Controller based on lifestyle event detection

Abstract

A controller and associated sensor system for enhancing automatic drug delivery are provided. The controller and associated sensor system are based on the detection and determination of specific physical lifestyle events. Specifically, for example, a pump enhancement system includes: a six-axis accelerometer sensor, a gyroscope pitch sensor, and a controller. The controller is configured to receive motion data from the six-axis accelerometer sensor and direction data from the gyroscope pitch sensor. The controller provides a pump instruction signal for changing the drug delivery rate to the user based on the motion data and the direction data. When the pump is an insulin pump, the pump enhancement system is an insulin pump enhancement system that provides precise insulin control for controlling the user's blood sugar level.

Description

Technical Field

[0001] The present invention generally relates to a controller and related sensor system based on lifestyle event detection, and more specifically, to a controller and related sensor system for enhancing automatic drug delivery based on the detection and determination of specific lifestyle events. In one aspect, the controller and related sensor system are related to the operation of an insulin pump, and more specifically, to an insulin pump enhancement system (IPAS) for assisting an insulin pump in delivering insulin to a user based on lifestyle event detection. Background Art

[0002] Despite advances in diabetes management via insulin pumps, even after the introduction and integration of continuous glucose monitoring with a “closed loop” approach, conventional insulin pump systems still do not have the ability to satisfactorily detect and compensate for individual physiological, lifestyle, and exercise variations. All of these conditions frequently result in unexpected increases and / or decreases in blood glucose levels, often causing blood glucose levels to fall outside of the expected, target, or acceptable glycemic range.

[0003] For example, the mere act of waking up triggers the release of hormones that cause an increase in blood sugar levels. In non-diabetic patients, blood sugar levels are regulated organically so that these conditions go unnoticed. However, in diabetic patients, there are no (or only limited) physiological mechanisms to recognize and compensate for these conditions. Currently, the treatment of diabetes often relies on "after the fact" corrective measures to bring fluctuating blood sugar levels back into the normal range.

[0004] Even with "closed-loop" insulin pump therapy, people with diabetes continually face the opposite problem of the need to treat rising blood sugar levels. Normal physical activity, such as working, walking, or exercising, can often cause a person with diabetes to drop their blood sugar levels to dangerously low levels. Further complicating matters is that, in some cases, the same physical exertion during periods of elevated blood sugar levels can actually further increase blood sugar levels to dangerous levels.

[0005] At the heart of the overall control problem is that insulin pumps follow a strict, time-of-day-based schedule for insulin delivery and can respond to abnormal blood glucose levels only if a deviation has occurred or is occurring.

[0006] At best, conventional or closed-loop insulin pumps are inherently limited to responding indirectly to changes in interstitial fluid glucose levels, which are themselves a delayed measure of true blood glucose levels. Current treatments lack the ability to dynamically and automatically proactively increase or decrease insulin delivery rates, and therefore can only address the consequences of lifestyle or physiological activity. Summary of the invention

[0007] According to a first aspect, a controller based on lifestyle event detection may be provided, more particularly, a controller for enhancing automatic drug delivery based on detection and determination of specific lifestyle events.

[0008] For example, in one embodiment, an insulin pump enhancement system may include: a body, an accelerometer sensor, a gyro pitch sensor, and a controller. The accelerometer sensor may be disposed on the body and configured to output motion data based on the detected motion. The gyro pitch sensor may be disposed on the body and configured to output direction data based on the detected direction. The controller may communicate with the accelerometer sensor and the gyro pitch sensor. In addition, the controller may be configured to receive the motion data and / or the direction data. The controller may be configured to generate a pump command signal based on the motion data and / or the direction data. The pump command signal may include a signal to change the insulin delivery rate of the insulin pump.

[0009] The signal to change the insulin delivery rate of the insulin pump may be a signal to decrease or increase insulin flow, a signal to start insulin flow, a signal to stop insulin flow, or a signal to deliver a bolus amount of insulin.

[0010] According to another embodiment, the controller can be configured to analyze the motion data and / or the directional data on a time-weighted basis. In addition, the controller can be configured to utilize a data pattern matching algorithm to provide a determination of a lifestyle event occurring to the user. The data pattern matching algorithm can utilize pattern data previously input by the user. The pump instruction signal can be based in whole or in part on the determined lifestyle event.

[0011] The controller may also be configured to receive circulating insulin level data indicative of insulin levels circulating in the user. The pump instructions may be based in whole or in part on the circulating insulin level data.

[0012] The controller may be configured to receive blood glucose level data indicative of a blood glucose level in a user. The pump command signal may be based in whole or in part on the blood glucose level data.

[0013] The controller may be configured to analyze the circulating insulin level data and the blood glucose level data. The pump command signal may be based in whole or in part on the analysis of the circulating insulin level data and the blood glucose level data.

[0014] According to another aspect, the controller may be configured to analyze the circulating insulin level data and the blood glucose level data in accordance with the determined lifestyle event.The pump command signal may be based in whole or in part on the analysis of the circulating insulin level data and the blood glucose level data in accordance with the determined lifestyle event.

[0015] According to yet another embodiment, the controller may be configured to analyze the motion data and / or the directional data on a time-weighted basis. The controller may be configured to compare the motion data to one or more predetermined motion data patterns stored in the pump enhancement system using a data pattern matching algorithm. The controller may be further configured to determine at least one of a type of food ingested by a user, an amount of said food ingested by a user, and a carbohydrate load derived from the user's ingestion. The controller may be configured to determine a target insulin amount based on at least one of the determined type of food, the determined amount of food, and the determined carbohydrate load. The pump instruction signal may be based in whole or in part on the determined target insulin amount.

[0016] According to another embodiment, the controller may include a memory and be configured to store in the memory the motion data and direction data received by the controller during the user's lifestyle event. In addition, the motion data and direction data may be associated with a specific type of lifestyle event in multiple types of lifestyle events.

[0017] According to one embodiment, the insulin pump enhancement system may be incorporated into and operably connected to an internal or external insulin pump that interfaces with a user.

[0018] According to one embodiment, the main body of the insulin pump enhancement system can be an independent wearable device configured to be worn by a user. The wearable device can be configured to be worn on a limb, such as worn at the wrist of the user's arm, and operably connected to an internal or external insulin pump in contact with the user.

[0019] According to another embodiment, the insulin pump enhancement system may include a microphone configured to detect audio and output audio data based on the detected audio. The controller may be configured to receive the audio data. The pump instruction signal may be based in whole or in part on the audio data received by the controller.

[0020] According to yet another embodiment, the controller may include a memory and be configured to store in the memory certain previously stored audio data received by the controller during food ingestion. The controller may also be configured to receive an identification input from a user to define and match a specific food type previously ingested and matched to the audio data received by the controller. The controller may be configured to store audio data associated with the specific food type represented by the input. In addition, the controller may be configured to determine the specific food type based on the stored audio data.

[0021] The controller may be configured to store the motion data and direction data received by the controller during a previous intake of a specific type of food in the memory. In the memory, the motion data and direction data may be associated with a specific food type in the plurality of food types.

[0022] The controller may be configured to receive a user selection of a physical ingestion characteristic for a particular food type based on the stored motion data and directional data or other physical ingestion characteristics.

[0023] According to an embodiment, the controller may be configured to select a specific food type from a plurality of food types stored in the memory based on at least one of the motion data, the direction data, and the audio data. The controller may be further configured to generate a pump instruction signal based on selecting the specific food type.

[0024] The controller can be configured to estimate the caloric intake of the user and maintain a continuous caloric count representing the sum of the caloric intake of the user over a period of time. In addition, the controller can be configured to generate a signal when the sum of the caloric intake of the user is greater than or equal to a predetermined caloric threshold.

[0025] The controller can be configured to estimate the amount of carbohydrates ingested by the user and maintain a continuous carbohydrate count representing the sum of carbohydrates ingested by the user over a period of time. In addition, the controller can be configured to generate a signal when the sum of carbohydrates ingested by the user is greater than or equal to a predetermined carbohydrate threshold.

[0026] According to another embodiment, the insulin pump enhancement system may include an indication transmitting device configured to emit a sound or vibration. The controller may be operably connected to the indication transmitting device and configured to increase the sound level and / or vibration level and increase the duration of the sound and / or vibration when the controller determines that the user does not respond to the confirmation sound or vibration.

[0027] The controller may be operably connected to the communication device and may be configured to activate the communication device when the controller determines that the user does not respond to the escalating series of alarm sounds or vibrations. Optionally, when the communication device is activated, an emergency call or message may be sent, including real-time medical information and / or location information related to the user.

[0028] According to another aspect, a pump enhancement system may include a body, at least one six-axis accelerometer sensor, a gyro pitch sensor, and a controller. The six-axis accelerometer sensor may be disposed in or on the body and configured to output motion data based on the detected motion. The gyro pitch sensor may be disposed in or on the body and configured to output orientation data based on the detected orientation. The controller may be operably connected to the six-axis accelerometer and the gyro pitch sensor and configured to receive the motion data and / or orientation data. The controller may be configured to generate a pump command signal based on the motion data and / or orientation data, wherein the pump command signal may include a signal to change a material delivery rate of the pump.

[0029] According to another aspect, a method of enhancing a pump system includes: monitoring motion data and / or direction data, and generating a pump command signal based on the motion data and / or direction data. The pump command signal may include a signal to change the material delivery rate of the pump. The pump system may include: a body; an accelerometer sensor disposed in or on the body and configured to output motion data based on the detected motion; a gyroscope pitch sensor disposed in or on the body and configured to output direction data based on the detected direction; and a controller connected to the accelerometer sensor and the gyroscope pitch sensor, the controller being configured to receive the motion data and / or direction data. The controller may perform the generation of the pump command signal.

[0030] The above and other objects, features and advantages of the present invention will become apparent through the description of the embodiments and their features, and through the illustration and supplement of the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 An exemplary IPAS-enabled insulin pump is shown according to an embodiment of the present invention;

[0032] Figure 2 An exemplary IPAS-enabled wristband device according to an embodiment of the present invention is shown;

[0033] Figure 3 Shows Figure 1 An exemplary flow chart of the operation of an IPAS according to an embodiment of the present invention;

[0034] Figure 4 Shows Figure 1 An exemplary flow chart of the operation of an IPAS according to an embodiment of the present invention;

[0035] Figure 5 Shows Figure 1 An exemplary flow chart of the operation of an IPAS according to an embodiment of the present invention; and

[0036] Figure 6Shows Figure 1 FIG. 1 is an exemplary flow chart of the operation of an IPAS according to an embodiment of the present invention. DETAILED DESCRIPTION

[0037] Before describing various embodiments in further detail, it should be understood that the present invention is not limited to the specific embodiments described. It should also be understood that the methods and devices described herein can be appropriately adjusted and modified according to their applications, and the devices, systems and methods described herein can also be used in other suitable applications, and such other additions and modifications will not deviate from the scope thereof.

[0038] Although various features have been shown in different figures for simplicity, it should be apparent to those skilled in the art that the various features may be combined without departing from the scope of the invention.

[0039] According to certain aspects, a controller associated with a pump augmentation system (PAS) or an insulin pump augmentation system (IPAS) according to the present disclosure can provide improved pump operation or insulin pump operation control schemes, and devices and systems for pumps or insulin pumps.

[0040] For example, the present invention provides an Insulin Pump Augmentation System (IPAS) that uniquely provides a closed loop insulin pump that can learn in real time about the various physiological and / or lifestyle activities that a user is performing in order to dynamically proactively automatically compensate for said activities to better maintain a diabetic patient's (or other person's) blood glucose levels within an "ideal" target range. This proactiveness is very important because mechanical insertion of insulin into the body, whether through a manual injection process or through an insulin pump, does not produce the same immediate blood glucose response to a diabetic patient's blood glucose levels as compared to the effects of a "normal" (non-diabetic) organic solution.

[0041] There is a time lag between changes in blood glucose levels and those changes being subsequently reflected in interstitial fluid readings, so existing "after the fact" insulin delivery responses and corrections for external lifestyle factors often result in undesirable "out of range" situations. While insulin pumps are typically able to provide different preset basal insulin infusion (delivery) rates based on a fixed, predetermined schedule, these infusion rates fail to account for the typical variability of insulin pump users on different schedules.

[0042] For example, the best that current technology can do with the rise in glucose levels that diabetic patients experience upon waking due to the "dawn phenomenon" is static programming to allow for increases in basal insulin delivery within specific pre-set time frames. However, the obvious problem with this approach is that unless the patient fully adheres to a strict schedule corresponding to the expected increase in insulin delivery, this timed increase in insulin delivery level will be inconsistent with the actual glucose level insulin requirement and may result in abnormally low or high blood sugar levels.

[0043] Given the many daily "real world" variations, it is almost impossible to achieve the exact time of falling asleep and the exact time of waking up in order to maintain a consistent sleep schedule to predict the release of hormones. Because currently designed insulin pumps are not equipped to recognize changes in sleep patterns (such as changes between sleeping hours on weekdays and sleeping hours on weekends or holidays), existing treatments have inherent timing issues and cannot respond appropriately to the blood sugar changes of the "dawn phenomenon."

[0044] Similarly, conventional insulin pumps have no way to proactively respond to spontaneous bodily activity, whether in an emergency (such as having to flee for safety during an emergency evacuation) or for recreation (such as spontaneously playing an extra game of tennis or other sport that was not planned), and as a result, even closed-loop insulin pumps can only attempt to passively reduce or suspend insulin delivery after the fact to maintain control.

[0045] Where "traditional" (non-PAS or non-IPAS enabled) "smart watches" or similar devices are capable of generating reports or saving information about total steps or other physical activity, these devices only display prior information such as calories burned and distance traveled, and are not configured to perform automatic responsive actions based on such information to control or modify the insulin pump. In contrast, according to one aspect of the present invention, a controller (e.g., a controller integrated into an IPAS) uses sensory data to automatically determine and provide beneficial changes to the insulin delivery rate of an insulin pump (e.g., increase and / or decrease the insulin delivery rate). The novel use of the insulin pump enhancement system (IPAS) enables a closed-loop insulin pump to have physiological and / or physical condition sensing capabilities for the first time so that the insulin delivery level is better matched to the actual insulin demand of the body, for example, it can be combined with one or more six-axis accelerometer / gyroscope pitch sensors (or accelerometers of other numbers of axes), and its data output can be processed and analyzed in real time by an artificial intelligence software program. IPAS is also very suitable for common problem situations, that is, insulin pump users forget to temporarily suspend the delivery of the insulin pump before and / or during exercise, and / or forget to supplement a large dose of insulin for a carbohydrate load that is expected or has been ingested. Both of the above situations may lead to potentially serious blood sugar excursions, which can be avoided by using IPAS according to embodiments of the present invention.

[0046] For the purposes of the present invention, the term "lifestyle" includes events such as: the individual's current sleep state (e.g., determining whether the individual is awake or asleep); the individual's current state of motion or physical movement (or action state); the individual's current state of food intake (eating, chewing, drinking, etc.); and the individual's real-time identification of specific foods currently being ingested and the total amount of said foods ingested. IPAS provides insulin pumps with enhanced awareness of "lifestyle" situations, enabling closed-loop insulin pumps to monitor and automatically correct physical exertion activities that may change the user's blood sugar level; perform "real-time" monitoring, identification, and insulin compensation for a range of ingested foods; and be able to monitor the individual's sleep / wakefulness state and compensate for changes in the user's blood sugar level caused by hormone release at the end of sleep.

[0047] According to certain aspects, the controller is associated with an insulin pump enhancement system (IPAS). The IPAS can be configured as different physical embodiments, three exemplary embodiments of which include:

[0048] 1) The IPAS components are fully integrated into the IPAS-enabled insulin pump body. Data from the pump's integrated IPAS sensors are processed by the relevant artificial intelligence subsystem within IPAS, and derived guidance is provided to the insulin pump's delivery system (or the controller of the insulin pump's delivery system) for action to be taken.

[0049] 2) The configuration of embodiment #1, further enhanced by the additional use of a second, effectively independent six-axis accelerometer and gyro pitch sensor, and a microphone integrated into a wrist-worn device, which is placed on the arm or wrist (preferably the dominant arm or wrist) of the insulin pump user, either as an IPAS-enabled smartwatch or as a dedicated IPAS wearable device. The data output from these additional sensors is transmitted to the IPAS-equipped insulin pump (e.g., via wireless communication means), where the additional data streams are combined with the data provided by the sensors integrated with the pump, and the two data streams are then processed by the artificial intelligence subsystem within the insulin pump.

[0050] 3) Configuration for non-IPAS closed-loop insulin pumps. In this configuration, all IPAS sensing elements and IPAS data processing functions are actually integrated into the body of a "smart watch" or other IPAS wearable device, which is worn on the wrist or arm of the insulin pump user (e.g., the dominant wrist or arm). Built-in six-axis accelerometer and gyroscope pitch sensor, as well as microphones are used as input devices. In this embodiment, the IPAS-enabled arm-worn device itself calculates supplemental insulin and / or modifies delivery instructions, and then wirelessly transmits the instructions to a "traditional" insulin pump, i.e., an insulin pump not equipped with IPAS, for execution. The insulin pump also transmits "real-time" parameters, such as blood glucose levels and circulating insulin, to the IPAS device.

[0051] In the first example of sensing a newfound lifestyle and communicating it to the insulin pump, the enhanced pump is now able to dynamically determine the user's sleep or wake state and proactively make compensatory adjustments to the insulin delivery rate to match the estimated hormone release by the body while awake. With this new lifestyle awareness, the glucose-lowering effects of insulin can now be better timed to match the proportional insulin released when IPAS senses the insulin pump user's body's awake state with the blood sugar-raising effects of hormone release while awake.

[0052] According to an embodiment of the present invention, a controller associated with IPAS can determine whether an individual is in a sleeping state or a non-sleeping state based on the individual's body orientation. For example, regardless of whether the individual's body orientation is in a position characteristic of sleep and in a state of reduced movement for a long time, IPAS can similarly identify the individual's body orientation and long-term lack of movement through its six-axis accelerometer and gyroscope pitch sensor, and match this data with a stored template indicating that the individual is in a sleeping state. Conversely, when the controller associated with IPAS detects that the individual changes from a position of a limited movement, long-term sleeping state to an upright position through the detected multi-axis motion, IPAS can also determine the position of the non-sleeping state (or awake state or morning awakening). The IPAS artificial intelligence subsystem can be determined by an algorithm, for example, including time-weighted motion analysis (to prevent temporary awakening from being mistakenly interpreted as morning awakening), and observing the detected range and speed of motion, so as to filter out the typical instantaneous motion and position transfer of individuals in various sleep stages from the actual awake state.

[0053] Because the controller associated with the IPAS has an inherent ability to detect the user's sleep state, the IPAS has the ability to not only advance or delay the time-based pre-programmed basal rate, but also to modify and adjust the fixed / preset basal rate based on actual observed conditions, such as encountering sleep or traveling between time zones. Likewise, according to embodiments of the present invention, the IPAS can temporarily offset the current basal rate to better align with the immediate or predicted near-term body insulin needs.

[0054] IPAS's sleep / wakefulness judgment can also provide key user condition judgments and responses. In the case where the controller associated with an insulin pump equipped with IPAS senses an abnormally low (or too high) blood glucose reading when its user is thought to be sleeping, it can increase the volume of the warning alarm and extend the duration of this alarm to beyond its normal daytime parameters, because waking up a person with a low blood glucose level who is sleeping may be particularly challenging. In some embodiments, if the insulin pump equipped with IPAS does not sense that the user is awake after completing the enhanced alarm program, the controller associated with IPAS is configured to assume that the user has lost consciousness (or no response) and automatically commands a nearby mobile device to call an emergency number for medical help. At the same time, the controller associated with IPAS can cause the insulin pump to automatically suspend insulin delivery. If the individual does not respond and observes an extremely low blood glucose index, IPAS can be configured to automatically suspend insulin delivery and / or deliver an infusion that raises glucose, such as glucagon. In the case of excessively high blood glucose levels, IPAS can be configured to automatically provide an appropriate large dose of insulin to avoid or correct ketosis. For example, a controller associated with IPAS can command a nearby mobile device via Bluetooth wireless communication or similar means. Even though an unconscious person may not be able to speak, a digitized voice message will explain to first responders the nature of the medical emergency and, if location information is not available through the enhanced 911 system, relay the user's location via the mobile device's GPS or other location information technology. Optionally, IPAS can provide first responders with observed blood sugar levels so that first responders can understand and take action more promptly.

[0055] In the second example, a non-IPAS-enabled insulin pump has absolutely no understanding of its user's "moment-by-moment" lifestyle activities and therefore has no ability to proactively deviate from its preset delivery settings. It is well known that physical activity can affect a diabetic patient's blood glucose levels by either lowering or raising them, depending on their blood glucose levels at the time of the exercise. By using an integrated multi-axis accelerometer and pitch sensing sensor (or a standalone auxiliary multi-axis accelerometer and gyroscopic pitch sensor), an insulin pump is able to continuously (or semi-continuously) understand the user's exercise / physical activity and dynamically and proactively adjust the user's insulin delivery rate accordingly, rather than attempting to passively correct for exercise-derived changes in blood glucose levels as conventional insulin pump devices do.

[0056] According to an embodiment of the present invention, IPAS can achieve improvements in glucose readings "within the range" of the user. Changes in exercise or physical activity can now be detected immediately (or almost immediately) so that the user's basal insulin rate can be changed immediately (or nearly immediately) when the exercise begins. Artificial intelligence (AI) logic can be used to analyze the user's current blood sugar level, and to determine the (current) circulating insulin level (provided by the insulin pump) so that the pump can make appropriate insulin adjustments when needed. If the instantaneous circulating insulin level during exercise is considered sufficient, and the detected blood sugar level is within the "normal" range (or within a predetermined range), the controller associated with IPAS can be configured to bias the insulin pump to stop or reduce the insulin delivery basal rate commensurate with the sensed level and exercise time. If at the beginning of exercise, the detected blood sugar level is much higher than the normal level (or higher than a predetermined threshold) and / or the circulating insulin level is low (or lower than a predetermined threshold), the controller associated with IPAS can be configured to cause the insulin pump to provide a large dose of insulin and / or increase its basal rate to compensate for exercise to prevent further increases in blood sugar levels caused by exercise.

[0057] The determination of exercise or other strenuous activity (e.g., playing tennis) can be made by an artificial intelligence motion algorithm, which can make a determination based on how many axes initiate reported motion exceeding a predetermined motion threshold level, the range of axis excursions in the reported motion, and any repetitive rhythmic patterns (to detect running or other specific activities). The algorithm can be designed to filter out "false" motion reporting situations, such as when an individual is riding in a car (repetitive up and down) so as not to confuse the vertical up and down "bounce" with vertical motion that may be associated with running. The motion algorithm will notice that while vertical motion (and possibly other motion) is present, its excursion distance is limited compared to the expected excursion distance for exercise, and there is a lack of forward motion and other axis readings, and the rhythmic pattern is also very different.

[0058] The Insulin Pump Augmentation System (IPAS) is not limited to the lifestyle examples described herein. Conventional insulin pumps have no means of directly sensing lifestyle, and due to this deficiency, the pump is completely unaware of the user's food intake. Since there is no "real time" method to sense the ingested carbohydrate load, conventional closed loop pumps cannot sense the ingested food, but only indirectly and passively sense that the user's blood glucose level is rising toward or has exceeded the target range or rate, and then initiate corrective measures. Even in the case of an insulin pump user manually injecting a bolus of insulin before eating, such action is only a guess as to how much carbohydrates may or may not be subsequently consumed.

[0059] Through the present invention, an insulin pump equipped with IPAS can not only obtain real-time information representing food intake simultaneously, but in many cases, it can even estimate and provide the pump with accurate food type, actual amount of food ingested, calculated derived ingested carbohydrate load, glycemic index of the food, and compensatory large dose insulin and release timing for the intake. This enables the insulin pump to immediately (or nearly immediately) and simultaneously actively match the supplemental insulin dose to the amount and type of food ingested, while a pump not equipped with IPAS needs to passively compensate for the food intake in an imperfect "after the fact" manner.

[0060] For example, in the case of a person eating popcorn, the dominant hand (or non-dominant hand) wearing the IPAS sensor moves repeatedly in a distinct pattern as it removes food from a fixed "serving container" and delivers the popcorn to its mouth. By analyzing data from one or more six-axis accelerometer sensors and / or one or more gyroscope pitch / yaw / roll sensors during the activity, the unique repetitive pattern enables a controller (e.g., with an incorporated artificial intelligence algorithm) to record the detected arm and hand movements, which can be accurately saved as a template representing that a particular food is being ingested. The controller / artificial intelligence system can not only analyze the repetitive multi-axis position, speed, and rhythm of the movement, but can also generate a digitized audio file from a wrist-mounted microphone when it is determined that the wrist-mounted device is in the closest position to the user's mouth. The audio file can further help the artificial intelligence algorithm distinguish, for example, a person eating popcorn from a person eating potato chips by distinguishing their unique chewing sounds and the duration of the chewing sounds.

[0061] By determining and analyzing the "dwelling" time of the hand at or near the mouth, and the number and type of successive angular movements of the hand and wrist before leaving the mouth, it is possible to further quantitatively determine the food that has been ingested, and by simple calculations of supplementation, the instantaneous carbohydrate intake level for each such movement cycle can be calculated and the compensatory "bolus" insulin can be determined. By infusing insulin close to when ingestion occurs (and at the appropriate compensatory level), and adjusting according to the glycemic index of the identified food, excellent active matching of insulin and carbohydrate load can be achieved.

[0062] The variation of food types is quite extensive. By having individuals "record" the various foods eaten and the data tags of the recorded foods, the controller associated with IPAS according to an embodiment of the present invention can easily match and reference carbohydrate values, glycemic index, calories, etc. to accurately customize the delivery value required by the insulin pump to match the insulin demand and time, thereby compensating for the increase in blood glucose levels caused by the intake of food.

[0063] The body movements and rhythms that are usually associated with eating various foods may be quite unique for certain foods. Examples of this include, but are not limited to: eating corn, eating apples (with a unique "bounce" after each bite), licking an ice cream cone, peeling and eating bananas, etc. Because of the unique body movements when not eating and / or the sounds of eating associated with each food, a series of specialized food templates can be generated and / or pre-stored in a controller associated with IPAS. In addition, by manually inputting the food type into IPAS by the user, such as pressing a button on a wrist-worn device and saying the name of a specific food, carbohydrate and calorie information can be called (or identified) for foods that are difficult to automatically identify based on food templates, and IPAS will monitor the intake to resolve (or determine) carbohydrate load and bolus insulin. For low-carbohydrate foods, such as meat, IPAS can identify the unique movement of meat cutting before ingestion (if the user prepares the food to be ingested).

[0064] Not only the sound characteristics of the actual intake of beverages, but also the sound generated (or lack thereof) by the actual bottle or container may be particularly important for identifying beverages (and their carbohydrate content). For example, disposable plastic water bottles, because they do not need to handle the pressure of carbonation, are usually made of thinner plastic materials than "soda" bottles, so they will generate a unique "plastic bending / crackling" sound when they are taken and drunk. This unique plastic water bottle sound will be used by IPAS to determine that the intake of no calories / zero carbohydrates is taking place. On the contrary, carbonated beverages will use different types of bottles and generate different intake / carbonation sounds. Regarding judging whether a carbonated beverage is a "healthy drink" or an ordinary beverage (its corresponding carbohydrate content is very different), the IPAS algorithm only needs to analyze the user's blood sugar level at the time of intake to make a reasonable distinction. Because the user of IPAS is assumed to be a diabetic, unless the user's blood sugar level is very low at the time of intake (in this case, "ordinary" soda or similar beverages need to be taken), the beverage is always assumed to be a "healthy drink".

[0065] Each food has a unique combination of position and rotational presentation in the mouth when ingested, unique bite patterns and sounds, slurping sounds, chewing noises, hand retraction rotational positioning, etc.

[0066] In some embodiments, the controller associated with the IPAS may not directly identify the type of food based on pre-stored food templates, but rather use a matching process where individual food templates are recorded and saved by the user during intake, and the user then manually identifies and registers each different food. Subsequent food identification can be accomplished by the IPAS automatically comparing active food intake to the saved digitized motion and sound patterns of the saved templates in real time. When matching is performed, carbohydrate levels, glycemic index, caloric information, and other information are provided to the insulin delivery system to determine the amount of insulin to be delivered and the timing of the delivery.

[0067] The algorithm used by the controller associated with the IPAS to determine the type of food ingested may include one or more verification methods to improve accuracy. One of these methods is to allow food audio matching (captured by a wristband device) only when the IPAS motion analysis determines that the user's hand is in a position close to their mouth. By using this "audio gating", the IPAS can prevent erroneous analysis when multiple people eat the same type of food, or eat other types of food near the target IPAS. The audio gating also inherently provides a degree of privacy because the microphone on the wrist is muted as long as the system does not detect that the hand is raised and close to the mouth. Therefore, when the IPAS is determined to be not near the mouth of the IPAS user, the IPAS may not record audio data from the microphone, or if the IPAS is recording audio data, the recorded audio data is ignored.

[0068] In some embodiments, the controller associated with IPAS is configured to initially include some "generic" motion templates to immediately allow recognition of waking, running, or other activities. IPAS is configured to allow users to not only generate and replace the "generic" templates with their own customized personalized templates to further improve event recognition and accuracy, but also to supplement the range of stored templates. Customized personalized templates can also replace the generic motion templates, or be used in addition to them to recognize waking, running, or other activities.

[0069] According to an embodiment of the present invention, another benefit of the controller associated with IPAS is that it plays a role when hypoglycemia attacks. In some cases, individuals usually overcompensate for their carbohydrate intake to treat the immediate symptoms of hypoglycemia. In some embodiments, IPAS is configured to monitor instant blood glucose levels, circulating insulin amounts, and the amount of carbohydrates taken in. The controller associated with IPAS can be configured to provide an "overdose" protection alarm to the user to prevent excessive carbohydrate intake from causing hyperglycemia. By comparing the intake with the instant glucose level and the circulating insulin amount through IPAS, the appropriate amount of carbohydrates required to normalize the user's blood sugar level can be calculated (or judged) by monitoring the instant carbohydrate intake, and an alarm is sounded at the overcompensation point.

[0070] In some embodiments, the controller may be associated with a pump augmentation system (PAS). The PAS may also be used to deliver other infusible drugs or other infusible substances, such as, but not limited to, drugs for treating Parkinson's disease. In this use case, the delivery time and amount of the infused drug may be matched to the immediate need, for example, as determined by an increase in tremor detected by the PAS.

[0071] For purposes of the present invention, although the primary disclosed application is for enhancing insulin pumps, the same or similar hardware configurations, with minor software modifications, may be used for other purposes. In another embodiment of the controller, the automatic food intake sensing may also be used as an "intake" calorie monitor, in contrast to existing devices that only report "burned" calories, rather than ingested. In some embodiments, a controller configured for caloric intake monitoring may be optionally configured to provide tactile or visual alarms or other guidance notifications upon reaching or failing to reach a target caloric intake at a certain time of day.

[0072] The present invention provides a controller associated with a system for sensing and determining "lifestyle" activities.

[0073] According to certain specific embodiments, an insulin pump enhancement system (IPAS) is provided for sensing and determining the "lifestyle" activities of an insulin pump user. Figure 1 As shown, the insulin pump enhancement system 10 according to an embodiment of the present invention is integrated into an insulin pump 100 having a main body 12 and / or is in operative communication therewith. The IPAS 10 includes: a controller 14, an accelerometer sensor 16, a gyro pitch sensor 18, an indication transmitting device 20, and a transmitter 22. The accelerometer sensor may be a multi-axis accelerometer sensor, such as a six-axis accelerometer sensor.

[0074] The controller 14 is operably connected to the six-axis accelerometer sensor 16, the gyro pitch sensor 18, the pointer transmitting device 20, and the transmitter 22. Although the controller 14 is shown as being physically connected to the six-axis accelerometer sensor 16, the gyro pitch sensor 18, the pointer transmitting device 20, and the transmitter 22, the controller 14 can also be "connected" to these elements through wireless communication methods and connections.

[0075] The six-axis accelerometer sensor 16 is configured to detect motion (or movement) and output motion data (or movement data). The controller 14 is configured to receive and / or record or store motion data from the six-axis accelerometer sensor 16. The gyro pitch sensor 18 is configured to detect direction and output direction data. The controller 14 is configured to receive and / or record direction data from the gyro pitch sensor 18. The indication transmitting device 20 is configured to transmit one or more sounds (e.g., alarm sounds) at various sound levels and / or display one or more visual indicators (e.g., flashing lights). The controller 14 is operably connected to the indication transmitting device 20. The transmitter 22 is configured to communicate with one or more communication devices.

[0076] The controller 14 is configured to communicate with the insulin pump 100 and receive various insulin pump 100 data. For example and without limitation, the controller 14 may receive circulating insulin level data of a user of the insulin pump 100, reported blood glucose level data of a user of the insulin pump 100, and / or current or scheduled insulin delivery rate data of the insulin pump 100. The controller 14 is operably connected to the insulin pump 100. The controller 14 is also operably connected to the transmitter 22 so that the transmitter 22 triggers an automatic emergency call or message when one or more predetermined criteria are met based on the motion data, the directional data, the audio data, the circulating insulin level data, the reported blood glucose level data, and / or the current or scheduled insulin delivery rate data.

[0077] like Figure 2 As shown, IPAS10 is further integrated into the wearable device 24, and / or is in operative communication therewith. In the present embodiment, the wearable device 24 is a wristband device. IPAS10 includes a six-axis accelerometer sensor 25 and a gyroscope pitch sensor 26 located in the wearable device 24. IPAS10 further includes a microphone 28. Microphone 28 is configured to detect audio and output audio data. The controller 14 is configured to receive audio data from the microphone 28, and / or the wearable device 24 includes an additional controller configured to assign motion data, direction data and / or audio data to the controller 14. It should be readily understood that the microphone 28 can be disposed at other locations of the wearable device 24 and / or there can be additional microphones.

[0078] In some embodiments, the controller 14 is disposed in or on the wearable device 24. In some embodiments, the controller 14 is disposed in or on the insulin pump 100, such as Figure 1 As shown, the second controller is disposed in or on the wearable device 24. The second controller is configured to communicate with the controller 14 and / or a dedicated controller of the insulin pump 100.

[0079] refer to Figure 3 , flow chart 30 shows the embodiment of the present invention Figure 1 1. An exemplary method of operating IPAS10 of the present invention. In block 32, the controller 14 monitors the motion data received from one or more six-axis accelerometer sensors 16 and six-axis accelerometer sensors 25 and the direction data received from one or more gyroscope pitch sensors 18 and gyroscope pitch sensors 26. In block 34, the controller 14 determines whether the motion data and / or direction data have changed. If the controller 14 determines that the motion data and / or direction data have not changed, the controller 14 returns to block 32 for monitoring. If the controller 14 determines that the motion data and / or direction data have changed, the controller 14 enters block 36, where the controller 14 analyzes the changes in the motion data and direction data. The controller 14 enters block 38, where the controller 14 compares the similarity of the feature templates stored in IPAS10 for the motion data and direction data that can be time-weighted. If the controller 14 determines that the motion data and / or direction data are not similar to the stored feature templates, the controller 14 returns to block 32 for monitoring. If the controller 14 determines that the motion data and / or direction data are similar to a stored template, the controller 14 determines that the detected motion and direction are related to ingested food and enters the recognition feature template method.

[0080] Reference Figure 4 , flow chart 39 shows an embodiment of the present invention, when the motion data and / or direction data is in block 38 ( Figure 3 ) is judged to be similar to food intake characteristics, Figure 1 The controller 14 enters block 40, where the controller 14 optionally receives a signal from the microphone 28 ( Figure 2 ) audio input 42. The controller 14 compares the similarity of one or more stored food intake templates for corresponding motion data, direction data and / or audio data determined to be simultaneous with food intake over a period of time. If the controller 14 determines that the data is similar to the stored food intake template, the controller enters block 48, which will be discussed in more detail below. If the controller 14 determines that the data is not similar to the stored food intake template, the controller enters block 44 and asks the user to input the type of food being ingested. If no user input is received, the controller 14 returns to block 32 for monitoring. If user input is received, the controller 14 enters block 46 and stores the motion data, direction data and / or audio data as a new food intake template corresponding to the provided input. The new food intake template is stored (e.g., in a memory associated with the controller) for future food intake template comparisons at block 40. The controller 14 then enters block 48.

[0081] At block 48, the controller 14 determines the specific food type identified as representing food that the user is ingesting. The controller 14 proceeds to block 50, where the controller 14 checks the user's reported blood glucose level (e.g., by querying the insulin pump 100). If the reported blood glucose level is greater than or equal to a predetermined threshold (e.g., 100 mg / dl), then at block 52, the controller 14 generates a pump command signal to cause the insulin pump 100 to provide a bolus of insulin to the user based on the ingested (or ingested) carbohydrate load determined by the controller 14, thereby changing the current or scheduled insulin delivery rate of the insulin pump 100. If the reported blood glucose level is less than the predetermined threshold (e.g., 100 mg / dl), then at block 54, the controller 14 checks the circulating insulin level in the user (e.g., by querying the insulin pump 100). If the circulating insulin level is less than the predetermined threshold, then at block 56, the controller 14 generates a pump command signal to provide a bolus of insulin to the user based on the ingested (or ingested) carbohydrate load determined by the controller 14. If the circulating insulin level is above the predetermined threshold, then at block 58, the controller 14 does not generate a pump command signal, or generates a pump command signal that reduces the insulin delivery rate from the current or predetermined insulin delivery rate. The controller 14 then returns to block 32 for monitoring.

[0082] Advantageously, the controller 14 is configured to request and receive input from the user at blocks 44, 46, allowing the controller 14 to repeatedly learn the user's unique physical characteristics and / or mannerisms. The stored patterns are personalized to the user, allowing the controller 14 to more accurately identify food templates (or other templates). The controller 14 can be configured to store any number of templates input by the user, giving the controller 14 the ability to store a virtually unlimited number of user-specific patterns. The ability to store user-specific patterns advantageously allows the controller 14 to "learn" the user's tendencies (or previously entered pattern data) corresponding to food templates (or other templates). For example, a user may tend to generate one or more unique movements, directions, or sounds when engaging in a physical lifestyle activity, which the controller 14, once stored, can recognize as a particular template. Thus, when the user again engages in the lifestyle event, such as eating potato chips in a particular physical manner, the controller 14 is configured to recognize the lifestyle event and accordingly generate a pump command signal as disclosed herein.

[0083] Reference Figure 5 , flow chart 60 shows an embodiment of the present invention, when the motion and / or direction data is in block 38 ( Figure 3 ) is judged to be similar to motion features, Figure 11. The exemplary operation method of IPAS10 of the present invention. In block 62, the controller 14 compares the similarity of motion data and / or direction data with a specific motion feature. In block 64, if the controller 14 determines that the motion data and / or direction data do not correspond to a specific motion feature, the controller 14 returns to block 32 for monitoring. If the controller 14 determines that the data does correspond to a specific motion feature, the controller 14 enters block 66, where the controller 14 checks the reported blood glucose level. If the reported blood glucose level is lower than a first threshold, the controller 14 enters block 68 and generates a pump instruction signal, instructing the insulin pump 100 to suspend insulin delivery or reduce insulin delivery. If the reported blood glucose level is higher than a first threshold but lower than a second threshold (e.g., 250 mg / dl), the controller 14 enters block 70 and checks the circulating insulin level in the user's body. If the circulating insulin level is lower than the first insulin threshold, the controller 14 enters block 72 and maintains the existing insulin delivery rate (or at least does not significantly change the insulin delivery rate). If the circulating insulin level is above the second insulin threshold, the controller will proceed to block 74 and reduce the basal insulin rate. Referring to block 66, if the blood glucose level is greater than the third threshold, the controller 14 will proceed to block 76 and determine to increase the insulin delivery rate and / or bolus insulin commensurate with the specific exercise characteristics, and the controller 14 will generate a pump command signal to cause the insulin pump 100 to deliver the determined commensurate insulin rate or bolus insulin.

[0084] Similar to the above combination Figure 4 In the method discussed, the controller 14 may be configured to require the user to input a motion template to be stored as a corresponding motion feature. In some embodiments, the controller 14 does not need to require the user to input a motion or food template. Even if the controller 14 does not require it, the user can enter the corresponding template. The input template is stored together with the recorded data of IPAS10. In some embodiments, the recorded data stored as a template will correspond to the data recorded by the user within a predetermined amount of time before the template is entered, such as but not limited to 1 minute, 2 minutes or 3 minutes. In some embodiments, the user can select which recorded data is related to the input template. For example, the user can select the amount of time before the template is entered, or the user can select a period of recorded data that occurs earlier in the day, for example, if the user plays tennis from 1 pm to 2 pm, then later that day at 6 pm when the user does not play tennis, the user can choose the time of playing tennis as a tennis motion feature or template to store.

[0085] Reference Figure 6 , flow chart 78 shows an embodiment of the present invention, when the motion and / or direction data is in block 38 ( Figure 3 ) is judged to be similar to sleep characteristics, Figure 180, the controller 14 determines that a sleep state is detected. The controller 14 enters a block 82, where the controller 14 continues to monitor motion data and / or direction data to determine a transition from sleep to wakefulness, which can be based on a time-weighted evaluation of the data. If a transition from sleep to wakefulness is not detected, the controller returns to block 80 to check whether the data is similar to a sleep characteristic, and if in a sleep state, returns to block 82 to determine whether a transition from sleep to wakefulness has occurred. If the controller 14 determines that a transition from sleep to wakefulness has occurred (e.g., by motion data indicating that the user is moving or walking, or direction data indicating that the direction of the IPAS 10 has changed), the controller 14 enters a block 84 to check the user's reported blood glucose level. If the reported blood glucose level is lower than a first threshold, the controller 14 enters a block 86, where the controller 14 determines that a large dose of insulin is not required to compensate for the hormone release associated with the transition to a wakefulness state as discussed herein. If the reported blood glucose level is higher than the second threshold, the controller 14 will enter block 88, where the controller 14 determines to increase the insulin delivery rate and / or provide a large dose of insulin to compensate for the user's hormone release, and then the controller 14 will generate a pump command signal to make the insulin pump 100 release appropriate insulin at an appropriate delivery rate. Then, the controller 14 returns to block 32 for monitoring.

[0086] In some embodiments, IPAS 10 is located entirely in or on insulin pump 100 (eg, Figure 1 In some embodiments, the IPAS 10 is located in or on the insulin pump 100 and in or on the wearable device(s) 24 (eg, Figure 1 and Figure 2 ), and as disclosed herein, the IPAS 10 elements in the wearable device 24 are configured to communicate and operate with the IPAS 10 elements in the insulin pump 100. In some embodiments, the IPAS 10 is completely located in or on the wearable device 24 (e.g. Figure 2 ), and is configured to communicate and work with a non-IPAS insulin pump (i.e., does not have any IPAS functionality itself), wherein the IPAS 10 in the wearable device 24 will supplement or override at least some of the controls of the non-IPAS insulin pump functionality, thereby making the insulin pump operate like an integrated IPAS insulin pump. In some embodiments, the user may wear one or more wearable devices with IPAS 10 elements, such as, but not limited to, a wearable device on each wrist of the user.

[0087] Advantageously, the pump that enables IPAS is configured to provide more advantages than the pump that does not enable IPAS. For example, if there is no IPAS to provide the real-time indication of the user's sleep state for the insulin pump, the traditional insulin pump may generate unnecessary alarms without considering the current situation. For example, some insulin pumps may track the amount of insulin remaining in its reservoir, and the pump may send an alarm indicating the situation at various insulin remaining levels. The result of doing so is that even if the situation is not too serious, the user of the insulin pump is still often awakened to take certain actions, such as changing the reservoir, and it is unwise to do such actions when just awakened in the middle of the night. In certain embodiments, the insulin pump that enables IPAS can judge whether the user is sleeping, and if it is judged that the alarm is only advisory, rather than time or situation critical, the insulin pump that enables IPAS can postpone such alarm and / or notification until the state of the user waking up and / or the alarm becomes time critical.

[0088] The foregoing description of the embodiments of the present invention is for the purpose of illustration and description. It is not intended to be exhaustive or to limit the invention to the disclosed forms. In light of the above disclosure, obvious modifications and variations are possible and should be considered to be within the scope and spirit of the present invention. The described embodiments are intended to best illustrate the principles of the present invention and its practical application, so that those skilled in the art can utilize the present invention in various embodiments and with various modifications as contemplated for the specific use.

Claims

1. An insulin pump enhancement system, characterized in that: include: Device body; an accelerometer sensor disposed in or on the device body and configured to output motion data based on the detected motion; a gyroscopic pitch sensor disposed in or on the device body and configured to output orientation data based on the detected orientation; as well as a controller in communication with the accelerometer sensor and the gyro pitch sensor, the controller configured to receive the motion data and / or the orientation data during a first food intake period and during a second food intake period; wherein the controller is configured to determine the position location of the device body, the speed of the device body, the dwell time of the device body and / or the movement rhythm of the device body occurring during the first food intake period and the second food intake period based on the motion data and / or the direction data; wherein the controller includes a memory and is configured to store in the memory the motion data and the direction data received by the controller during the first food intake period, such that the motion data and / or the direction data received during the first food intake period are associated with a specific food type among a plurality of food types based on manual identification by a user; wherein the controller is configured to associate the motion data and / or the direction data monitored during the second food intake with the specific food type among the plurality of food types based on one or more of the following: a determined position location of the device body, the speed of the device body, the dwell time of the device body, and the rhythm of the device body occurring during the second food intake are determined to match one or more of the following: a determined position location of the device body, the speed of the device body, the dwell time of the device body, and the rhythm of the device body occurring during the first food intake; wherein the controller is configured to generate an estimated ingested carbohydrate load and glycemic index of food ingested during the second food intake period based on the motion data and the specific food type associated with the motion data, the direction data and the specific food type associated with the direction data, and / or the motion data and the direction data and the specific food type associated with the motion data and the direction data; and The controller is configured to generate a pump instruction signal based on the estimated ingested carbohydrate load and the estimated glycemic index, the pump instruction signal including instructions for changing or pausing an insulin delivery rate of the insulin pump and instructions for when to change or suspend the insulin delivery rate.

2. The insulin pump enhancement system according to claim 1, characterized in that: The controller is configured to analyze the motion data and / or the direction data on a time-weighted basis, and is configured to use a data pattern matching algorithm of previously input pattern data to provide a determination of the occurrence of a lifestyle event of the user, and wherein the pump instruction signal is further based on the determined lifestyle event.

3. The insulin pump enhancement system according to claim 2, characterized in that: The controller is configured to receive circulating insulin level data representing a level of insulin circulating in a user's body, and wherein the pump command signal is further based on the circulating insulin level data.

4. The insulin pump enhancement system according to claim 2, characterized in that: The controller is configured to receive blood glucose level data indicative of blood glucose level in a user, and wherein the pump command signal is further based on the blood glucose level data.

5. The insulin pump enhancement system according to claim 2, characterized in that: The controller is configured to receive circulating insulin level data representing the level of insulin circulating in the user's body, and to receive blood glucose level data representing the blood glucose level in the user's body, and wherein the controller is further configured to analyze the circulating insulin level data and the blood glucose level data, and wherein the pump command signal is further based on the analysis of the circulating insulin level data and the blood glucose level data.

6. The insulin pump enhancement system according to claim 5, characterized in that: The controller is configured to analyze the circulating insulin level data and the blood glucose level data for a determined lifestyle event, and wherein the pump command signal is further based on the analysis of the circulating insulin level data and the blood glucose level data for a determined lifestyle event.

7. The insulin pump enhancement system according to claim 1, characterized in that: The controller is configured to analyze the motion data and / or the direction data on a time-weighted basis, and is configured to compare the motion data with one or more predetermined motion data patterns using a data pattern matching algorithm, wherein the controller is configured to determine at least one of a type of food that a user is ingesting, an amount of food that a user is ingesting, and a carbohydrate load that a user is ingesting, wherein the controller is configured to determine a target amount of insulin based on at least one of the determined type of food, the determined amount of food, and the determined carbohydrate load, and wherein the pump command signal of the controller is further based on the determined target amount of insulin.

8. The insulin pump enhancement system according to claim 1, characterized in that: The controller is configured to analyze the motion data and / or the directional data on a time-weighted basis and to utilize a data pattern matching algorithm to provide a determination of an occurring lifestyle event.

9. The insulin pump enhancement system according to claim 2, characterized in that: The instruction to change the insulin delivery rate of the insulin pump is a signal to deliver a bolus of insulin.

10. The insulin pump enhancement system according to claim 1, characterized in that: The controller is configured to store in the memory the motion data and the direction data received by the controller during a lifestyle event of a user such that the motion data and the direction data are associated with a particular lifestyle event type from among a plurality of lifestyle event types.

11. The insulin pump enhancement system according to claim 10, characterized in that: The plurality of lifestyle events include eating, sleeping, waking from a sleeping state, and exercise.

12. The insulin pump enhancement system according to claim 10, characterized in that: The device body is a wearable device configured to be worn by a user.

13. The insulin pump enhancement system according to claim 12, characterized in that: The wearable device is configured to be worn on a limb of a user.

14. The insulin pump enhancement system according to claim 12, characterized in that: The wearable device is configured to be worn on a wrist of a user, the insulin pump enhancement system further comprising a microphone configured to detect audio and output audio data based on the detected audio, wherein the controller is configured to receive the output audio data, and wherein the pump instruction signal is further based on the received output audio data.

15. The insulin pump enhancement system according to claim 14, characterized in that: The controller is configured to store in the memory the audio data received by the controller during food ingestion, wherein the controller is configured to receive input from a user to identify a specific food type of the ingested food when the controller receives the audio data, and wherein the controller is configured to store the received audio data matching the carbohydrate content associated with the specific food type identified by the user's input.

16. The insulin pump enhancement system according to claim 15, characterized in that: The controller is configured to determine a specific food type based on the received and stored audio data.

17. The insulin pump enhancement system according to claim 1, characterized in that: The accelerometer sensor is at least a six-axis accelerometer sensor that provides X / Y / Z direction data, as well as pitch / roll / yaw axis motion.

18. The insulin pump enhancement system according to claim 1, characterized in that: The controller is configured to match a specific food type from a plurality of food types stored in a memory during a second food intake period based on at least one of the motion data, the direction data, and the audio data, and wherein the controller is further configured to generate the pump instruction signal based on the specific food type matched during the second food intake period.

19. The insulin pump enhancement system according to claim 1, characterized in that: The controller is configured to estimate caloric intake by the user and maintain a running caloric count representing a total of caloric intake by the user over a period of time.

20. The insulin pump enhancement system according to claim 1, characterized in that: The controller is configured to estimate an amount of carbohydrates ingested by a user and maintain a running carbohydrate count representing a cumulative total of carbohydrates ingested by the user over a period of time.

21. The insulin pump enhancement system according to claim 19, characterized in that: The controller is configured to generate a signal when the total amount of calories ingested by the user is greater than or equal to a predetermined caloric threshold.

22. The insulin pump enhancement system according to claim 20, characterized in that: The controller is configured to generate a signal when the sum of carbohydrates ingested by the user is greater than or equal to a predetermined carbohydrate threshold.

23. The insulin pump enhancement system according to claim 22, characterized in that: Further included is a communication device that generates an emergency call or message including medical information and / or location information related to the user.

24. The insulin pump enhancement system according to claim 1, characterized in that: Further comprising an indication emitting device configured to emit a sound or generate a vibration motion, wherein the controller is operably connected to the indication emitting device, wherein the controller is configured to increase the sound level and / or the vibration level and / or increase the duration of the sound or vibration when the controller determines that the user does not respond to the sound.

25. The insulin pump enhancement system according to claim 1, characterized in that: The controller is operably connected to the communication device, and wherein the controller is configured to activate the communication device when the controller determines that the user has not responded to a series of escalating sound or vibration movements.

26. A pump enhancement system, characterized in that: include: Device body; an accelerometer sensor disposed in or on the device body and configured to output motion data based on the detected motion; a gyroscopic pitch sensor disposed in or on the device body and configured to output orientation data based on the detected orientation; as well as a controller in communication with the accelerometer sensor and the gyro pitch sensor, the controller configured to receive the motion data and / or the orientation data during a first food intake period and during a second food intake period; wherein the controller is configured to determine the position location of the device body, the speed of the device body, the dwell time of the device body and / or the movement rhythm of the device body based on the motion data and / or the direction data occurring during the first food intake period and the second food intake period; wherein the controller includes a memory and is configured to store in the memory the motion data and the direction data received by the controller during the first food intake period, such that the motion data and / or the direction data received during the first food intake period are associated with a specific food type among a plurality of food types based on manual identification by a user; wherein the controller is configured to associate the motion data and / or the direction data monitored during the second food intake with the specific food type among the plurality of food types based on one or more of the following: a determined position location of the device body, the speed of the device body, the dwell time of the device body, and the rhythm of the device body occurring during the second food intake are determined to match one or more of the following: a determined position location of the device body, the speed of the device body, the dwell time of the device body, and the rhythm of the device body occurring during the first food intake; wherein the controller is configured to generate an estimated ingested carbohydrate load and glycemic index of food ingested during the second food intake period based on the motion data and the specific food type associated with the motion data, the direction data and the specific food type associated with the direction data, and / or the motion data, the direction data and the specific food type associated with the motion data and the direction data; and wherein the controller is configured to generate a pump instruction signal based on the estimated ingested carbohydrate load and the estimated glycemic index, the pump instruction signal including instructions for changing or pausing the substance delivery rate of the pump and instructions when to change or pause the substance delivery rate.

27. The pump enhancement system of claim 26, It is characterized in that in, the controller being configured to store in the memory the motion data and the direction data received by the controller during a lifestyle event of a user such that the motion data and the direction data are associated with a particular lifestyle event type from among a plurality of lifestyle event types; wherein the device body is a wearable device configured to be worn by the user; wherein the wearable device is configured to be worn on a wrist of the user, the pump enhancement system further comprises a microphone configured to detect audio and output audio data based on the detected audio, wherein the controller is configured to receive the output audio data, and wherein the pump instruction signal is further based on the received output audio data; and wherein the controller is configured to store in the memory received audio data received by the controller during food ingestion, wherein the controller is configured to receive input from the user identifying a specific food type of food ingested when the received audio data is received by the controller, and wherein the controller is configured to store the received audio data in association with the specific food type identified by the user's input.

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