recipient that may orAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCImay not be impacted with the medical device, but are features that are related to the medical device in the total scheme of things. In an embodiment, a database analysis system which can be a commercially available system that can be used to manipulate and / or sort and / or analyze and / or evaluate data in a file that is a patent device setting file / a file that is usable in a database or otherwise can be uploaded that contains data that can be read by the systems herein in an automatic manner (digital data that can be accessed by a computer), which can be a commercially available database management tool can be utilized to implement at least some of the teachings detailed herein. In an embodiment, an interface layer can be superimposed over the underlying database management software or use software, so as to limit the reinventing of the wheel. In an embodiment, the software utilizes an algorithm that generates a GUI interface and includes a layer where the rules and / or queries can be stored or otherwise the layer includes the programming to implement the rules and receive input to create the rules. This layer interfaces with the underlying database software and manipulates the character strings into binary data for example, so that a request for search and / or evaluation, etc., can be made to the database in a manner that will be understood or otherwise recognized by the database. The results of the return information from the database, which could be for example, all of the data associated with a given patient with respect to the aforementioned file, could then be manipulated and evaluated according to the teachings detailed herein for compliance or otherwise to determine whether or not the dataset meets or does not meet one or more the criteria, which criteria is manipulated or otherwise used as a basis to further sort the data of the given file for presentation purposes. Embodiments include a layer that extracts information from a given file and checks that information against any one or more of the rules detailed herein.[oom] Figs 25 and 26 present exemplary images that can be presented on that GUI or otherwise the computer screen that outputs data to the user. Here, for example, the results of a check of the dataset utilizing the various rules detailed herein rules results in eight different data portions being presented to the user. In the embodiment of figure 25, there are eight different icons where the user can click or otherwise select to expand the data associated there with. The embodiment of figure 26 presents seven different icons. These are the results of the analysis according to some of the methods detailed herein. With respect to the check that results in figure 25, there is a variation in impedance that violates a rule, and thus this check is displayed. With respect to the check that results in figure 26, there is no variation in impedance that violates and impedance variation rule, and thus this check is not displayed.Atty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIAlso, it is noted that the system can provide details of the check for the user for instructional and / or sanity check purposes. Figure 27 presents an example of what happens when a given check box is selected for expansion, where here, explanation of the check is provided. This can enable the user to evaluate the check system or otherwise provide a basis for the user to implement his or her expertise or judgment based on the overall check. It could be that the checks that the system implemented are not deemed sufficient (subjectively) by the user, and the user could investigate the underlying data or otherwise revise checks or create a alternate check regime that is utilized for this particular recipient. Indeed, embodiments can allow a user to customize the checks. In an embodiment, the system provides an input subsystem where the user can create his or her own checks, and this checking regime is implemented for that particular user. For example, the user could change the number of maxima that results in a flag or the size of the dynamic range, etc. A check would be run utilizing the particular check regime created by the user as opposed to a default check regime. Both could be run, and the differences between the two could be presented to the user.

[0112] Briefly, it is noted that the methods herein and the devices and systems and software can be for and not for evaluating a medical device in real time, at least in some embodiments (although in some embodiments, such is not exclusive, but in other embodiments, they are mutually exclusive). Instead, this is a method of evaluating features related to a specific medical device in a database containing data based on data related to that specific medical device. In this regard, the medical device is not in signal communication with the computing system at the time that the computing system is accessed and / or at the time that the data is accessed (method action 610 and 620). This can also be the case with respect to method action 630 and / or method action 720. In an embodiment, at the time of the execution of any one or more the method actions detailed herein, the medical device is not in signal communication with the computing system. Indeed, in at least some exemplary embodiments, the medical device is remote from the computing system, such as, for example, tens of miles or hundreds of miles or even thousands of miles from the computing system. In an embodiment, a healthcare professional who could access one or more control settings that medical device in a technically competent and medically acceptable manner is any one or more of those distances away from the medical device. In an embodiment, at the time of the executions of any one or more these method actions, a healthcare professional or the like has no access to that medical device, directly or remotely. Embodiments thus include executing any one or more the method actions and / or utilizing any of the systems and / or softwareAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIdetailed herein to the exclusion of using such or even being capable of using such to directly access the medical device. Accordingly, the accessed data is non-real-time data. In an exemplary embodiment, the accessed data is data that is at least 5, 10, 15, 20, 25, 30, 35, 40, 60, 120, 180 minutes or more or 5 or 10 or 15 or 20 hours or more or 1, 2, 3, 4, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 70, 80, 90, 100, 125, 150, 175, 200, 250, 300, 350, 400, 500, 600, 700, 800, 900, 1000, 1250, 1500, 1750, 2000, 2500, 3000, 3500, 4000, 4500, 5000, 6000 or 7000 days old or older or any value or range of values therebetween in 1 minute increments or 1 our increments or 1 day increments, respectively (e.g., 22 minutes, 18 hours, 25 to 33 days, etc.). In an embodiment, the data can be real time data.

[0113] The data can be data that is obtained or was obtained within seconds or within minutes of any one or more the method actions detailed herein.

[0114] These implementations can be implemented utilizing if-then-else algorithms and otherwise logic to vet the different portions of data in the different datasets. This can be utilitarian as it can orient the user on the information contained in a given dataset and thus orient the user more quickly to the holistic meaning or impact of a given map for a given patient.

[0115] Embodiments have often been described in terms of a database having one or more data files associated with various patients and / or medical devices. In other embodiments, there is no database per se, or at least the presence of such is not necessary to implement at least some of the methods and / or systems of the teachings herein. For example, the method action 620 of obtaining access to data based on data based on the medical device settings via a computing system could be executed by for example uploading a given file, such as the data file, to the computing system. This could be dragging the file from an email for example into a portal for the computer system or otherwise uploading a file saved on the hard drive to the computing system. This could be opening the file on the computing system, where there is only one file. There could be two or more files on the system as well. This could enable a web-based approach where the software for executing one or more the method actions is located remotely. Accordingly, a system need not necessarily have a database of all of the files. This can be located on a separate system. Figure 28 presents an exemplary graphic that can be presented on a GUI of the system. Here, the given file has been selected and uploaded or ready for uploading to the system, and upon clicking the submit button, one or more of the analysis and / or evaluation actions are executed by the system, or the file is uploaded and then such is executed. Records of clinical sessions can be viewed utilizing a sessions tab forAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIexample. This can have utilitarian value with respect to allowing the user to determine how often or how few times the recipient of the medical device has had his or her device adjusted or checked in a clinical session. This can allow the user to select a set of data associated with one particular clinical session for evaluation.

[0116] Embodiments include a method where a clinician uses one or more of the devices and / or systems herein or executes one or more of the method actions herein to analyse clinician-configurable device settings (in the recipient data file for example - any file (digital for example) that contains data based on data based on adjustable settings of the medical device that can be used to enable any of the teachings herein can be used in some embodiments - the data can be uploaded from the medical device or can be created with a “wall” or “air gap” between the medical device and the system that is used to create the file) to provide / obtain notice (e.g., early notice) of non-normative or aberrant (from a statistically significant dataset, such as one based on a cohort of which the recipient and / or the particular medical device belongs (the former relating to age, sex, hearing loss time or onset date of hearing loss, etc.) device settings. The method includes evaluating the notice to determine if the settings are causing an overall issue with the device. For example, “bad” settings can masquerade as a different kind of issue with the medical device. An example of a different kind of issue is one pertaining to personalizing / fine tuning the device to match the recipient’s hearing loss, which can otherwise lead to more painstaking hearing tests and tweaking of the fine tuning. A further example of a different kind of issue is one pertaining to faults in the device firmware and / or hardware and / or software which can otherwise lead to unnecessary hardware reset or return to manufacturer. In an embodiment, an entity and / or the user is informed that a recipient is having an undesired or otherwise a less than desirable experience with a medical device (whether due to recipient information or based on latent variables), the desirability can be objective and / or subjective and / or based on statistical outcomes. Without the teachings herein, a default or a prime option could be to evaluate the medical device for a fault or defect and / or to engage in fine tuning of the settings for the recipient. Conversely, an embodiment of this method can include first executing one or more of the methods herein to “triage” the device to determine if there are the non-normative settings, etc. If there are one or more settings that are different / aberrant or otherwise not normal, or otherwise are different from what should, on a statistical basis, be present, for a given cohort, etc., the impact of those settings would first be evaluated / ascertained, before moving on to the more labour intensive and / or disruptive options (e.g., a factory reset of theAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCImedical device). In an embodiment, the user could recommend or in fact execute one or more changes to return one or more of the settings back to or towards a more normative value, etc. If the less than desirable results persist, then the method moves on to evaluate other issues, such as the utilitarian nature of fine tuning the device settings to the recipient and / or resetting or replacing one or more components of the medical device.

[0117] Thus, there is utilitarian value in identifying non-normative device settings early in the consultation process in which device recipients frequently present initially with complaints that suggest the presence of one or more of those different kinds of issues

[0118] In an embodiment, the electronics of the system is or includes an artificial intelligence subsystem that is used to implement one or more of the actions herein. This could instead be conventional logic circuitry. In an embodiment, the electronics implements machine learning and / or is a product of machine learning.[oooi] In an embodiment, the artificial intelligence system is a neural network that is at least a partially taught neural network (which means that it can be a fully taught neural network). It can be a deep neural network or can include such. In an embodiment, the artificial intelligence system is a neural network that is a partially taught neural network that is trainable with feedback provided through the input subsystem or another subsystem of the system. In an embodiment, the electronics includes or is a product of machine learning. The electronics can be configured to implement machine learning.

[0119] In an embodiment, the electronics and / or software used by the electronics (herein, reference is made to electronics - however, this is done in the interest of textual economy, and any reference to electronics corresponds to a corollary disclosure of and / or firmware that is utilized with the electronic) are configured to analyze data received via the input subsystem, and this can be or include a product of machine learning to develop output. In an exemplary embodiment, this can correspond to analyzing the raw data that is inputted to the system and / or analyze modified data or filtered data or transformed data (hence analyzing data based on the obtained data - this can be the data or data that has been transformed provided into the input subsystem). In an exemplary embodiment, the electronics can be or can include a chip that is fabricated based on the results of machine learning. In an exemplary embodiment, the electronics and / or software and / or firmware is a neural network, such as a deep neural network (DNN). The electronics and / or software and / or firmware can be based on or be from a neural network. In an exemplary embodiment, the system includes code to implement oneAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIor more of the teachings detailed herein. In an exemplary embodiment, the electronics includes a logic circuit that is fabricated based on the results of machine learning. The electronics can be an ASIC (e.g., an artificial intelligence ASIC). The electronics can be implemented directly on a silicon structure or the like. Any device, system, and / or method that can enable the results of artificial intelligence to be utilized in accordance with the teachings detailed herein, can be utilized in at least some exemplary embodiments. The electronics and / or software can be a trained neural network or a trained deep neural network and / or can be a product based on or from the neural network whatever that may be.

[0120] It is noted that any method action disclosed herein corresponds to a disclosure of a non-transitory computer readable medium that has program there on a code for executing such method action providing that the art enables such. Still further, any method action disclosed herein where the art enables such corresponds to a disclosure of a code from a machine learning algorithm and / or a code of a machine learning algorithm for execution of such. In some embodiments, the code results from traditional programming. Still, in this regard, the code can correspond to a trained neural network. That is, as will be detailed below, a neural network can be “fed” significant amounts (e.g., statistically significant amounts) of data corresponding to the input of a system and the output of the system (linked to the input), and trained, such that the system can be used with only input, to develop output (after the system is trained). This neural network used to accomplish this later task is a “trained neural network.” That said, in an alternate embodiment, the trained neural network can be utilized to provide (or extract therefrom) an algorithm that can be utilized separately from the trainable neural network.

[0214] It is noted that any method detailed herein also corresponds to a disclosure of a device and / or system configured to execute one or more or all of the method actions associated therewith detailed herein. In an exemplary embodiment, this device and / or system is configured to execute one or more or all of the method actions in an automated fashion. That said, in an alternate embodiment, the device and / or system is configured to execute one or more or all of the method actions after being prompted by a human being. It is further noted that any disclosure of a device and / or system detailed herein corresponds to a method of making and / or using that the device and / or system, including a method of using that device according to the functionality.

[0215] It is also noted that any disclosure herein of any process of manufacturing other providing a device corresponds to a device and / or system that results there from. It is alsoAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCInoted that any disclosure herein of any device and / or system corresponds to a disclosure of a method of producing or otherwise providing or otherwise making such.

[0216] Any method action disclosed herein can be executed in an automated or manual manner, providing that the art enables such.

[0217] Any embodiment or any feature disclosed herein can be combined with any one or more or other embodiments and / or other features disclosed herein, unless explicitly indicated and / or unless the art does not enable such. Any embodiment or any feature disclosed herein can be explicitly excluded from use with any one or more other embodiments and / or other features disclosed herein, unless explicitly indicated that such is combined and / or unless the art does not enable such exclusion.

[0218] While various embodiments of the present invention have been described above, it should be understood that they have been presented by way of example only, and not limitation. It will be apparent to persons skilled in the relevant art that various changes in form and detail can be made therein without departing from the spirit and scope of the invention.

Claims

Atty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCICLAIMSWhat is claimed is:

1. A method, comprising:obtaining access to a computing system;via the computing system, obtaining access to data based on data based on medical device settings and / or phenomena recorded in association with the medical device;executing an automated evaluation of the accessed data; andgauging efficacy of the medical device based on results of the automated evaluation.

2. The method of claim 1, wherein:the medical device is not in signal communication with the computing system at the time that the computing system is accessed and at the time that the data is accessed.

3. The method of claims 1 or 2, wherein:the accessed data is non-realtime data.

4. The method of claims 1, 2 or 3, wherein:the automated evaluation of the accessed data includes an automated check of the accessed data based on predetermined rules.

5. The method of claim 4, wherein:there are at least seven predetermined rules.

6. The method of claims 1, 2, 3, 4 or 5, wherein:the automated evaluation of the accessed data is a check of a medical device map.

7. The method of claims 1, 2, 3, 4, 5 or 6, further comprising:automatically presenting, via the computing system, based on result(s) of the evaluation, one or more portions of the accessed data and / or determinations about the accessed data that warrant further analysis according to predetermined rules.

8. The method of claim 7, wherein:Atty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIthe action of automatically presenting excludes one or more portions of the accessed data and / or determinations about the accessed data that do not warrant further analysis according to predetermined rules.

9. A computer system, comprising:an input subsystem configured to receive input based on data based on medical device settings and / or phenomena recorded in association with the medical device; andan output subsystem; anda processing subsystem interposed between the input subsystem and the output subsystem, wherein the processing subsystem is configured to identify data of the received input that is aberrant from and / or compliant with one or more rules applied to the processing subsystem.

10. The computer system of claim 9, wherein:the computer system is configured to be accessed remotely.

11. The computer system of claims 9 or 10, wherein:the computer system is a medical device map check tool.

12. The computer system of claims 9, 10 or 11, wherein:the processing subsystem is also configured output data based on received input based on criteria that are unrelated to aberrance and / or compliance with one or more rules.

13. The computer system of claims 9, 10, 11 or 12, wherein:the medical device is a cochlear implant.

14. The computer system of claims 9, 10, 11, 12 or 13, wherein:the one or more rules includes a power rule of the medical device.

15. The computer system of claims 9, 10, 11, 12 or 13, wherein:the one or more rules includes a medical device identification rule.

16. The computer system of claims 9, 10, 11, 12, 13, 14 or 15, wherein:the one or more rules includes a power management rule.Atty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCI17. A non-transitory computer readable medium having recorded thereon, a computer program for executing at least a portion of a method, the computer program including:code for adjusting and / or setting and / or accepting predetermined medical device technology data features;code for managing data related to a specific medical device; andcode for analyzing the managed data in congruence with the features to flag one or more features related to the specific medical device.

18. The medium of claim 17, further comprising:code for elaborating on one or more of the flagged features.

19. The medium of claims 17 or 18, wherein:the code for analyzing includes code for evaluating data related to the medical device and presenting a result of the evaluation as part of the flagging and / or as an additional user initiated action.

20. The medium of claim 19, wherein:the code for evaluating evaluates data related to a phenomenon impacting performance of the medical device.

21. The medium of claim 19, wherein:the code for evaluating evaluates data related to performance of the medical device.

22. The medium of claim 19, wherein:the code for evaluating evaluates data related to settings of the medical device.

23. The medium of claim 19, wherein:the code for evaluating evaluates data related to the state of the medical device.

24. The medium of claim 19, wherein:the code for evaluating evaluates data related to a temporally changing state of the medical device.Atty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCI25. A method, comprising:providing access to a computer system that has access to a database having respective datasets related to respective medical devices used by respective humans and / or is configured to receive one or more datasets related to respective medical devices used by respective humans;at least one of:receiving input that is indicative of a selection of one of the respective datasets of the database; orreceiving input that includes a dataset related to a specific medical device used by a specific human;automatically evaluating the selected one of the respective datasets and / or received dataset; andautomatically presenting one or more of the results of the evaluation.

26. The method of claim 25, wherein:the evaluation of the received input includes automatically checking the dataset for the presence and / or absence of one or more predetermined features.

27. The method of claims 25 or 26, wherein at least one of:the action of receiving input results in automatic presentation of one or more data of the dataset; orthe method further comprises receiving input indicative of a request for presentation of one or more data of the dataset and automatically presenting one or more data of the dataset based on the received input indicative of the request for presentation.

28. The method of claim 27, wherein:the one or more data include a status of a medical device identification and / or pairing feature.

29. The method of claim 26, wherein:the action of automatically evaluating the selected one of the respective datasets includes evaluating a change in impedance values impacted by tissue of the respective human; orAtty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIthe action of automatically evaluating the selected one of the respective datasets includes evaluating a variation in impedance across neighboring electrodes of the medical device.

30. The method of claims 26 or 29, wherein:the action of automatically evaluating the selected one of the respective datasets includes checking for any map parameters of the medical device that are different from default parameters.

31. The method of claims 26, 29 or 30, wherein:the action of automatically evaluating the selected one of the respective datasets includes checking for a number of maxima and / or whether a feature of a maxima application of the medical device is different from a baseline.

32. The method of claims 26, 29, 30 or 31, wherein:the action of automatically evaluating the selected one of the respective datasets includes checking a dynamic range feature of the medical device.

33. The method of claims 26, 29, 30, 31 or 32, wherein:the action of automatically evaluating the selected one of the respective datasets includes checking for a change in settings of the medical device that have occurred over a predetermined temporal period.

34. A device, comprising:an input terminal including one of a monitor, keyboard and mouse combination or a server, the input terminal being configured to receive input based on data based on medical device settings and / or phenomena recorded in association with the medical device;an output terminal including one of a monitor, keyboard and mouse combination or a server; anddedicated electronics circuitry interposed between the input subsystem and the output subsystem, wherein the dedicated electronics circuitry is configured to identify data of the received input that is aberrant from and / or compliant with one or more rules applied to the dedicated electronics.Atty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCI35. A device and / or system and / or method and / or computer readable medium, wherein at least one of:the method includes any one or more of the method actions of any one or more of claims 1-9 and 25-33;the system includes any one or more of the features of any one or more of claims 9-16;the computer readable medium includes code to execute any one or more of the method actions of claims 1-9 and 25-33;the computer readable medium includes any one or more of the features of claims 17-24;the method includes any actions executed by the computer readable medium of claims 17-24;the method includes and / or the device / system is configured to log data for any one or more of the method actions and / or functionalities of any of the claims;the accessed data is data that is at least 5, 10, 15, 20, 25, 30, 35, 40, 60, 120, 180 minutes or more or 5 or 10 or 15 or 20 hours or more or 1, 2, 3, 4, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 70, 80, 90, 100, 125, 150, 175, 200, 250, 300, 350, 400, 500, 600, 700, 800, 900, 1000, 1250, 1500, 1750, 2000, 2500, 3000, 3500, 4000, 4500, 5000, 6000 or 7000 days old or older or any value or range of values therebetween in 1 minute increments or 1 our increments or 1 day increments, respectively;there are at least and / or equal to and / or no more than 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 40, 45, 50, 55 or 60 or more or any value or range of values therebetween in one increment rules;determining whether medical device ID status is even present within the dataset or otherwise whether the medical device even has the identification functionality in the first instance;any one or more of the method actions are executed automatically;the method includes a check to verify if certain data is present in a first instance; the data includes neural telemetry response data;the medical device is one of a cochlear implant, a tinnitus treatment device, a retinal prosthesis, a hearing prosthesis, a sensory prosthesis or a heart prosthesis;the method includes a check on a source of the data to be evaluated;Atty. Docket No. 5441-222PCT Client Ref. No. CID04063 WOPCIthe method includes a temporal check on the source of the data to be evaluated; the checks include a check of one or more data portions of more than or equal to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 or 20 maps of the medical device; the check evaluates a deminimus nature of a data portion;the method is executed by an artificial intelligence system;the medical device is implanted in a human at a time that all of the method actions are executed of any one or more of claims 1-34;the action of automatically presenting excludes one or more portions of the accessed data and / or determinations about the access data that do not warrant further analysis according to the predetermined rules;the method is executed through the world- wide- web;the method includes adjusting one or more features of the medical device based on a result of the method;the system is configured to automatically adjust one or more features of the medical device based on an evaluation of the data;the method includes providing a recommendation and / or instruction to an audiologist and / or the recipient to take an action based on one or more of the method actions and / or functions executed by the system;the system includes a layer that extracts information from a given file and checks that information against any one or more of the rules of the system;the method is executed at least 100 miles from the medical device; orthe method includes obtaining access to a data file of a medical device indicated as having less than desirable performance results, executing one or more actions of one or more of the methods above, determining that it is likely that the less than desirable performance results are due to non-normative settings, and recommending and / or adjusting one or more settings of the medical device, and performing additional tests, and if the performance results are not as desirable as they are desired to be, proceeding to fine tune settings of the medical device and / or replace and / or reset one or more components of the medical device;the system and / or method is executed with a system that has data related less than and / or equal to and / or greater than 1, 2, 3, 4, 5, 6, 7, 8, 9, 500, 1000, 3000, 10,000, 50000, 100,000, 500,000 or 1,000,000 or more or any value or range of values therebetween in one increments medical devices.

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