Acceleration-based patient weight determination

Abstract

Systems and methods are disclosed for determining a patient weight measure using existing medical device sensors, including receiving acceleration information for a patient, and if a value of the acceleration information exceeds an activity threshold for a measurement window, using the acceleration information to detect patient steps in the measurement window, using the detected patient steps to determine a patient walking rate for the measurement window, determining a patient walking force measure for the measurement window, and using the determined patient walking rate and patient walking force measure to determine the patient weight measure.

Description

[0001] Related applications

[0002] This application claims the benefit of U.S. Patent Application Serial No. 63 / 185,848, filed May 7, 2021, which is incorporated herein by reference in its entirety. Technical Field

[0003] This document generally relates to medical devices including accelerometers, and more specifically to acceleration-based determination of patient weight. Background Technology

[0004] Implantable medical devices (IMDs) (such as heart rhythm management (CRM) devices) can be used to monitor, detect, or treat various cardiac conditions associated with a reduced ability of the heart to adequately deliver blood to the body. In some cases, cardiac conditions may result in rapid, irregular, or inefficient heart contractions. To alleviate one or more of these conditions, various medical devices can be implanted in a patient to monitor cardiac activity or provide electrical stimulation to optimize or control heart contractions.

[0005] Heart failure (HF) is a decline in the heart's ability to deliver enough blood to meet the body's needs. Patients with heart failure typically have an enlarged heart and weakened heart muscle, leading to reduced contractility and poor cardiac output. Typical signs of heart failure include shortness of breath, fatigue, weakness, pulmonary congestion, and edema.

[0006] Sudden or steady weight gain is an indication of fluid retention or accumulation and is often one of the first physical signs of worsening heart failure. Patients with cardiac conditions such as heart failure are typically provided with a scale to monitor their weight. Traditional scales require patient compliance. Measurements taken with a traditional scale (even daily and at the same time) are often difficult to rely on because daily variations in clothing, patient diet, fluid intake, sleep quality, the surface under the scale, possible tilting or falling, etc., can significantly alter an individual's weight measurement. Due to this unreliability, many healthcare providers and patient care facilities have stopped providing scales to patients to save costs.

[0007] However, reliable, cost-effective measurements of patient weight, or sudden or gradual changes in patient weight, still have clinical value. Summary of the Invention

[0008] A system and method for determining a patient's weight measurement using existing medical device sensors are disclosed, comprising: receiving the patient's acceleration information, and using the acceleration information to detect the patient's gait within the measurement window if the value of the acceleration information exceeds an activity threshold within the measurement window, using the detected patient gait to determine the patient's walking rate within the measurement window, determining a patient's walking force measurement for the measurement window, and using the determined patient walking rate and patient walking force measurement to determine the patient's weight measurement.

[0009] Examples of the subject (e.g., implantable medical devices) (e.g., “Example 1”) may include: a signal receiver circuit configured to receive acceleration information of a patient; and an evaluation circuit configured to determine whether the value of the acceleration information exceeds an activity threshold, and in response to the value of the acceleration information exceeding the activity threshold, to use the acceleration information to detect patient steps within a measurement window, and to use the detected patient steps to determine a patient walking rate within the measurement window, and to determine a patient walking force measure for the measurement window, wherein the evaluation circuit is configured to use the determined patient walking rate and the patient walking force measure to determine a patient weight measure.

[0010] In Example 2, the subject of Example 1 can optionally be configured such that the evaluation circuit is configured to: determine patient walking rate and patient walking strength measure for multiple corresponding measurement windows; classify the determined patient walking strength measure into one of the compartment groups based on the determined patient walking rate for the corresponding measurement window; and use the determined patient walking strength measure from one of the compartment groups to determine the patient weight measure.

[0011] In Example 3, any one or more of the topics in Examples 1-2 may optionally be configured such that the evaluation circuit is configured to: determine patient walking rate and patient walking strength measures for multiple corresponding measurement windows over multiple days; determine daily patient walking strength measures for each ward in the ward group, having the determined patient walking strength measures for the corresponding days; and use the determined daily patient walking strength measures from one of the ward groups to determine patient weight measures.

[0012] In Example 4, any one or more of the subjects in Examples 1-3 may optionally be configured such that: the patient weight measure includes changes in patient weight, and the evaluation circuit is configured to determine a measure of change in a determined patient walking strength measure over time for one of the ward groups; and use the determined measure of change to determine changes in patient weight.

[0013] In Example 5, any one or more of the topics in Examples 1-4 may optionally be configured such that the evaluation circuit is configured to: determine intraday changes in patient weight using changes in a determined patient walking strength measure occurring within one day for one of the ward groups; determine short-term changes in patient weight using changes in a determined patient walking strength measure occurring over a first time period including multiple days for one of the ward groups; or determine long-term changes in patient weight using changes in a determined patient walking strength measure occurring over a second time period longer than the first time period for one of the ward groups.

[0014] In Example 6, any one or more of the subjects in Examples 1-5 may optionally be configured such that the evaluation circuit is configured to: classify the determined patient walking force measure into one of the compartment groups based on at least one of the determined patient walking rate for the corresponding measurement window and the time of day and the length of the measurement window; and determine the patient weight measure using the determined patient walking force measure of one of the compartment groups corresponding to at least one of the specified time of day or the specified measurement window length.

[0015] In Example 7, any one or more of the subjects in Examples 1-6 may optionally be configured such that the compartment group corresponds to different patient walking rate ranges and time periods of day, including: a first compartment corresponding to a first patient walking rate range and a first time period of day and a first length of measurement window; and at least one of the following: a second compartment corresponding to a first patient walking rate range and a second time period of day and a second length of measurement window; a third compartment corresponding to a first patient walking rate range and a second time period of day and a first length of measurement window; a fourth compartment corresponding to a second patient walking rate range and a first time period of day and a first length of measurement window; a fifth compartment corresponding to a first patient walking rate range and a second time period of day and a second length of measurement window; or a sixth compartment corresponding to a second patient walking rate range and a first time period of day and a second length of measurement window.

[0016] In Example 8, any one or more of the topics in Examples 1-7 may optionally be configured such that the first patient's walking rate range includes 40 to 60 steps per minute, and the second patient's walking rate range includes 60 to 90 steps per minute, and the first time period of the day includes the morning time period of the day, and the second time period of the day includes the evening time period of the day.

[0017] In Example 9, any one or more of the topics in Examples 1-8 may optionally be configured such that the bins correspond to different patient walking rate ranges, including: a first bin corresponding to a first patient walking rate range; and a second bin corresponding to a second patient walking rate range higher than the first range, and the evaluation circuit is configured to: determine a patient weight measure using determined patient walking force measures of the first bin and the second bin, wherein the priority for determined patient walking force measures of the first bin corresponding to the first patient walking rate range is lower than that for the second patient walking rate range.

[0018] In Example 10, any one or more of the subjects in Examples 1-9 may optionally be configured such that the evaluation circuit is configured to: determine the patient's walking speed within the determined measurement window using the determined patient walking rate within the measurement window; and determine the patient's weight measure using the determined patient walking speed and the patient's walking force measure.

[0019] In Example 11, any one or more of the subjects in Examples 1-10 may optionally be configured such that: the medical device includes an implantable medical device configured to be implanted in a patient, the implantable medical device including an accelerometer sensor configured to sense acceleration information of the patient, and a signal receiver circuit configured to receive acceleration information from the accelerometer sensor.

[0020] In Example 12, any one or more of the subjects in Examples 1-11 may optionally be configured such that: the signal receiver circuit is configured to receive the patient's impedance information, and the evaluation circuit is configured to use the received impedance information and the determined patient weight measure to determine an indication of fluid retention in the patient.

[0021] In Example 13, any one or more of the subjects in Examples 1-12 may optionally be configured such that: the evaluation circuit is configured to receive instructions for patient treatment and to determine the treatment effect using a measure of the patient's weight determined after treatment.

[0022] In Example 14, any one or more of the subjects in Examples 1-13 may optionally be configured such that: the signal receiver circuit is configured to receive the patient's heart sound information, and the evaluation circuit is configured to use the received heart sound information and the determined patient weight measure to determine an indication of heart failure.

[0023] Examples of the subject matter (e.g., methods) (e.g., “Example 15”) may include: receiving acceleration information of a patient; using evaluation circuitry to determine whether the value of the acceleration information exceeds an activity threshold within a measurement window, and in response to the value of the acceleration information exceeding the activity threshold within the measurement window, performing the following operations: using the acceleration information to detect patient steps within the measurement window; using the detected patient steps to determine the patient walking rate within the measurement window; and determining a patient walking force measure for the measurement window; and using evaluation circuitry to determine a patient weight measure by using the determined patient walking rate and the patient walking force measure.

[0024] In Example 16, the subject matter of Example 15 may optionally be configured to include: using evaluation circuitry to determine patient walking rate and patient walking strength measure for multiple corresponding measurement windows, and classifying the determined patient walking strength measure into one of the compartment groups based on the determined patient walking rate for the corresponding measurement window, wherein determining the patient weight measure includes using the determined patient walking strength measure from one of the compartment groups.

[0025] In Example 17, any one or more of the topics in Examples 1-16 may optionally be configured such that: determining patient walking rate and patient walking strength measures includes determining patient walking rate and patient walking strength measures for multiple corresponding measurement windows over multiple days, and includes determining daily patient walking strength measures for each cell in the cell group, having the determined patient walking strength measures for the corresponding days, wherein determining patient weight measures includes using the determined daily patient walking strength measures from one of the cell groups.

[0026] In Example 18, any one or more of the topics in Examples 1-17 may optionally be configured to include: using an evaluation circuit to determine a measure of change in a determined patient walking ability over time for one of the ward groups, wherein determining the patient weight measure includes using the determined measure of change to determine the change in the patient's weight.

[0027] In Example 19, any one or more of the topics in Examples 1-18 may optionally be configured such that: classifying the determined patient walking strength measure includes classifying the determined patient walking strength measure into one of the bin groups based on the determined patient walking rate for the corresponding measurement window and the time of day of the measurement window, and determining the patient weight measure includes using the determined patient walking strength measure from one of the bin groups at the specified time of day.

[0028] In Example 20, any one or more of the topics in Examples 1-19 may optionally be configured such that: the group of compartments corresponds to different patient walking rate ranges, including a first compartment corresponding to a first patient walking rate range and a second compartment corresponding to a second patient walking rate range above the first range, and determining a patient weight measure includes determining a patient weight measure using determined patient walking force measures of the first and second compartments, wherein the priority for determined patient walking force measures of the first compartment corresponding to the first patient walking rate range is lower than that for the second patient walking rate range.

[0029] In Example 21, the subject matter (e.g., system or apparatus) may optionally combine any part or combination of any one or more of Examples 1-20 to include an "apparatus" for performing any part of any one or more functions or methods of Examples 1-20, or at least one "non-transitory machine-readable medium" including instructions that, when executed by a machine, cause the machine to perform any part of any one or more functions or methods of Examples 1-20.

[0030] This summary is intended to provide an overview of the subject matter of this patent application. It is not intended to provide a unique or exhaustive interpretation of this disclosure. The detailed description is included to provide further information regarding this patent application. Other aspects of this disclosure will be apparent to those skilled in the art upon reading and understanding the following detailed description and viewing the accompanying drawings, which form a part of it, and each of the drawings should not be construed as limiting. Attached Figure Description

[0031] In accompanying drawings that are not necessarily drawn to scale, the same numbers may describe similar parts in different views. The same numbers with different letter suffixes may represent different instances of similar parts. The accompanying drawings illustrate various embodiments discussed in this document by way of example and not by way of limitation.

[0032] Figures 1-2 The relationship between patient acceleration information measured at a stable walking speed is shown, with and without additional load-bearing weight.

[0033] Figure 3 The relationship between measured patient acceleration information and patient weight is shown for a number of patients moving at different stable walking speeds.

[0034] Figure 4 An example method for determining a patient's weight measure using patient acceleration information is shown.

[0035] Figure 5 The relationship between daily walking strength values ​​of patients from different wards and daily walking strength values ​​of patients from combined wards over several days is shown.

[0036] Figure 6 An example system for determining a patient's weight measurement is shown.

[0037] Figure 7 An example patient management system and a portion of the environment in which the system can operate are shown.

[0038] Figure 8 A block diagram of an example machine on which any one or more of the techniques discussed herein can be performed is shown. Detailed Implementation

[0039] Implantable and mobile medical devices often include one or more accelerometer sensors and corresponding processing circuitry to determine and monitor patient acceleration information, such as, among others, cardiac vibration information associated with blood flow or motion in the heart or the patient's vascular system (e.g., heart sounds, heart wall motion, etc.), patient body activity or location information (e.g., patient posture, activity, etc.), respiratory information (e.g., respiratory rate, phase, breath sounds, etc.). Among other things, the inventors have recognized that systems and methods for determining patient weight measurements using existing implantable or mobile medical device sensors provide additional functionality to existing sensor systems with little or no additional physical cost. The determined patient weight measurement can be used as an additional clinical measure or as an additional measure in diagnostic algorithms, thereby improving the sensitivity, specificity, confidence, or speed of detection of different patient conditions, determinations, treatment effects, or alarms.

[0040] When a patient walks, they exert a force on the ground. The magnitude of this force is directly related to the patient's mass. Patients with less mass exert relatively less force when walking compared to those with greater mass. Existing implantable or mobile medical device sensors can detect the force exerted by a patient during movement. However, the force exerted during movement varies depending on various environmental and patient factors, including the type and speed of movement, footwear, gait, surface hardness, fluid retention, time of day, whether the patient is carrying additional objects or weight, whether they are moving with physical assistance, or whether they are moving at a deliberately faster or slower pace compared to their normal walking speed.

[0041] The inventors have recognized that, among other things, force measurements can be gated using different criteria to provide a reliable measure of patient weight. In some examples, the determined patient weight measurement can be used to escalate, confirm, validate, or adjust the priority of one or more other patient status determinations or alerts, such as early indications of heart failure, fluid retention, etc., or to determine improved patient status or treatment effectiveness, such as confirming weight loss or return to baseline after administration of diuretics or other heart failure treatments.

[0042] Figure 1 The relationship 100 between patient acceleration information 101 measured in milligalons (mG) at a stable walking speed with and without additional weight 102 is shown. Multiple 12-second force measurements are shown where the patient is not carrying additional weight at 103, the patient is carrying an additional +2.25 kg (approximately 5 lbs) at 104, and the patient is carrying an additional +4.5 kg (approximately 10 lbs) at 105. Figure 1 The first best-fit line 106 for the measured values ​​shown is presented as having a positive correlation (r) of 0.5.

[0043] Figure 2 The relationship 200 between patient acceleration information 201 measured at a stable walking speed with and without additional load 202 is shown. Figure 1 Compared to the number of 12-second force measurements shown in the figure, Figure 2 The number of force measurements over 120 seconds is shown, where the patient did not carry any extra weight at 203A and 203B, the patient carried an extra +2.25 kg (approximately 5 lbs) at 204, and the patient carried an extra +4.5 kg (approximately 10 lbs) at 205. Figure 2 The second best-fit line 206 shown in the figure has a positive correlation (r) of 0.981 with the measured values.

[0044] Figure 3 The diagram illustrates the relationship 300 between measured patient acceleration information 301 (e.g., sensor rectified average (SRA) of 120-second force measurements) and patient weight 302 for multiple patients moving at a walking speed of 1.0 mph (shown using square data points 303A, 303B, etc.) and multiple patients moving at a walking speed of 1.2 mph (shown using circular data points 304A, 304B, etc.). A third best-fit line 306 illustrates the general relationship between the measured force measurements and patient weight. For example, patient weight determination can be estimated along the best-fit line of population data of patients with heart failure or those with implantable or mobile medical devices. In other examples, the population data can be further separated by other factors such as age, average movement speed, or otherwise calibrated using other patient inputs or other indicators of physical speed (e.g., GPS watches, estimates of movement speed from mobile phone data, etc.).

[0045] Force measurements are typically correlated with patient weight. For example, force measurements collected from different patients at different walking speeds on a treadmill from different devices (and different axes of a multi-axis device) show a moderate correlation (r > 0.5) between measured patient acceleration information and patient weight. At different walking speeds, the mean root mean square (RMS) value of 120-second cycle force measurements from a single-axis pulse generator provides a correlation (r) of 0.54 across different patients and speeds. The mean RMS value of 120-second cycle force measurements from a multi-axis insertable cardiac monitor (ICM) provides varying correlations (r) across different axes, with the axis most closely aligned with the patient's vertical axis providing the highest correlation (r) of 0.56.

[0046] In various examples, the same or different accelerometer sensors can be used in overlapping or non-overlapping time periods to identify different patient acceleration information that occurs at different frequencies and has different power, processing, performance, or storage requirements. For example, cardiac acceleration information (such as patient heart sounds or endocardial or cardiac acceleration information) or specific patient breath sounds can occur at different frequencies and require different sampling rates, higher than those for patient exertion or activity information (such as patient posture, body movement, or respiratory rate). Patient exertion information is typically detected at a sampling rate of 50 Hz or lower, while heart sound information is typically detected at a sampling rate of 200 Hz or higher.

[0047] In some examples, a single accelerometer sensor comprising one or more axes (e.g., a single-axis accelerometer, a triaxial accelerometer (e.g., X, Y, and Z axes)) can be gated to require a first sampling rate (e.g., a high sampling rate, such as 200 Hz or higher, etc.) in a first cycle and a different second sampling rate (e.g., a low sampling rate, such as 50 Hz or lower, etc.) in a second cycle that does not overlap with the first cycle, in order to reduce the power consumption of the device. In other examples, different axes of a multi-axis sensor may be sampled at different cycles, different sampling rates, or with different processing (e.g., filtering, signal conditioning, etc.) or storage requirements. In still other examples, implantable or mobile medical devices may include different accelerometer sensors configured to detect different acceleration information of a patient at different cycles, different frequencies, or with different processing or storage requirements. For example, it may be advantageous to use a more rigid sensor to detect physical activity or labor information, which is tuned to sense activity with a higher amplitude and lower frequency response than cardiac acceleration information; however, it may be advantageous to use a sensor with higher sensitivity and sampling frequency (e.g., a microphone, etc.) to detect cardiac acceleration information.

[0048] Increasing the amount of data collected in each measurement generally improves the accuracy of patient weight measurements and determination. Correlating force measurements with measured patient weight, a 12-second force measurement shows an error of approximately 3 lbs, a 60-second force measurement shows an error of approximately 2 lbs, and a 120-second force measurement shows an error of less than 1 lb. Longer measurement cycles (e.g., 120-second cycles, compared to 12-second cycles, etc.) provide better determination of patient weight. Since a change of 2 pounds per day can trigger a patient alarm, longer measurement cycles are preferable for determining patient weight measurements. Combinations of multiple shorter measurement cycles, or combinations of longer and shorter measurement cycles, can reduce measurement error. However, considering other gating criteria (e.g., activity thresholds, walking rate, time of day, location, etc.), the need for longer measurement cycles compared to shorter cycles may reduce the number of individual data measurements available each day, which is a trade-off.

[0049] Patient weight determination and the confidence level of patient weight determination can be determined and provided (e.g.) as a linear or nonlinear combination of measurements with respect to preferred gating criteria. Among other things, preferred gating criteria may include one or more of the following: a relatively long measurement period (e.g., a 120-second period, such as compared to a relatively short measurement period, etc.), a threshold number of measurements, a specified time of day, temperature, activity threshold, walking rate, patient movement speed, location, etc.

[0050] In some examples, measurements that do not meet every preferred criterion can be used to determine patient weight in order to obtain a threshold number of measurements, although this reduces the confidence level of the patient weight determination. The threshold number of measurements can be static (e.g., at least two) or dynamic, such as depending on the change from the expected value. If a single measurement is within the threshold range of the expected value (previous or trending value), additional measurements may not be needed. However, if a measurement exceeds the threshold range (e.g., ±2% of the previous or trending value, ±1% of the previous or trending value, etc.), additional measurements may be required. The confidence level of the determined patient weight measurement can depend on the change from the previous or trending value, the number of consistent and preferred criteria constituting the determined patient weight measurement, etc. In the examples, criteria other than preferred gating criteria can be used to determine confidence, such as consistency or inconsistency with other measurements that are relatively close in time (e.g., from a single continuous activity cycle, within a set time period, such as within an hour, on the same day, etc.), etc.

[0051] In some examples, acceleration information sensed during the same time periods each day (e.g., in the morning, before noon, between noon and 5 p.m., between 5 p.m. and 10 p.m., etc.) can be used to determine patient walking strength measures, such as reducing patient weight changes associated with food or fluid intake at mealtimes. For many patients, their weight is typically lowest in the morning, peaks at mealtimes, reaches its highest point after dinner, and tends to decrease before and shortly after each meal. Measurements can preferably be taken in the morning (when the patient is first active each day) or later in the morning (before lunch). In other examples, different daily patient weight determinations can be performed, such as morning, noon, and evening determinations, to measures such as determining patient weight fluctuations at relative time periods throughout the day, or a combination of different daily patient weight determinations can be used to determine average daily weight. In some examples, for patients with higher intraday weight variability (such as compared to patients with more stable daily baseline weight and smaller intraday variability), the priority of daily or short-term alerts can be reduced.

[0052] Daily patient weight determination can be performed as a linear or non-linear combination of force measurements (e.g., given a larger weight, the measurements meet more gating criteria), and can determine daily variation measures, as well as different short-term measurements (e.g., longer than one day but less than one or two weeks, such as 3 days, 5 days, 1 week, etc.) or long-term measurements (e.g., longer than short-term, such as longer than one week, longer than two weeks, etc.). Alerts, such as indications of fluid accumulation, can be triggered or provided based on daily, short-term, or long-term variations exceeding thresholds.

[0053] Further gating of force measurements increases relevance. While estimates of patient weight can be determined with relatively high confidence levels within a few percent, changes in patient weight detected using differences in force measurements provide higher relevance and confidence, with the highest relevance occurring at measurements taken at the same time and under the same conditions each day, minimizing variations in environment, circumstances, etc. For example, daily walking at approximately the same time each day, wearing the same shoes, at the same speed, and along the same route will provide the highest relevance and accuracy. Such activities are recommended, but as with weighing scales, patient compliance and such measurements are generally unreliable. Furthermore, slower walking speeds (e.g., 1 mph or 1.2 mph, compared to higher walking speeds (e.g., 2 mph, etc.)) provide better determination of patient weight measurements.

[0054] The inventors have recognized that, among other things, repetitive features can be detected to reduce variability in force measurements and improve patient weight determination. In addition to time of day, force measurements can also be gated by activity type, speed, etc. For example, a patient may exert different ground forces when walking up or down stairs or on a ramp or downhill compared to walking on a level surface. However, a patient's walking rate on a level surface is generally different from their walking rate on stairs, ramps, or downhill.

[0055] Patient walking rate can be detected in patient accelerometer information as a repetitive pattern of amplitude variation that has a relatively constant phase of variation throughout the measurement window (e.g., variation less than 30% across the measurement window, etc.) or a threshold amount of the measurement window (e.g., at least 70% of the measurement window, etc.). Walking speed can be determined based on a general relationship with walking rate (e.g., assuming 2500 steps per mile for a patient with heart failure, etc.). Force measurements within a qualifying measurement window can be determined, such as by using the average RMS value or square root of amplitude (SRA) value of steps over the measurement window, the average amplitude, the amplitude of the peak frequency of the measurement window, etc.

[0056] Force measurements can be compartmentalized by walking speed or walking rate, and measurements in a specific compartment can be used to determine a patient's weight measure, or changes in measurements in a specific compartment over time can be used to determine changes in a patient's weight measure. In different examples, different numbers of compartments with different granularities can be used in steps per minute, miles per hour (mph), or one or more other units. For example, compartmentalized by speed, a 1 mph compartment could include a measurement window where the patient's walking speed is determined to be up to 1 mph, a 1.5 mph compartment could include a measurement window between 1 mph and 1.5 mph, a 2 mph compartment could include a measurement window between 1.5 mph and 2 mph, and so on. In other examples, a 1 mph compartment could include a measurement window where the patient's walking speed is determined to be below 1.5 mph, a 2 mph compartment could include a measurement window between 1.5 mph and 2.5 mph, and a 3 mph compartment could include a measurement window above 2.5 mph. In another example, compartments are created based on walking rate (steps per minute). The first compartment might include a measurement window corresponding to a range of the patient's walking rate (e.g., between 40 and 60 steps per minute), the second compartment might include a measurement window corresponding to a second range of the patient's walking rate (e.g., between 60 and 90 steps per minute), and the third compartment might include a measurement window corresponding to a third range of the patient's walking rate (e.g., greater than 90 steps per minute). In other examples, the compartments may be more or less granular, with different, higher, lower, or additional ranges.

[0057] In some examples, walking rate or walking speed can be tracked as an indicator of patient health, because a faster walking rate or walking speed is generally associated with a better patient condition, where an increased walking rate or walking speed indicates an improved patient condition, while a decreased walking rate or walking speed indicates a worsening patient condition.

[0058] Figure 4 An example method 400 for determining a patient weight measure using patient acceleration information is illustrated. At 401, acceleration information can be received, such as using a signal receiver circuit. In the example, an accelerometer sensor from an implantable medical device can be used to sense the acceleration information. In some examples, one or both of the accelerometer sensor or the signal receiver circuit may include one or more analog or digital signal processing circuits, such as filters, rectifiers, integrators, etc., configured to modulate the sensed acceleration information and, in some examples, determine one or more values ​​or measures of the acceleration information. In other examples, evaluation circuitry may receive acceleration information from the signal receiver circuitry, determine a value of the acceleration information, and then compare the determined value to a threshold. This value may include an amplitude or energy measure of the acceleration information representing the patient's level of motion, such as the rate or frequency of a peak across a measurement window, the energy value of the measurement window (e.g., an integral measure, RMS value, SRA value, etc.).

[0059] At 402, the value of the acceleration information can be compared to a threshold (such as an activity threshold representing walking or below-walking activity levels) to quickly filter out periods of low or no activity, for example, using an evaluation circuit. In the example, the measurement window can be a static length or variable that depends on the acceleration information (e.g., remaining above a threshold, etc.). In the example, longer or shorter measurement periods described herein can include a single measurement window, a portion of a measurement window, a combination of consecutive full or partial measurement windows, etc. If the value of the acceleration parameter does not exceed the threshold, the method returns to 401. If the value of the acceleration parameter exceeds the threshold, the method continues.

[0060] At 403, an evaluation circuit can be used to detect patient steps in the acceleration information within the measurement window. In this example, among other things, the evaluation circuit can detect steps using one or more of the following: the frequency or amplitude of peaks in the acceleration information, the shape of the acceleration information, the repetition pattern of amplitude changes, etc. If no patient steps are detected in the measurement window, the method returns to 401. If patient steps are detected in the measurement window, such as a number of steps exceeding a threshold, or passing through a threshold portion of the measurement window (e.g., at least 70% of the measurement window, etc.), the method continues.

[0061] At 404, the patient's walking rate within the measurement window can be determined, for example, by using an evaluation circuit to count the detected steps within the measurement window. In the example, the evaluation circuit can cause the measurement window to be unexpectedly trapped to include only the portion of the acceleration information containing detected steps. In other examples, the evaluation circuit can correct for missed steps, such as identifying patterns that are likely to be omitted (e.g., identifying patterns in the patient's step set or in right / left step variations) but were not detected, excessive noise, or other motions.

[0062] In some examples, the evaluation circuitry can be configured to determine the patient's walking speed using a determined walking rate. For example, the determined walking rate may be population-related or a patient-specific relationship between the determined walking rate (for patients with heart failure or those with implantable or mobile medical devices) and the patient's walking speed. In other examples, the patient's walking rate can be used instead of the determined walking speed.

[0063] At 405, a measure of patient walking force for the measurement window can be determined, such as other measures of force using RMS, SRA, mean peak amplitude, or by using acceleration information from an evaluation circuit on the measurement window. In the example, the patient walking force measure can be the same as or different from the value of the acceleration parameter used to determine patient activity above a threshold at 402. For example, the patient walking force measure at 405 can be...

[0064] At point 406, the evaluation circuitry can compartmentate patient gait strength measures into different data sets based on one or more of the following: walking rate, walking speed, length of the measurement window, time of day (e.g., morning, afternoon, evening, or a more specific time of day), value of the acceleration parameter, etc. In some examples, different compartments may represent different gating criteria. For example, a compartment representing a preferred gating criterion may be used to determine a daily value for the patient's gait strength, and other criteria may be added or supplemented if the preferred gating criterion is absent, less pronounced, or otherwise variable or different from the expected value. The patient's gait strength measures and the corresponding information associated with one or more different compartments can be stored in memory by the evaluation circuitry.

[0065] At 407, a patient weight measure can be determined, such as by using a group-related patient gait strength measure or a patient-specific relationship between the patient gait strength measure and the patient's weight. In the example, the evaluation circuitry can select a patient gait strength measure from a specific cell based on received or predefined preferred gating criteria, and use the patient gait strength measure from the specific cell to determine a patient weight measure, as described elsewhere herein.

[0066] At point 408, an evaluation circuit can be used to determine or verify indicators of fluid retention, such as a function of a determined measure of patient weight. In some examples, the evaluation circuit can use physiological information of the patient, such as impedance, pressure, heart sounds, respiration, activity, or other physiological information of the patient, to determine one or more indicators of fluid retention. The determined measure of patient weight can be used to confirm or otherwise improve the confidence or accuracy of the determined indicators of fluid retention.

[0067] At 409, an assessment circuit can be used to determine or verify indications of heart failure, such as by a function of a determined measure of patient weight. In some examples, the assessment circuit can use physiological information of the patient, such as impedance, pressure, heart sounds, respiration, activity, or other physiological information of the patient, to determine a composite heart failure risk score, as described in one or more of the following jointly assigned applications: U.S. Application Serial No. 14 / 510392 entitled “Methods and apparatus for detecting heart failure decompensation event and stratifying the risk of the same” by Qi An et al.; U.S. Application Serial No. 14 / 282353 entitled “Methods and apparatus for stratifying risk of heart failure decompensation” by Robert. J. Sweeney et al.; and U.S. Application No. 13 / 726786 entitled “Risk stratification based heart failure detection algorithm” by Qi An et al., each of which is incorporated herein by reference in its entirety.

[0068] The Composite Heart Failure Risk Score can detect early indications of heart failure before a patient presents with physical symptoms, in some cases 30 to 60 days before the patient's condition deteriorates to the point requiring intervention. Patient condition often fluctuates, and the time intervals between thresholds for heart failure detection scores can reduce caregivers' sensitivity to slowly deteriorating patient conditions. In contrast, sudden or short-term weight gain, such as 2 lbs in 24 hours or 5 lbs in a week, is a more immediate precursor to intervention or hospitalization (e.g., 3 to 7 days, compared to 30 to 60 days). Therefore, in the absence of additional patient compliance issues, a combination of two measures from a single implantable or mobile medical device with a single sensor set—the Composite Heart Failure Risk Score combined with an identified measure of patient weight—can be clinically meaningful.

[0069] At point 410, treatment effectiveness can be determined, for example, by using changes in a determined measure of patient weight. In the example, the measure of treatment effectiveness can be determined from a period of time prior to the effect request (e.g., current change compared to the previous day, short-term trends, etc.). In other examples, the assessment circuit can receive the time when treatment was provided to the patient and use changes in a determined measure of patient weight after the time when treatment was provided to determine the measure of treatment effectiveness. The determined treatment effectiveness can provide an indication that the treatment provided is effective (such as an early indication in response to heart failure) and an indication of whether more or less treatment should be provided in response to current or future indications.

[0070] Figure 5 The diagram illustrates the relationship 500 between daily values ​​of patient walking ability from different first compartments (BIN1) 501 and second compartments (BIN2) 502 and a combined daily value 503 of patient walking ability over several days 504. As described above, the evaluation circuitry can apply preferred gating criteria to the determined patient walking ability measure. In this example, the first compartment 501 is superior to the second compartment 502, resulting in a combined daily value 503 of patient walking ability providing a trend 506 of values ​​from the first compartment 501 on days 1 through 3 and from the second compartment 502 on days 4 and 5 (where there are no values ​​from the first compartment 501 here). In other examples, other combinations of values ​​from different compartments can be used to determine the combined daily value.

[0071] Figure 6 An example system 600 for determining a patient's weight measurement is illustrated, such as a medical device system, a heart rhythm management (CRM) device, etc. In the example, one or more aspects of the example system 600 may be a component or communication coupled to a mobile medical device (AMD), a pluggable cardiac monitor, etc. The system 600 may be configured to monitor, detect, or treat various physiological conditions of the body, such as cardiac conditions associated with a reduced ability of the heart to adequately deliver blood to the body, including heart failure, arrhythmias, asynchrony, etc., or one or more other physiological conditions, and in some examples, may be configured to provide electrical stimulation or one or more other therapies or treatments to the patient.

[0072] System 600 may include a single or multiple medical devices implanted in or otherwise positioned on or around a patient to monitor the patient’s physiological information using one or more sensors, such as sensor 601. In the example, sensor 601 may include one or more of the following: a respiratory sensor configured to receive respiratory information (e.g., respiratory rate, respiratory volume (tidal volume), etc.); an acceleration sensor (e.g., accelerometer, microphone, etc.) configured to receive cardiac acceleration information (e.g., cardiac vibration information, pressure waveform information, heart sound information, endocardial acceleration information, acceleration information, activity information, posture information, etc.); an impedance sensor configured to receive impedance information (e.g., intrathoracic impedance sensor, transthoracic impedance sensor, etc.); a cardiac sensor configured to receive electrocardiogram information; an activity sensor configured to receive information about body movement (e.g., activity, gait, etc.); a posture sensor configured to receive posture or position information; a pressure sensor configured to receive pressure information; a volumetric sensor (e.g., photoplethysmography sensor, etc.); a chemical sensor (e.g., electrolyte sensor, pH sensor, anion gap sensor, etc.); a temperature sensor; a skin elasticity sensor; or one or more other sensors configured to receive physiological information of a patient.

[0073] Example system 600 may include signal receiver circuitry 602 and evaluation circuitry 603. Signal receiver circuitry 602 may be configured to receive physiological information from a patient (or patient group) from sensor 601. Evaluation circuitry 603 may be configured to receive information from signal receiver circuitry 602 and use the received physiological information (such as that described herein) to determine one or more parameters (e.g., physiological parameters, stratification, etc.) or existing or changing patient conditions (e.g., indications of patient dehydration, respiratory status, cardiac status (e.g., heart failure, arrhythmia), sleep apnea, etc.). Among other things, physiological information may include cardiac electrical information, impedance information, respiratory information, heart sound information, activity information, posture information, temperature information, or one or more other types of physiological information.

[0074] Evaluation circuit 603 can be configured to provide output to a user, such as to a display or one or more other user interfaces, including scores, trends, alarms, or other indications. In other examples, evaluation circuit 603 can be configured to provide output to another circuit, machine, or process, such as treatment circuit 604 (e.g., cardiac resynchronization therapy (CRT) circuit, chemotherapy circuit, etc.), to control, adjust, or stop treatment by a medical device, drug delivery system, etc., or otherwise alter one or more processes or functions of one or more other aspects of a medical device system, such as one or more cardiac resynchronization therapy parameters, drug delivery, dosing determination, or recommendations. In examples, treatment circuit 604 may include one or more of stimulation control circuitry, cardiac stimulation circuitry, neural stimulation circuitry, dosing determination, or control circuitry. In other examples, treatment circuit 604 may be controlled by evaluation circuit 603 or one or more other circuits.

[0075] Traditional heart rhythm management devices, such as insertable cardiac monitors, pacemakers, defibrillators, or cardiac resynchronizers, include implantable or subcutaneous devices with a sealed housing configured for implantation in a patient's chest. Heart rhythm management devices may include one or more leads to position one or more electrodes or other sensors at various locations within or near the heart, such as in one or more atria or ventricles of the heart, etc. Thus, heart rhythm management devices may include a subcutaneous aspect (albeit close to the patient's distal skin) and an aspect located near one or more organs of the patient (such as leads or electrodes). Separately from or in addition to the one or more electrodes or other sensors in the leads, heart rhythm management devices may include one or more electrodes or other sensors (e.g., pressure sensors, accelerometers, gyroscopes, microphones, etc.) powered by a power source within the heart rhythm management device. The one or more electrodes or other sensors in the leads, the heart rhythm management device, or combinations thereof may be configured to detect physiological information from the patient or to provide the patient with one or more treatments or stimulations.

[0076] Implantable devices may additionally or separately include leadless pacemakers (LCPs), small (e.g., smaller than conventional implantable rhythm management devices, having a volume of about 1 cc in some examples, etc.) standalone devices comprising one or more sensors, circuitry, or electrodes configured to monitor physiological information from the heart (e.g., heart rate, etc.), detect physiological conditions associated with the heart (e.g., tachycardia), or provide one or more treatments or stimulations to the heart without the complications of conventional leaded or implantable rhythm management devices (e.g., required incisions and pockets, complications associated with lead placement, breakage, or migration, etc.). In some examples, leadless pacemakers may have more limited power and processing capabilities than conventional rhythm management devices; however, multiple leadless pacemakers may be implanted within or around the heart to detect physiological information from one or more chambers of the heart, or to provide one or more treatments or stimulations to one or more chambers of the heart. Multiple leadless pacemakers may communicate with each other or with one or more other implantable or external devices.

[0077] Figure 7 An example patient management system 700 and a portion of the environment in which the patient management system 700 may operate are illustrated. The patient management system 700 can perform a range of activities, including remote patient monitoring and diagnosis of disease conditions. Such activities can be performed near the patient 701, such as in the patient's home or office, via a centralized server, such as in a hospital, clinic, or doctor's office, or via a remote workstation, such as a secure wireless mobile computing device.

[0078] The patient management system 700 may include one or more mobile medical devices, an external system 705, and a communication link 711 providing communication between the one or more mobile medical devices and the external system 705. The one or more mobile medical devices may include an implantable medical device (IMD) 702, a wearable medical device 703, or one or more other implantable, leadless, subcutaneous, external, wearable, or mobile medical devices configured to monitor, sense, or detect information from a patient 701, determine physiological information about the patient 701, or provide one or more treatments to treat various conditions of the patient 701, such as one or more cardiac or non-cardiac conditions (e.g., dehydration, sleep apnea, etc.).

[0079] In one example, the implantable medical device 702 may include one or more conventional cardiac rhythm management devices implanted in the chest of a patient, having a lead system including one or more transvenous, subcutaneous, or non-invasive leads or catheters to position one or more electrodes or other sensors (e.g., heart sound sensors) within, on, or around the heart of the patient 701, or in one or more other locations in the chest, abdomen, or neck. In another example, the implantable medical device 702 may include, for example, a monitor subcutaneously implanted in the chest of the patient 701. The implantable medical device 702 includes a housing containing circuitry and, in some examples, includes one or more sensors, such as temperature sensors.

[0080] The implantable medical device 702 may include assessment circuitry configured to detect or determine specific physiological information of the patient 701, or to determine one or more conditions, or to provide information or alerts to users such as the patient 701 (e.g., a patient), a clinician, or one or more other caregivers or processes. The implantable medical device 702 may alternatively or additionally be configured as a therapeutic device, configured to treat one or more medical conditions of the patient 701. Treatment may be delivered to the patient 701 via a lead system and associated electrodes or using one or more other delivery mechanisms. Treatment may include delivering one or more medications to the patient 701, such as using the implantable medical device 702 or one or more other mobile medical devices. In some examples, treatment may include cardiac resynchronization therapy to correct asynchrony in patients with heart failure and to improve their cardiac function. In other examples, the implantable medical device 702 may include a drug delivery system, such as a drug infusion pump, to deliver medication to the patient for managing arrhythmias or complications arising from arrhythmias, hypertension, or one or more other physiological conditions. In other examples, the implantable medical device 702 may include one or more electrodes configured to stimulate the patient’s nervous system or to provide stimulation to the muscles of the patient’s airway, etc.

[0081] Wearable medical device 703 may include one or more wearable or external medical sensors or devices (e.g., automated external defibrillator (AED), Holter monitor, patch-based device, smartwatch, smart accessory, wrist or finger-worn medical device, such as finger-based photoplethysmography sensor, etc.).

[0082] External system 705 may include dedicated hardware / software systems, such as a programmer, a remote server-based patient management system, or alternatively, a software-defined system primarily running on a standard personal computer. External system 705 may manage patient 701 via implantable medical device 702 or one or more other mobile medical devices connected to external system 705 via communication link 711. In other examples, implantable medical device 702 may be connected to wearable medical device 703 via communication link 711, or wearable device 703 may be connected to external system 705. This may include, for example, programming implantable medical device 702 to perform one or more of the following: acquiring physiological data, performing at least one self-diagnostic test (such as for device operating status), analyzing physiological data, or optionally delivering or adjusting treatment for patient 701. Furthermore, external system 705 may send or receive information to or from implantable medical device 702 or wearable medical device 703 via communication link 711. Examples of information may include: real-time or stored physiological data from patient 701; diagnostic data, such as detection of patient hydration status, hospitalization, and response to treatment delivered to patient 701; or device operational status (e.g., battery status, lead impedance, etc.) of implantable medical device 702 or wearable medical device 703. Communication link 711 may be an inductive telemetry link, a capacitive telemetry link, or a radio frequency (RF) telemetry link, or wireless telemetry based on standards such as “Strong” Bluetooth or IEEE 802.11 Wireless Fidelity “Wi-Fi” interface standards. Other configurations and combinations of patient data source interfaces are also possible.

[0083] External system 705 may include an external device 706 located near one or more mobile medical devices, and a remote device 708 located relatively far from the one or more mobile medical devices, communicating with external device 706 via communication network 707. Examples of external device 706 may include a medical device programmer. Remote device 708 may be configured to evaluate collected patient or patient information and provide alarm notifications, among other possible functions. In an example, remote device 708 may include a centralized server acting as a central hub for storing and analyzing the collected data. The server may be configured as a single, multiple, or distributed computing and processing system. Remote device 708 may receive data from multiple patients. This data may be collected by one or more mobile medical devices and other data acquisition sensors or devices associated with patient 701. The server may include storage devices to store data in a patient database. The server may include alarm analyzer circuitry to evaluate the collected data to determine whether specific alarm conditions are met. The fulfillment of alarm conditions may trigger the generation of alarm notifications, for example, provided by one or more human-perceptible user interfaces. In some examples, alert conditions may be alternatively or additionally evaluated by one or more mobile medical devices, such as implantable medical devices. By way of example, alert notifications may include web page updates, telephone or pager calls, emails, SMS, text or "instant" messages, as well as messages to patients and direct notifications to both emergency services and clinicians. Other alert notifications are also possible. The server may include alert priority ordering circuitry configured to prioritize alert notifications. For example, alerts for detected medical events may be prioritized using a similarity metric between physiological data associated with a detected medical event and physiological data associated with historical alerts.

[0084] Remote device 708 may additionally include one or more locally configured clients or remote clients securely connected to the server via communication network 707. Examples of clients may include personal desktop computers, laptops, mobile devices, or other computing devices. System users, such as clinicians or other qualified medical professionals, can use the clients to securely access stored patient data assembled in a database on the server, and select and prioritize patients and alerts for healthcare provisioning. In addition to generating alert notifications, remote device 708, including the server and interconnected clients, can also implement follow-up protocols by sending follow-up requests to one or more mobile medical devices, or by sending messages or other communications as compliance notifications to patients 701 (e.g., patients), clinicians, or authorized third parties.

[0085] The communication network 707 can provide wired or wireless interconnection. In this example, the communication network 707 may be based on the Transmission Control Protocol / Internet Protocol (TCP / IP) network communication specification, although other types or combinations of networking implementations are also possible. Similarly, other network topologies and arrangements are also possible.

[0086] One or more of the external device 706 or remote device 708 may output detected medical events to system users, such as patients or clinicians, or to a process including, for example, an instance of a computer program executable in a microprocessor. In examples, this process may include automatically generating recommendations for antiarrhythmic treatment, or recommendations for further diagnostic tests or treatments. In examples, external device 706 or remote device 708 may include a corresponding display unit for displaying physiological or functional signals, or alarms, alerts, emergency calls, or other forms of warning to signal the detection of an arrhythmia. In some examples, external system 705 may include an external data processor configured to analyze physiological or functional signals received by one or more mobile medical devices and confirm or reject the detection of an arrhythmia. Computationally intensive algorithms, such as machine learning algorithms, may be implemented in the external data processor to retrospectively process data to detect arrhythmias.

[0087] One or more portions of a mobile medical device or external system 705 may be implemented using hardware, software, firmware, or a combination thereof. One or more portions of a mobile medical device or external system 705 may be implemented using dedicated circuitry, which may be constructed or configured to perform one or more functions, or may be implemented using general-purpose circuitry, which may be programmed or otherwise configured to perform one or more functions. Such general-purpose circuitry may include a microprocessor or a portion thereof, a microcontroller or a portion thereof, or programmable logic circuitry, memory circuitry, network interfaces, and various components for interconnecting these components. For example, a "comparator" may, among other things, include an electronic circuit comparator that may be constructed to perform a specific function of comparing two signals, or the comparator may be implemented as part of a general-purpose circuitry that may be driven by code instructing a portion of the general-purpose circuitry to perform a comparison between two signals. A "sensor" may include electronic circuitry configured to receive information and provide an electronic output representing such received information.

[0088] Treatment device 710 can be configured to send or receive information from one or more of a mobile medical device or an external system 705 using a communication link 711. In the example, one or more mobile medical devices, an external device 706, or a remote device 708 can be configured to control one or more parameters of treatment device 710. External system 705 can allow programming of one or more mobile medical devices and can receive information acquired by one or more mobile medical devices regarding one or more signals, such as those received via communication link 711. External system 705 may include a local external implantable medical device programmer. External system 705 may include a remote patient management system that can, for example, monitor patient status from a remote location or adjust one or more treatments.

[0089] Figure 8 A block diagram of an example machine 800 is shown, on which any one or more of the techniques (e.g., methods) discussed herein can be executed. Parts of this description can be applied to the computational framework of one or more medical devices described herein (such as implantable medical devices, external programmers, etc.). Furthermore, as described herein with respect to medical device components, systems, or machines, this may require regulatory compliance that is not possible with general-purpose computers, components, or machines.

[0090] As described herein, examples may include logic or multiple components or mechanisms in machine 800, or those that can be operated by them. A circuit system (e.g., a processing circuit system, an evaluation circuit, etc.) is a collection of circuits implemented in a tangible entity of machine 800, including hardware (e.g., simple circuits, gates, logic, etc.). The components of a circuit system can be flexible over time. A circuit system includes components that can perform specific operations individually or in combination during operation. In the examples, the hardware of the circuit system may be designed immutably to perform specific operations (e.g., hardwired). In the examples, the hardware of the circuit system may include physically connected components (e.g., execution units, transistors, simple circuits, etc.) including physically modified machine-readable media (e.g., magnetic, electrical, movable placement of immutable aggregated particles, etc.) to encode instructions for specific operations. When the physical components are connected, the fundamental electrical characteristics of the hardware components change, for example, from an insulator to a conductor, and vice versa. Instructions enable embedded hardware (e.g., an execution unit or loading mechanism) to create components of the circuit system in the hardware via variable connections to perform portions of specific operations during operation. Therefore, in this example, during device operation, the machine-readable medium element is part of the circuit system or communicatively coupled to other components of the circuit system. In this example, any physical component can be used in more than one component of more than one circuit system. For example, during operation, an execution unit can be used in a first circuit of a first circuit system at one point in time and reused by a second circuit of the first circuit system, or reused by a third circuit of the second circuit system at a different time. The following are additional examples of these components of machine 800.

[0091] In alternative embodiments, machine 800 may operate as a standalone device or may be connected (e.g., networked) to other machines. In a networked deployment, machine 800 may operate as a server machine, a client machine, or both in a server-client network environment. In the example, machine 800 may act as a peer-to-peer (P2P) (or other distributed) network environment. Machine 800 may be a personal computer (PC), tablet PC, set-top box (STB), personal digital assistant (PDA), mobile phone, network device, network router, switch, or bridge, or any machine capable of executing instructions (sequentially or otherwise) specifying the actions to be taken by that machine. Furthermore, while only a single machine is shown, the term "machine" should also be considered to include any collection of machines that independently or jointly execute one or more sets of instructions to implement any one or more methods discussed herein, such as cloud computing, Software as a Service (SaaS), or other computer cluster configurations.

[0092] Machine (e.g., computer system) 800 may include a hardware processor 802 (e.g., a central processing unit (CPU), graphics processing unit (GPU), hardware processor core, or any combination thereof), main memory 804, static memory (e.g., memory or storage for firmware, microcode, basic input / output (BIOS), unified extensible firmware interface (UEFI), etc.) 806, and mass storage 808 (e.g., hard disk drive, tape drive, flash storage, or other block devices), some or all of which may communicate with each other via interconnect (e.g., bus) 830. Machine 800 may also include a display unit 810, an input device 812 (e.g., a keyboard), and a user interface (UI) navigation device 814 (e.g., a mouse). In the example, display unit 810, input device 812, and UI navigation device 814 may be a touchscreen display. Machine 800 may additionally include a signal generation device 818 (e.g., a speaker), a network interface device 820, and one or more sensors 816, such as a global positioning system (GPS) sensor, a compass, an accelerometer, or one or more other sensors. Machine 800 may include an output controller 828, such as a serial (e.g., Universal Serial Bus (USB), parallel, or other wired or wireless (e.g., infrared (IR), near field communication (NFC), etc.) connection, to communicate with or control one or more peripheral devices (e.g., printers, card readers, etc.).

[0093] The registers of the hardware processor 802, main memory 804, static memory 806, or mass storage 808 may be or include a machine-readable medium 822, on which one or more sets of data structures or instructions 824 (e.g., software) embody or be utilized by any one or more of the technologies or functions described herein. During execution of the instructions 824 by the machine 800, the instructions 824 may also reside wholly or at least partially within any register of the hardware processor 802, main memory 804, static memory 806, or mass storage 808. In the example, one or any combination of the hardware processor 802, main memory 804, static memory 806, or mass storage 808 may constitute the machine-readable medium 822. Although the machine-readable medium 822 is shown as a single medium, the term "machine-readable medium" can include a single medium or multiple media (e.g., a centralized or distributed database, and / or associated caches and servers) configured to store one or more instructions 824.

[0094] The term "machine-readable medium" can include any medium capable of storing, encoding, or carrying instructions executable by machine 800 and causing machine 800 to perform any one or more of the techniques disclosed herein, or any medium capable of storing, encoding, or carrying data structures used by or associated with those instructions. Examples of non-limiting machine-readable media can include solid-state memory, optical media, magnetic media, and signals (e.g., radio frequency signals, other photon-based signals, sound signals, etc.). In examples, non-transitory machine-readable media includes machine-readable media having a plurality of particles with invariant (e.g., rest) masses, and thus being a component of matter. Therefore, a non-transitory machine-readable medium is a machine-readable medium that does not include transiently propagating signals. Specific examples of non-transitory machine-readable media can include: non-volatile memory, such as semiconductor memory devices (e.g., electrically programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM)) and flash memory devices; disks, such as internal hard disks and removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks.

[0095] Commands 824 can be further sent or received via network interface device 820 and communication network 826 using a transmission medium, utilizing any of a variety of transport protocols (e.g., Frame Relay, Internet Protocol (IP), Transmission Control Protocol (TCP), User Datagram Protocol (UDP), Hypertext Transfer Protocol (HTTP), etc.). Example communication networks may include local area networks (LANs), wide area networks (WANs), packet data networks (e.g., the Internet), mobile phone networks (e.g., cellular networks), conventional telephone (POTS) networks, and wireless data networks (e.g., referred to as…). The Institute of Electrical and Electronics Engineers (IEEE) 802.11 family of standards, known as The IEEE 802.16 family of standards, the IEEE 802.15.4 family of standards, peer-to-peer (P2P) networks, etc. In the example, network interface device 820 may include one or more physical jacks (e.g., Ethernet, coaxial, or telephone jacks) or one or more antennas to connect to communication network 826. In the example, network interface device 820 may include multiple antennas to perform wireless communication using at least one of single-input multiple-output (SIMO), multiple-input multiple-output (MIMO), or multiple-input single-output (MISO) technologies. The term "transmission medium" should be understood to include any intangible medium capable of storing, encoding, or carrying instructions executable by machine 800, and includes digital or analog communication signals or other intangible media to facilitate communication of such software. The transmission medium is a machine-readable medium.

[0096] Various embodiments are illustrated in the accompanying drawings above. One or more features from one or more of these embodiments can be combined to form other embodiments. The method examples described herein may be at least partially implemented by a machine or computer. Some examples may include a computer-readable or machine-readable medium encoded with instructions operable to configure an electronic device or system to perform the methods described in the examples above. Implementations of this method may include code, such as microcode, assembly language code, high-level language code, or the like. Such code may include computer-readable instructions for performing various methods. The code may form part of a computer program product. Furthermore, the code may be tangibly stored on one or more volatile or non-volatile computer-readable media during execution or at other times.

[0097] The detailed description above is intended to be illustrative and not restrictive. Therefore, the scope of this disclosure should be determined by reference to the appended claims and the full scope of their equivalents.

Claims

1. A medical device comprising: A device for receiving acceleration information from a patient; as well as An evaluation circuit is configured to determine whether the value of the acceleration information exceeds an activity threshold, and to perform the following operations in response to the value of the acceleration information exceeding the activity threshold: The acceleration information is used to detect the patient's gait within the measurement window; and Use the detected patient steps to: Determine the patient's walking rate within the measurement window; and Determine the patient's walking ability measurement for the measurement window. The evaluation circuit is configured to determine the patient's weight measurement using the determined patient walking rate and patient walking strength measurement.

2. The medical device according to claim 1, wherein, The evaluation circuit is configured as follows: Determine patient walking rate and patient walking strength measurements for multiple corresponding measurement windows; Based on the determined patient walking rate for the corresponding measurement window, the determined patient walking force measurement is assigned to one of the compartment groups; and The patient's weight was determined using a patient walking strength measure determined by one of the aforementioned bins.

3. The medical device according to claim 2, wherein, The evaluation circuit is configured as follows: Determine patient walking rate and patient walking strength measurements over multiple days for multiple corresponding measurement windows; For each cell in the cell group, a daily patient walking ability measure is determined, which is based on the patient walking ability measure for the corresponding day. and The patient's weight was determined using the daily patient walking strength measurement identified by one of the aforementioned groups.

4. The medical device according to any one of claims 2 to 3, wherein the patient weight measurement includes changes in patient weight, and in, The evaluation circuit is configured as follows: Determine the change over time of a specific patient walking ability measure for one of the said ward groups; and Use the identified measure of change to determine changes in the patient's weight.

5. The medical device of claim 4, wherein the evaluation circuit is configured to be at least one of the following: The intraday change in patient weight was determined using changes in patient walking ability measurements for one of the cell groups that occurred within a day. Short-term changes in patient weight were determined using changes in patient walking ability measurements identified within a first time period comprising multiple days for one of the said ward groups; or Long-term changes in patient weight were determined using changes in patient walking ability measurements identified for one of the ward groups that occurred during a second time period longer than the first time period.

6. The medical device according to any one of claims 2 to 5, wherein, The evaluation circuit is configured as follows: Based on the determined patient walking rate for the corresponding measurement window and at least one of the time of day and length of the measurement window, the determined patient walking force measurement is assigned to one of the compartment groups; and The patient weight measurement is determined using a patient walking strength measurement that corresponds to at least one of the bin groups corresponding to a specified time of day or the length of a specified measurement window.

7. The medical device of claim 6, wherein the compartments correspond to different patient walking rate ranges and times of day, comprising: The first compartment corresponds to the first patient's walking rate range and the first time period of day and the first length of the measurement window; as well as At least one of the following: The second compartment corresponds to the first patient's walking rate range and the second length of the measurement window during the first time of day; The third compartment corresponds to the first patient's walking rate range and the first length of the second time period of day and the measurement window; The fourth compartment corresponds to the second patient's walking rate range and the first time period of the day and the first length of the measurement window; The fifth compartment corresponds to the first patient's walking rate range and the second time period of the day and the second length of the measurement window; or The sixth compartment corresponds to the second patient's walking rate range and the second length of the first time period of the day and the measurement window.

8. The medical device of claim 7, wherein the first patient walking rate range includes 40 to 60 steps per minute, and the second patient walking rate range includes 60 to 90 steps per minute, and in, The first time period of the day includes the morning period of the day, and the second time period of the day includes the evening period of the day.

9. The medical device according to any one of claims 2 to 6, wherein the compartments correspond to different patient walking rate ranges, comprising: The first compartment corresponds to the first patient's walking rate range; as well as The second compartment corresponds to a second range higher than the walking speed range of the first patient, and The evaluation circuit is configured to determine a patient weight measurement using determined patient walking force measurements from a first compartment and a second compartment, wherein the determined patient walking force measurement from the first compartment, corresponding to a first patient walking rate range, has a lower priority than the determined patient walking force measurement from the second patient walking rate range.

10. The medical device according to any one of claims 1 to 9, wherein, The evaluation circuit is configured as follows: The patient's walking speed within the determined measurement window is used to determine the patient's walking rate within that measurement window; and The patient's weight was determined using the established patient walking speed and patient walking strength measurements.

11. The medical device according to any one of claims 1 to 10, wherein the means for receiving acceleration information of the patient includes a signal receiver circuit configured to receive the acceleration information of the patient.

12. The medical device of claim 11, wherein the medical device comprises an implantable medical device configured to be implanted in the patient. The implantable medical device includes an accelerometer sensor configured to sense the patient's acceleration information. in, The signal receiver circuit is configured to receive acceleration information from the accelerometer sensor.

13. The medical device according to any one of claims 11 to 12, wherein the signal receiver circuit is configured to receive at least one of the patient's impedance information or the patient's heart sound information, and in, The evaluation circuit is configured to use the received impedance information and the determined patient weight measurement to determine an indication of fluid retention in the patient.

14. The medical device according to any one of claims 11 to 13, wherein, The signal receiver circuit is configured to receive the patient's heart sound information, and The assessment circuit is configured to use received heart sound information and determined patient weight measurements to determine an indication of heart failure.

15. A method comprising: Receive the patient's acceleration information; An evaluation circuit is used to determine whether the value of the acceleration information exceeds an activity threshold within the measurement window, and the following operations are performed in response to the value of the acceleration information exceeding the activity threshold within the measurement window: The acceleration information is used to detect the patient's gait within the measurement window; The patient's walking rate within the measurement window is determined using the detected patient steps. and Determine the patient's walking ability measurement for the measurement window; and Using the evaluation circuit, a patient weight measurement is determined by using the determined patient walking rate and the patient walking force measurement.

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