Acceleration-Based Patient Weight Determination

Abstract

A system and method for determining a measurement of patient weight using existing medical device sensors is disclosed, the system and method including receiving patient acceleration information, detecting patient steps within a measurement window using the acceleration information when a value of the acceleration information exceeds an activity threshold over the measurement window, determining a patient step count over the measurement window using the detected patient steps, determining a measurement of patient walking force in the measurement window, and determining a measurement of patient weight using the determined patient step count and the measurement of patient walking force.

Description

[Technical field]

[0001] This specification relates generally to medical devices with accelerometers, and in particular to acceleration-based patient weight determination. This application claims the benefit of U.S. Provisional Patent Application No. 63 / 185,848, filed May 7, 2021, which is incorporated by reference in its entirety. [Background technology]

[0002] Implantable medical devices (IMDs), such as cardiac 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, the cardiac condition can result in rapid, irregular, or inefficient heart contractions, etc. To alleviate one or more of these conditions, various medical devices can be implanted in a patient's body to monitor cardiac activity or provide electrical stimulation to optimize or control heart contractions.

[0003] Heart failure (HF) is the decline in the heart's ability to deliver enough blood to meet the body's needs. Heart failure patients generally have enlarged hearts with weakened myocardium, resulting in reduced contractility and reduced cardiac output of blood. Typical symptoms of heart failure include shortness of breath, fatigue, weakness, pulmonary congestion, edema, etc.

[0004] Sudden or steady weight gain is an indicator of fluid retention or fluid 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 weight scale to monitor their weight. Traditional weight scales require patient compliance. Measurements on traditional weight scales, even when taken at the same time each day, are often difficult to rely on because daily variations in clothing, the patient's diet, fluid intake, sleep quality, the surface under the scale, possible tilt or deviation, etc., can significantly alter an individual's weight measurement. This lack of reliability has led many healthcare providers and patient care facilities to stop providing weight scales to patients in order to save costs.

[0005] However, reliable and cost-effective measurement of a patient's weight, or sudden or gradual changes in a patient's weight, remains of clinical value. Summary of the Invention

[0006] A system and method for determining a measurement of patient weight using existing medical device sensors is disclosed, comprising receiving patient acceleration information, detecting patient walking within a measurement window using the acceleration information if a value of the acceleration information exceeds an activity threshold over the measurement window, determining a patient step count over the measurement window using the detected patient walking, determining a measurement of patient walking force in the measurement window, and determining a measurement of patient weight using the determined patient step count and the measurement of patient walking force.

[0007] One example (e.g., "Example 1") of the subject matter (e.g., an implantable medical device) may include a signal receiving circuit configured to receive acceleration information of a patient, and an evaluation circuit configured to determine whether a value of the acceleration information exceeds an activity threshold, and in response to the value of the acceleration information exceeding an activity threshold, to detect patient steps within a measurement window using the acceleration information, to determine a patient step count over the measurement window using the detected patient steps, and to determine a measure of patient walking force in the measurement window. The evaluation circuit is configured to determine a measure of patient weight using the determined patient step count and the measure of patient walking force.

[0008] In Example 2, the subject matter of Example 1 may be optionally configured such that the evaluation circuit is configured to determine a patient step count and a patient walking force measurement value for a plurality of measurement windows, bin the determined patient walking force measurement value into one of a set of bins corresponding to the determined patient step count in each of the measurement windows, and determine a patient weight measurement value using the determined patient walking force measurement value of one of the set of bins.

[0009] In Example 3, the subject matter of any one or more of Examples 1 to 2 may optionally be configured such that the evaluation circuit is configured to determine patient steps and patient walking force measurements for the multiple measurement windows spanning multiple days, determine a daily measurement of patient walking force in each bin of the set of bins having the determined patient walking force measurements for each of the days, and determine the patient weight measurement using the determined daily measurement of patient walking force for one bin of the set of bins.

[0010] In Example 4, the subject matter of any one or more of Examples 1 to 3 may optionally be configured such that the measurement value of patient weight includes a change in patient weight, and the evaluation circuit is configured to determine a measurement value of change over time in the determined patient walking force measurement value in one bin of the set of bins, and to determine the change in patient weight using the determined measurement value of change.

[0011] In Example 5, the subject matter of any one or more of Examples 1 to 4 may optionally be configured such that the evaluation circuit is configured to determine at least one of: an intra-day change in patient weight using a change in the determined patient walking force measurement in one of the set of bins occurring over a day; a short-term change in patient weight using a change in the determined patient walking force measurement in one of the set of bins occurring over a first time period including a plurality of days; and a long-term change in patient weight using a change in the determined patient walking force measurement in one of the set of bins occurring over a second time period longer than the first time period.

[0012] In Example 6, the subject matter of any one or more of Examples 1 to 5 may be optionally configured such that the evaluation circuit is configured to bin the determined patient walking force measurement into one of the set of bins corresponding to the determined patient step count in each of the measurement windows and at least one of a time of the measurement window and a length of the measurement window, and to determine the patient weight measurement using the determined patient walking force measurement of one of the set of bins corresponding to a particular time and at least one of a particular length of the measurement window.

[0013] In Example 7, the subject matter of any one or more of Examples 1-6 may further include a method for measuring the patient's step count by measuring the patient's step count over a period of time corresponding to different ranges of patient steps and different time periods of a day, the set of bins including at least one of a first bin corresponding to a first range of patient steps, a first time period of a day, and a first length of the measurement window, a second bin, a third bin, a fourth bin, a fifth bin, and a sixth bin, the second bin corresponding to the first range of patient steps, the first time period of a day, and a second length of the measurement window, and a sixth bin corresponding to the first range of patient steps, the first time period of a day, and a second length of the measurement window. The measurement window may optionally be configured to include at least one of: the third bin corresponding to a second time period and the first length of the measurement window; the fourth bin corresponding to a second range of patient steps, the first time period of a day and the first length of the measurement window; the fifth bin corresponding to the first range of patient steps, the second time period of a day and the second length of the measurement window; and the sixth bin corresponding to the second range of patient steps, the first time period of a day and the second length of the measurement window.

[0014] In Example 8, the subject matter of any one or more of Examples 1 to 7 may be optionally configured such that the first range of patient steps includes 40 to 60 steps / minute, the second range of patient steps includes 60 to 90 steps / minute, the first period of a day includes a morning period of a day, and the second period of a day includes an evening period of a day.

[0015] In Example 9, the subject matter of any one or more of Examples 1 to 8 may be optionally configured such that the set of bins corresponds to different ranges of patient steps, the set of bins including a first bin corresponding to a first range of patient steps and a second bin corresponding to a second range of patient steps greater than the first range, and the evaluation circuitry is configured to determine the measurement value of the patient weight using the determined patient walking force measurements for the first and second bins while prioritizing the determined patient walking force measurement of the first bin corresponding to the first range of patient steps less than the second range of patient steps.

[0016] In Example 10, the subject matter of any one or more of Examples 1 to 9 may be optionally configured such that the evaluation circuit is configured to determine a patient walking speed over the measurement window using the determined patient step count over the measurement window, and to determine a measure of the patient weight using the determined patient walking speed and a measure of patient walking force.

[0017] In Example 11, the subject matter of any one or more of Examples 1 to 10 may be optionally configured such that the medical device includes an implantable medical device configured to be implanted within the patient's body, the implantable medical device having an acceleration sensor configured to detect acceleration information of the patient, and the signal receiving circuit is configured to receive the acceleration information from the acceleration sensor.

[0018] In Example 12, the subject matter of any one or more of Examples 1 to 11 may optionally be configured such that the signal receiving circuit is configured to receive patient impedance information, and the evaluation circuit is configured to determine an indication of patient fluid retention using the received impedance information and the determined measurement of patient weight.

[0019] In Example 13, the subject matter of any one or more of Examples 1 to 12 may optionally be configured such that the evaluation circuit is configured to receive an indication of patient treatment and determine treatment efficacy using the determined patient weight measurement after treatment.

[0020] In Example 14, the subject matter of any one or more of Examples 1 to 13 may be optionally configured such that the signal receiving circuit is configured to receive heart sound information of the patient, and the evaluation circuit is configured to determine an indicator of heart failure using the received heart sound information and the determined measurement of the patient's weight.

[0021] One example (e.g., "Example 15") of the subject matter (e.g., a method) may include receiving patient acceleration information; using an evaluation circuit to determine whether a value of the acceleration information exceeds an activity threshold over a measurement window; in response to the value of the acceleration information exceeding the activity threshold over the measurement window, using the acceleration information to detect patient walking within the measurement window, using the detected patient walking to determine a number of patient steps over the measurement window, and determining a measurement of patient walking force in the measurement window; and using the evaluation circuit to determine a measurement of patient weight using the determined number of patient steps and the measurement of patient walking force.

[0022] In Example 16, the subject matter of Example 15 may be optionally configured to include using the evaluation circuit to determine a patient step count and a patient walking force measurement value for a plurality of measurement windows, and binning the determined patient walking force measurement value into one of a set of bins corresponding to the determined patient step count in each of the measurement windows, and determining the patient weight measurement value includes using the determined patient walking force measurement value of one of the set of bins.

[0023] In Example 17, the subject matter of any one or more of Examples 1 to 16 may be optionally configured such that determining the patient step count and patient walking force measurements includes determining patient step count and patient walking force measurements for the multiple measurement windows spanning multiple days, the subject matter includes determining a daily measurement value of patient walking force in each bin of the set of bins having the determined patient walking force measurements for each of the days, and determining the patient weight measurement includes using the determined daily measurement value of patient walking force for one bin of the set of bins.

[0024] In Example 18, the subject matter of any one or more of Examples 1 to 17 may be optionally configured to include using the evaluation circuit to determine a measure of change over time in the determined patient walking force measure in one bin of the set of bins, and determining the measure of patient weight includes determining a change in the patient weight using the determined measure of change.

[0025] In Example 19, the subject matter of any one or more of Examples 1 to 18 may be optionally configured such that binning the determined patient walking force measurement value includes binning the determined patient walking force measurement value into one of the set of bins corresponding to the determined patient step count in each of the measurement windows and a time of the measurement window, and determining the patient weight measurement value includes using the determined patient walking force measurement value of one of the set of bins at the particular time.

[0026] In Example 20, the subject matter of any one or more of Examples 1 to 19 may be optionally configured such that the set of bins corresponds to different ranges of patient steps, the set of bins including a first bin corresponding to a first range of patient steps and a second bin corresponding to a second range of patient steps greater than the first range, and determining the measurement value of the patient weight includes using the determined patient walking force measurements for the first and second bins while prioritizing the determined patient walking force measurement for the first bin corresponding to the first range of patient steps less than the second range of patient steps.

[0027] In Example 21, the subject matter (e.g., a system or apparatus) may include a "means" for performing any one or more of the functions or methods of Examples 1-20, optionally by combining any part or combination of any part of any one or more 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 one or more of the functions or methods of Examples 1-20.

[0028] This summary is intended to provide an overview of the subject matter of this patent application. It is not intended to provide an exclusive or exhaustive description of the disclosure. The detailed description is included to provide further information of this patent application. Other aspects of the disclosure may become apparent to those skilled in the art upon reading and understanding the following detailed description and viewing the drawings that form a part thereof, each of which should not be construed in a limiting sense. [Brief description of the drawings]

[0029] [Figure 1] FIG. 1 illustrates the relationship between measured patient acceleration information with and without added weight at a steady walking speed. [Diagram 2] FIG. 2 illustrates the relationship between measured patient acceleration information with and without added weight at a steady walking speed. [Diagram 3] FIG. 3 is a diagram showing the relationship between measured values ​​of patient acceleration information and measured values ​​of patient weight for a number of patients moving at different stable walking speeds. [Figure 4] FIG. 4 illustrates an exemplary method for determining a measure of patient weight using patient acceleration information. [Diagram 5] FIG. 5 illustrates the relationship between daily values ​​of patient walking force from different bins and combined values ​​of daily values ​​of patient walking force across multiple days. [Figure 6] FIG. 6 illustrates an exemplary system for determining a patient weight measurement. [Figure 7]FIG. 7 is a diagram illustrating an exemplary patient management system and a portion of the environment in which the system may operate. [Figure 8] FIG. 8 is a block diagram of an example machine upon which any one or more of the techniques described herein may be implemented. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0030] The drawings are not necessarily drawn to scale, and in the drawings like numerals may refer to like components in different figures. Like numerals with different subscripts may represent different instances of like components. The drawings illustrate generally, by way of example, but not by way of limitation, various embodiments discussed in the present document.

[0031] Implantable and portable medical devices may often include one or more acceleration sensors and processing circuitry for determining and monitoring patient acceleration information, cardiac vibration information (e.g., heart sounds, cardiac wall motion, etc.) related to blood flow or motion in the heart or patient vasculature, patient physical activity or patient position information (e.g., patient posture, activity, etc.), and respiratory information (e.g., respiratory rate, respiratory phase, respiratory sounds, etc.), among others. The inventors have recognized systems and methods that use sensors in existing implantable or portable medical devices to determine a patient weight measurement, among others, providing additional functionality to existing sensor systems with little or no additional physical cost. The determined patient weight measurement may be used as an additional clinical measurement or as an additional measurement in a diagnostic algorithm to improve the sensitivity, specificity, reliability, and speed of detection, determination, treatment efficacy, or alerting of different patient conditions.

[0032] A patient exerts a force on the ground as he or she walks. The magnitude of the applied ground force is directly related to the patient's mass. A patient with a smaller mass exerts a relatively smaller force when walking as opposed to a patient with a larger mass. Existing implantable or portable medical device sensors may detect the force applied while the patient is moving. However, the force applied while the patient is moving varies depending on a variety of environmental or patient factors, including the type and speed of the patient's movement, footwear, gait, surface hardness, fluid retention, time of day, whether the patient is carrying additional objects or weight, moving with the aid of physical assistance, or moving at an artificially faster or slower pace compared to the patient's normal moving speed, etc.

[0033] The inventors have recognized that, among other things, force measurements may be gated using different criteria to provide a reliable measure of patient weight. In certain examples, the determined patient weight measurement may be used to escalate, confirm, verify, or adjust one or more other patient status determinations or alerts, such as early signs of heart failure or fluid retention, or to determine improvement in patient status or treatment effectiveness, such as confirmation of loss of patient weight or return to baseline after a diuretic or other heart failure therapy has been provided.

[0034] Figure 1 shows a relationship 100 of measurements of patient acceleration information 101 in milligals (mG) with and without added weight 102 at a steady walking speed. Multiple force measurements over a 12 second period are shown with a patient 103 with no added weight, a patient 104 with an added +2.25 kg (approximately 5 pounds), and a patient 105 with an added +4.5 kg (approximately 10 pounds). A first best fit line 106 for the measurements shown in Figure 1 has a positive correlation (r) of 0.5.

[0035] Figure 2 shows a relationship 200 between measurements of patient acceleration information 201 with and without added weight 202 at a steady walking speed. In contrast to the number of force measurements over a 12 second period shown in Figure 1, Figure 2 shows a number of force measurements over a 120 second period with patients 203A, 203B having no added weight, a patient 204 having an additional +2.25 kg (approximately 5 pounds), and a patient 205 having an additional +4.5 kg (approximately 10 pounds). A second best fit line 206 for the measurements shown in Figure 2 has a positive correlation (r) of 0.981.

[0036] FIG. 3 illustrates a relationship 300 between measured patient acceleration information 301 (e.g., sensor rectified average (SRA) of force measurements over a 120 second period) and patient weight 302 for a number of patients moving at a walking speed of 1.0 mph (illustrated using square data points 303A, 303B, etc.) and a number of patients moving at a walking speed of 1.2 mph (illustrated using round data points 304A, 304B, etc.). A third best-fit line 306 illustrates the overall relationship between the measured force measurements and patient weight. Determination of patient weight can be estimated along a best-fit line to population data, for example, of heart failure patients and patients with implanted or portable medical devices. In other examples, the population data can be further separated by other factors, such as age or average movement speed, or calibrated using other patient inputs or other indicators of physical speed (e.g., GPS watch, estimates of movement speed from mobile phone data, etc.).

[0037] Force measurements generally correlate with patient weight. For example, force measurements collected on a treadmill from different patients at different walking speeds with different devices (and different axes of a multi-axis device) showed moderate correlation (r>0.5) between measurements of patient acceleration information and measurements of patient weight. The root mean square (RMS) value of force measurements over a 120-second period from a single-axis pulse generator across different walking speeds provided a correlation (r) between different patients and speeds of 0.54. The average RMS value of force measurements over a 120-second period from a multi-axis insertable cardiac monitor (ICM) provided different correlations (r) in different axes, with the axis most closely aligned with the patient's vertical axis providing the highest correlation (r) at 0.56.

[0038] In various examples, the same or different acceleration sensors may be used in overlapping or non-overlapping time periods to determine different patient acceleration information that occurs at different frequencies with different power, processing, performance, or storage requirements. For example, cardiac acceleration information, such as patient heart sounds and endocardial or cardiac acceleration information, or certain patient breath sounds, may occur at different frequencies and may require a higher sampling rate than patient motion or activity information, such as patient posture, physical activity, or respiratory rate. Patient motion information is often detected at sampling rates of 50 Hz or less, while heart sound information is often detected at sampling rates of 200 Hz or more.

[0039] In some examples, a single acceleration sensor with one or more axes (e.g., a single-axis accelerometer, a three-axis accelerometer (e.g., X-axis, Y-axis, Z-axis), etc.) may be gated to require a first sampling rate (e.g., a high sampling rate such as 200 Hz or more) during a first time period and a different second sampling rate (e.g., a low sampling rate such as 50 Hz or less) during a second time period that does not overlap with the first time period, such as to reduce power consumption of the device. In other examples, different axes of a multi-axis sensor may be sampled at different periods, different sampling rates, or with different processing (e.g., filters, signal conditioning, etc.) or storage requirements. In yet other examples, an implantable or portable medical device may include different acceleration sensors configured to detect different acceleration information of a patient at different periods, different frequencies, or with different processing or storage requirements. For example, it may be advantageous to detect physical activity or motion information using a stiffer sensor tuned to detect activities with a higher magnitude and lower frequency response than cardiac acceleration information, while it may be advantageous to detect cardiac acceleration information using a sensor (e.g., a microphone, etc.) with higher sensitivity and sampling frequency.

[0040] Increasing the amount of data collected in each measurement generally improves the accuracy of the measurement and determination of patient weight. When correlating force measurements to measured patient weight, 12-second force measurements showed an error of nearly 3 pounds, while 60-second force measurements showed an error of about 2 pounds, and 120-second force measurements showed an error of less than 1 pound. A longer measurement period (such as a 120-second period as opposed to a 12-second period) provides a better determination of patient weight. Since a daily variation of 2 pounds may trigger a patient alert, it may be preferable to use a longer measurement period to determine the patient weight measurement. A combination of multiple shorter measurement periods, or a combination of longer and shorter measurement periods, may reduce measurement error. However, when other gating criteria (e.g., activity threshold, number of steps, time of day, location, etc.) are considered, requiring a longer measurement period as opposed to a shorter measurement period may reduce the number of separate data measurements available for daily use, which is a trade-off.

[0041] The determination of patient weight, and the reliability of the patient weight determination, may be, for example, Gating Criteria It can be determined and provided as a linear or non-linear combination of measurements on Gating Criteria may include, among others, one or more of a relatively long measurement period (e.g., a 120 second period, as opposed to a relatively short measurement period, etc.), a threshold number of measurements, a specific time of day, temperature, an activity threshold, number of steps, patient movement speed, location, etc.

[0042] In certain examples, measurements that do not meet each preferred criterion reduce the reliability of the patient weight determination but can still be used for patient weight determination, such as achieving a threshold number of measurements. The threshold number of measurements can be static (e.g., at least two) or dynamic, such as dependent on the variation from an expected value. If a single measurement is within a threshold range of an expected value (previous or trend value), additional measurements may not be required. However, if a measurement is outside the threshold range (e.g., ±2 percent of the previous or trend value, ±1 percent of the previous or trend value, etc.), additional measurements may be required. The reliability of a determined patient weight measurement can depend on the variation from the previous or trend value, the number of matching and preferred criteria that make up the determined patient weight measurement, and the like. In one example, the reliability is determined based on preferred criteria, such as agreement or disagreement with other measurements that are relatively close in time (e.g., from a single continuous activity period within a set time period, such as within an hour, from the same day, etc.). Gating Criteria It may be determined using other criteria besides.

[0043] In certain examples, a measure of patient walking force may be determined for the patient using acceleration information sensed during the same time period each day (e.g., in the morning, before noon, between noon and 5 p.m., between 5 p.m. and 10 p.m., etc.) to reduce patient weight fluctuations associated with mealtime food or fluid intake. For many patients, weight generally tends to be lowest in the morning, peak with meals, highest after dinner, and decline for a short period before and after each meal. Measurements taken early in the morning (at the first patient activity each day) or late in the morning (before lunch) may be preferred. In other examples, different patient weight determinations may be made on a daily basis, such as morning, midday, and evening determinations, to determine a measure of patient weight fluctuations in relative periods each day, to determine a daily average weight using a combination of different patient weight determinations on a daily basis, etc. In certain examples, daily or short-term alerts may be deprioritized for patients with larger intraday weight fluctuations as opposed to patients with a more stable daily baseline weight with smaller intraday fluctuations.

[0044] The determination of daily patient weight can be determined as a linear or non-linear combination of force measurements (e.g., more weights are given to the force measurements). Gating Criteria (using measurements that satisfy a threshold) to determine day-to-day change measurements, as well as different short-term measurements (e.g., greater than 1 day but less than 1 or 2 weeks, e.g., 3 days, 5 days, 1 week, etc.) or long-term measurements (e.g., greater than short-term, e.g., greater than 1 week, greater than 2 weeks, etc.). Alerts may be triggered or provided based on daily, short-term, or long-term changes above a threshold, such as indicating fluid accumulation.

[0045] Further gating of the force measurements increases the correlation. Although estimates of patient weight can be determined with a relatively high degree of confidence within a few percent, changes in patient weight detected using differences in force measurements provide a higher degree of correlation and confidence, with the highest correlation occurring with measurements taken at the same time and conditions each day to minimize differences in environment, conditions, etc. For example, daily walking, performed at the same speed, on the same route, and at approximately the same time each day, using the same footwear, may provide the highest correlation and accuracy. While such activity may be encouraged, as with weight scales, patient compliance and such measurements are often unreliable. Also, slower walking speeds (e.g., 1 mph or 1.2 mph as opposed to faster walking speeds such as 2 mph) provide better determination of measurements of patient weight.

[0046] The inventors have recognized that, among other things, repeated features can be detected to reduce variability in force measurements and improve patient weight determination. In addition to time of day, force measurements can be gated by type of activity, speed, etc. For example, a patient walking up or down stairs or on an incline or downhill may exert different forces on the ground than walking on level ground. On the other hand, a patient's steps on level ground will generally be different than a patient's steps on stairs, on an incline, or downhill.

[0047] Patient step rate may be detected in the patient acceleration information as a repeating pattern of relatively constant phase change over the entire measurement window (e.g., changing less than 30% over the entire measurement window) or amplitude change with a threshold amount of the measurement window (e.g., at least 70% of the measurement window). Walking speed may be determined based on a general relationship to step rate (e.g., assuming 2500 steps per mile for a heart failure patient). Force measurements may be determined for qualified measurement windows, such as using the average RMS value or square root of amplitude (SRA) value of the step over the measurement window, the average amplitude, the amplitude of the peak frequency of the measurement window, etc.

[0048] The force measurements may be binned by walking speed or number of steps. Also, measurements in a particular bin may be used to determine a measurement of patient weight. Or, changes in measurements in a particular bin over time may be used to determine changes in a measurement of patient weight. In different examples, different numbers of bins with different granularity may be used in steps per minute, miles per hour (mph), or one or more other units. For example, in binning by speed, a 1 mph bin may include a measurement window with a determined patient walking speed up to 1 mph, a 1.5 mph bin may include a measurement window between 1 mph and 1.5 mph, and a 2 mph bin may include a measurement window between 1.5 mph and 2 mph. In another example, a 1 mph bin may include a measurement window with a determined patient walking speed less than 1.5 mph, a 2 mph bin may include a measurement window between 1.5 mph and 2.5 mph, and a 3 mph bin may include a measurement window above 2.5 mph. In another example, for binning by steps (steps / min), a first bin may include a measurement window corresponding to a range of patient steps, e.g., 40-60 steps / min, a second bin may include a measurement window corresponding to a second range of patient steps, e.g., 60-90 steps / min, and a third bin may include a measurement window corresponding to a third range of patient steps, e.g., greater than 90 steps. In other examples, the bins may be finer or coarser granular, such as having different ranges, higher ranges, lower ranges, or additional ranges.

[0049] In certain instances, higher step counts or walking speeds are generally correlated with better patient condition, and step counts or walking speeds themselves may be tracked as an indicator of patient health, with an increase in step count or walking speed indicating an improvement in the patient condition and a decrease in step count or walking speed indicating a worsening of the patient condition.

[0050] FIG. 4 illustrates an example method 400 for determining a measurement of patient weight using patient acceleration information. At 401, acceleration information may be received, such as using a signal receiving circuit. In one example, the acceleration information may be sensed using an acceleration sensor of an implantable medical device. In some examples, one or both of the acceleration sensor or the signal receiving circuit may include one or more analog or digital signal processing circuits, such as filters, rectifiers, integrators, etc., configured to condition the sensed acceleration information and, in certain examples, determine one or more values ​​or measurements of the acceleration information. In other examples, the evaluation circuit may receive the acceleration information from the signal receiving circuit, determine a value of the acceleration information, and compare the determined value to a threshold value. The value may include an amplitude or energy measurement of the acceleration information representative of a level of patient movement, such as a percentage or frequency of peaks over a measurement window, an energy value of the measurement window (e.g., an integrated measurement, an RMS value, an SRA value, etc.).

[0051] At 402, the value of the acceleration information may be compared to a threshold, such as an activity threshold representing an activity level of walking or less than walking, using an evaluation circuit, for example, to quickly filter out periods of low activity or inactivity. In one example, the measurement window may be of fixed length or may be variable depending on the acceleration information (e.g., remain above a threshold, etc.). In one example, longer or shorter measurement periods as described herein may 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 does exceed the threshold, the method continues.

[0052] At 403, patient walking may be detected in the acceleration information of the measurement window using the evaluation circuit. In one example, the evaluation circuit may detect walking using one or more of the frequency or amplitude of peaks in the acceleration information, the shape of the acceleration information, a repeating pattern of amplitude variations, among others. If patient walking is not detected within the measurement window, the method returns to 401. If patient walking is detected within 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), the method continues.

[0053] At 404, the evaluation circuitry can be used to determine the number of patient steps over the measurement window, such as by measuring the detected steps over the measurement window. In one example, the evaluation circuitry can crop the measurement window to include only the portion of the acceleration information having detected steps. In another example, the evaluation circuitry can correct for missed steps, such as excessive noise or other movement, such as by identifying patterns in which steps were likely located but were not detected (e.g., identifying patterns within a set of patient steps or right / left step variations).

[0054] In some examples, the evaluation circuitry may be configured to use the determined step count to determine patient walking speed. For example, the determined step count may be correlated with a population or patient-specific relationship between the determined step count (for heart failure patients or patients with implantable or portable medical devices) and patient walking speed. In other examples, patient step count may be used in place of the determined walking speed.

[0055] At 405, a measure of patient walking force may be determined for the measurement window, such as using an RMS, SRA, average peak amplitude, or other measure of force of the acceleration information over the measurement window. In one example, the measure of patient walking force may be the same as or different from the value of the acceleration parameter used to determine above-threshold patient activity at 402. For example, the measure of patient walking force at 405 may be.

[0056] At 406, using the evaluation circuitry, the measurements of the patient walking force can be binned into different data sets according to one or more of the number of steps, walking speed, length of the measurement window, time of day (e.g., morning, afternoon, night, or a particular period of the day), values ​​of acceleration parameters, etc. Different bins may, in some examples, be different. Gating Criteria In one example, the daily value of the patient walking force may represent, for example, a preferred Gating Criteria or, using bins representing Gating Criteria may be determined daily for the patient, supplemented or complemented with other criteria if absent, low or variable, or different from expected values. The measurements of the patient walking force and corresponding information associated with one or more different bins may be stored in a memory by the evaluation circuit.

[0057] At 407, the patient weight measurement may be determined, such as using a population-correlated patient walking force measurement, or a patient-specific relationship between the patient walking force measurement and the patient weight. In one example, the evaluation circuitry may determine a received or predetermined preferred Gating Criteria The patient walking force measurement may be selected from a particular bin depending on the patient weight and the patient walking force measurement from that particular bin may be used to determine a patient weight measurement as described herein.

[0058] At 408, the evaluation circuitry may be used to determine or verify an indicator of fluid retention, such as a function of a determined measurement of patient weight. In certain examples, the evaluation circuitry may determine one or more indicators of fluid retention using patient physiological information, such as impedance, pressure, heart sounds, respiration, activity, or other patient physiological information. The determined measurement of patient weight may be used to confirm or improve the reliability or accuracy of the determined indicator of fluid retention.

[0059] At 409, the evaluation circuitry may be used to determine or verify indicators of heart failure, such as a function of the determined patient weight measurement. In certain examples, the evaluation circuitry may determine a composite heart failure risk score using patient physiological information, such as impedance, pressure, heart sounds, respiration, activity, or other patient physiological information, as described in one or more of commonly assigned U.S. patent applications Ser. No. 14 / 510,392, entitled "Methods and apparatus for detecting heart failure decompensation event and stratifying the risk of the same" by Qi An et al., Ser. No. 14 / 282,353, entitled "Method and apparatus for stratifying risk of heart failure decompensation" by Robert. J. Sweeney et al., and Ser. No. 13 / 726,786, entitled "Risk stratification based heart failure detection algorithm" by Qi An et al., each of which is incorporated herein by reference in its entirety.

[0060] The composite heart failure risk score may detect early signs of heart failure before the patient exhibits physical symptoms, in certain instances 30-60 days before the patient's physical condition deteriorates to the point that therapeutic intervention is required. The period between threshold crossings of the heart failure detection score due to frequent fluctuations in patient condition may reduce the caregiver's sensitivity to gradually worsening patient condition. In contrast, sudden or short-term weight gain, such as 2 pounds in 24 hours, or 5 pounds in one week, is a harbinger of more imminent therapeutic intervention or hospitalization (e.g., 3-7 days as opposed to 30-60 days). Thus, the combination of two measurements from a single implantable or portable medical device with a single sensor set, without additional patient compliance issues, i.e., the composite heart failure risk score combined with the measurement of determined patient weight, may be clinically significant.

[0061] At 410, the effectiveness of the therapy may be determined, such as using the change in the determined patient weight measurement. In one example, the measure of therapy effectiveness may be determined from a period preceding the request for efficacy (e.g., current change from the previous day, short-term trends, etc.). In another example, the evaluation circuit may receive the time of therapy provided to the patient and determine the measure of therapy effectiveness using the change in the determined patient weight measurement after the time of therapy provided. The determined therapy effectiveness may provide an indication that the therapy provided was effective, such as in response to early signs of heart failure, and whether more or less therapy should be provided in response to current or future signs.

[0062] 5 shows a relationship 500 between the daily values ​​of the patient walking force from different first and second bins (Bin 1, Bin 2) 501, 502 and the combined value 503 of the daily values ​​of the patient walking force over the number of days 504. As mentioned above, the evaluation circuitry determines the preferred value of the measured values ​​of the patient walking force. Gating Criteria may be applied. In this example, a first bin 501 is preferred over a second bin 502, such that a combination 503 of daily values ​​of patient walking force provides a trend 506 of values ​​from the first bin 501 on days 1-3, and a trend 506 of values ​​from the second bin 502 on days 4 and 5, where there is no value in the first bin 501. In other examples, other combinations of values ​​from different bins may be used to determine a combination of daily values.

[0063] 6 illustrates an exemplary system 600 for determining a measurement of a patient's weight, such as a medical device system, a cardiac rhythm management (CRM) device, etc. In an example, one or more aspects of the exemplary system 600 may be a component of or communicatively coupled to an ambulatory medical device (AMD), an insertable 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, arrhythmia, dyssynchrony, etc., or one or more other physiological conditions, and in certain examples, may be configured to provide electrical stimulation or one or more other therapies or procedures to the patient.

[0064] System 600 may include a single medical device or multiple medical devices implanted within or otherwise placed on or around a patient to monitor physiological information of the patient using one or more sensors, such as sensor 601. In one example, the sensors 601 may include one or more of 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 (e.g., intrathoracic impedance sensor, transthoracic impedance sensor, etc.) configured to receive impedance information, a cardiac sensor configured to receive cardiac electrical information, an activity sensor configured to receive information regarding physical movement (e.g., activity, walking, etc.), a posture sensor configured to receive posture or position information, a pressure sensor configured to receive pressure information, a plethysmographic sensor (e.g., a photoplethysmographic sensor, etc.), a chemical sensor (e.g., an electrolyte sensor, a pH sensor, an anion gap sensor, etc.), a temperature sensor, a skin elasticity sensor, or one or more other sensors configured to receive physiological information of the patient.

[0065] The exemplary system 600 may include a signal receiving circuit 602 and an evaluation circuit 603. The signal receiving circuit 602 may be configured to receive physiological information of a patient (or group of patients) from the sensor 601. The evaluation circuit 603 may be configured to receive information from the signal receiving circuit 602 and use the received physiological information to determine one or more parameters (e.g., physiological parameters, classifiers, etc.) or existing or changed patient conditions (e.g., indicators of the patient's dehydration, respiratory condition, cardiac condition (e.g., heart failure, arrhythmia), sleep disordered breathing, etc.), as described herein. The 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, among others.

[0066] The evaluation circuit 603 may be configured to provide output to a user including a score, trend, alert, or other indicator, such as to a display device or one or more other user interfaces. In other examples, the evaluation circuit 603 may be configured to provide output to other circuits, machines, or processes, such as the therapy circuit 604 (e.g., cardiac resynchronization therapy (CRT) circuit, chemotherapy circuit, etc.) to control, adjust, or stop therapy of a medical device, drug delivery system, etc., or to modify 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, dosage determination or recommendation, etc. In one example, the therapy circuit 604 may include one or more of a stimulation control circuit, a cardiac stimulation circuit, a neural stimulation circuit, a dosage determination or control circuit, etc. In other examples, the therapy circuit 604 may be controlled by the evaluation circuit 603, or one or more other circuits, etc.

[0067] Conventional cardiac rhythm management devices, such as insertable cardiac monitors, pacemakers, defibrillators, or cardiac resynchronization devices, include implantable or subcutaneous devices having a hermetically sealed housing configured to be implanted in a patient's chest. A cardiac rhythm management device may include one or more leads for placing one or more electrodes or other sensors at various locations in or near the heart, such as one or more of the atria or ventricles of the heart. Thus, a cardiac rhythm management device may include embodiments such as leads or electrodes that are placed subcutaneously proximate to the patient's distal skin, as well as embodiments such as leads or electrodes that are placed near one or more organs of the patient. Alternatively or in addition to the one or more electrodes or other sensors on a lead, a cardiac rhythm management device may include one or more electrodes or other sensors (e.g., pressure sensors, accelerometers, gyroscopes, microphones, etc.) that are powered by a power source within the cardiac rhythm management device. The one or more electrodes or other sensors on the lead, the cardiac rhythm management device, or a combination thereof, may be configured to detect physiological information from the patient or provide one or more therapies or stimuli to the patient.

[0068] The implantable device can additionally or alternatively include a leadless cardiac pacemaker (LCP) or a small, self-contained device (e.g., smaller than conventional implantable cardiac rhythm management devices, e.g., having a volume of about 1 cc in a particular example). The small, self-contained device includes one or more sensors, circuits, or electrodes configured to monitor physiological information from the heart (e.g., heart rate), detect physiological conditions associated with the heart (e.g., tachycardia), or deliver one or more therapies or stimuli to the heart without the complications of conventional leads or implantable cardiac rhythm management devices (e.g., required incisions and pockets, lead placement complications, breakage, or migration complications). In a particular example, a leadless cardiac pacemaker can be more limited in power and processing capabilities than conventional cardiac rhythm management devices, but multiple leadless cardiac pacemakers can be implanted in or around the heart to detect physiological information from and deliver one or more therapies or stimuli to one or more chambers of the heart. Multiple leadless cardiac pacemakers can communicate among themselves or with one or more other implanted or external devices.

[0069] 7 illustrates an exemplary patient management system 700 and a portion of the environment in which the patient management system 700 may operate. The patient management system 700 may perform a range of activities including remote patient monitoring and diagnosis of disease conditions. Such activities may be performed near the patient 701, such as the patient's home or office, via a centralized server, such as a hospital, clinic, or doctor's office, or via a remote workstation, such as a secure wireless mobile computing device.

[0070] The patient management system 700 may include one or more portable medical devices, an external system 705, and a communications link 711 providing communications between the one or more portable medical devices and the external system 705. The one or more portable 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 portable medical devices configured to monitor, sense, or detect information from, determine physiological information, or provide one or more therapies to, the patient 701 to treat various conditions of the patient 701, such as one or more cardiac or non-cardiac conditions (e.g., dehydration, sleep disordered breathing, etc.).

[0071] In one example, the implantable medical device 702 may include one or more conventional cardiac rhythm management devices implanted in the patient's chest having a lead system including one or more intravenous, subcutaneous, or non-invasive leads or catheters for placing one or more electrodes or other sensors (e.g., heart sound sensors) in, on, or around the heart of the patient 701, or at one or more other locations on the chest, abdomen, or neck of the patient 701. In another example, the implantable medical device 702 may include a monitor implanted, for example, subcutaneously in the chest of the patient 701. The implantable medical device 702 includes a housing that contains circuitry and, in a particular example, includes one or more sensors, such as a temperature sensor.

[0072] The implantable medical device 702 may include evaluation circuitry configured to detect or determine certain physiological information of the patient 701 and to determine one or more conditions or provide information or alerts to a user, such as the patient 701 (e.g., the patient), a clinician, or one or more other caregivers or practitioners. The implantable medical device 702 may alternatively or additionally be configured as a therapy device configured to treat one or more medical conditions of the patient 701. The therapy may be delivered to the patient 701 via a lead system and associated electrodes or using one or more other delivery mechanisms. The therapy may include delivering one or more drugs to the patient 701, such as using one or more of the implantable medical device 702 or other portable medical devices. In some examples, the therapy may include cardiac resynchronization therapy to correct dyssynchrony and improve cardiac function in a heart failure patient. In other examples, the implantable medical device 702 may include a drug delivery system, such as an infusion pump, that delivers drugs to the patient to manage arrhythmias or complications from arrhythmias, hypertension, or one or more other physiological conditions. In other examples, implantable medical device 702 may include one or more electrodes configured to stimulate the patient's nervous system, to provide stimulation to muscles of the patient's airway, or the like.

[0073] The wearable medical device 703 may include one or more wearable or external medical sensors or devices (e.g., an automated external defibrillator (AED), a Holter monitor, a patch-based device, a smart watch, a smart accessory, a wrist- or finger-worn medical device (e.g., a finger-based photoplethysmography sensor, etc.)).

[0074] The external system 705 may include a dedicated hardware / software system, such as a programmer, a remote server-based patient management system, or a system defined primarily by software running on a standard personal computer. The external system 705 may manage the patient 701 through the implantable medical device 702 or through one or more other portable medical devices connected to the external system 705 via a communication link 711. In other examples, the implantable medical device 702 may be connected to a wearable medical device 703 via a communication link 711, or the wearable medical device 703 may be connected to the external system 705 via a communication link 711. This may include, for example, programming the implantable medical device 702 to perform one or more of acquiring physiological data, performing at least one self-diagnostic test (such as device operating status), analyzing the physiological data, or optionally delivering or adjusting therapy to the patient 701. The external system 705 may also send information to or receive information from the implantable medical device 702 or the wearable medical device 703 via the communication link 711. For example, this information may include real-time or stored physiological data from the patient 701, diagnostic data such as detection of the patient's hydration status, length of hospital stay, response to therapy delivered to the patient 701, or device operating status of the implantable medical device 702 or wearable medical device 703 (e.g., battery status, lead impedance, etc.). The communications link 711 may be an inductive telemetry link, a capacitive telemetry link, a radio frequency (RF) telemetry link, or wireless telemetry based, for example, on the "strong" Bluetooth or IEEE 802.11 wireless fidelity "Wi-Fi" interface standards. Other configurations and combinations of patient data source interfaces are possible.

[0075] The external system 705 may include an external device 706 in proximity to one or more portable medical devices and a remote device 708 that is relatively remote from the one or more portable medical devices and communicates with the external device 706 via a communication network 707. An example of the external device 706 may include a medical device programmer. The remote device 708 may be configured to evaluate collected patient or patient information and provide alert notifications, among other possible functions. In one example, the remote device 708 may include a centralized server that serves as a central hub for storage and analysis of collected data. The server may be configured as a single, multiple, or distributed computing and processing system. The remote device 708 may receive data from multiple patients. The data may be collected by one or more portable medical devices, among other data acquisition sensors or devices associated with the patient 701. The server may include a memory device for storing the data in a patient database. The server may include an alert analysis circuit that evaluates the collected data to determine if a particular alert condition is met. Satisfaction of an alert condition may trigger the generation of an alert notification provided by one or more human-perceptible user interfaces. In some examples, the alert condition may alternatively or additionally be evaluated by one or more portable medical devices, such as an implantable medical device. By way of example, the alert notification may include a web page update, a phone or pager call, an email, an SMS, a text or "instant" message, a message to the patient, and a simultaneous direct notification to emergency services and clinicians. Other alert notifications are possible. The server may include an alert prioritization circuit configured to prioritize the alert notifications. For example, an alert of a detected medical event may be prioritized using a similarity metric between physiological data associated with the detected medical event and physiological data associated with historical alerts.

[0076] The remote device 708 may further include one or more locally configured or remote clients securely connected to the server via the communication network 707. Examples of clients may include personal desktops, notebook computers, mobile devices, or other computing devices. Using the clients, a system user, such as a clinician or other qualified medical professional, may securely access stored patient data collected in a database in the server to select and prioritize patients and alerts for medical provisioning. In addition to generating alert notifications, the remote device 708, including the server and interconnected clients, may also execute a follow-up scheme by sending follow-up requests to one or more portable medical devices, or by sending messages or other communications to the patient 701 (e.g., the patient), the clinician, or an authorized third party as compliance notifications.

[0077] The communications network 707 may provide wired or wireless interconnections. In one example, the communications network 707 may be based on the Transmission Control Protocol / Internet Protocol (TCP / IP) network communications specification, although other types or combinations of networking implementations are possible. Similarly, other network topologies and configurations are possible.

[0078] One or more of the external device 706 or remote device 708 may output the detected medical event to a system user, such as a patient or a clinician, or to a process including, for example, an instance of a computer program executable on a microprocessor. In one example, the process may include automatic generation of a recommendation for an antiarrhythmic therapy, or a recommendation for further diagnostic testing or treatment. In one example, the external device 706 or remote device 708 may include a respective display unit for displaying a physiological signal, a functional signal, an alert, an alarm, an emergency call, or other form of alert that signals the detection of the arrhythmia. In some examples, the external system 705 may include an external data processor configured to analyze the physiological or functional signals received by the one or more portable medical devices and confirm or reject the detection of the arrhythmia. Computationally intensive algorithms, such as machine learning algorithms, may be implemented in the external data processor to retrospectively process the data to detect cardiac arrhythmias.

[0079] The one or more portable medical devices or portions of the external system 705 may be implemented using hardware, software, firmware, or a combination thereof. The one or more portable medical devices or portions of the external system 705 may be implemented using application specific circuitry that may be constructed or configured to perform one or more functions, or may be implemented using general purpose circuitry that may be programmed or otherwise configured to perform one or more functions. Such general purpose circuitry may include a microprocessor or portion thereof, a microcontroller or portion thereof, or programmable logic circuitry, memory circuitry, network interfaces, and various components for interconnecting these components. For example, a "comparator" may include, among other things, an electronic circuit comparator that may be constructed to perform the specific function of a comparison between two signals. Or, the comparator may be implemented as part of a general purpose circuit that may be driven by code that instructs it to perform a comparison between two signals. A "sensor" may include an electronic circuit configured to receive information and provide an electronic output representative of the received information.

[0080] The therapy device 710 may be configured to send information to and receive information from one or more of the portable medical devices or external systems 705 using the communication link 711. In one example, one or more of the portable medical devices, external devices 706, or remote devices 708 may be configured to control one or more parameters of the therapy device 710. The external system 705 may be capable of programming the one or more portable medical devices and may receive information regarding one or more signals acquired by the one or more portable medical devices, for example, via the communication link 711. The external system 705 may include a local external implantable medical device programmer. The external system 705 may include a remote patient management system that may monitor a patient's condition or adjust one or more therapies from a remote location, etc.

[0081] 8 illustrates a block diagram of an example machine 800 in which any one or more of the techniques (e.g., methods) described herein may be implemented. Portions of this description may be applicable to the computing framework of one or more of the medical devices described herein, such as implantable medical devices, external programmers, etc. Also, as described herein with respect to components, systems, or machines of medical devices, they may require regulatory compliance that is not possible with general purpose computers, components, or machines.

[0082] As described herein, an embodiment may include or operate by logic or some components or mechanisms within the machine 800. A circuit (e.g., processing circuit, evaluation circuit, etc.) is a collection of circuits implemented in the tangible entity of the machine 800 including hardware (e.g., simple circuits, gates, logic, etc.). The configuration of a circuit may be flexible over time. A circuit includes members that, when operated, are capable of performing specific operations alone or in combination. In one example, the hardware of a circuit may be invariably designed (e.g., hardwired) to perform specific operations. In one example, the hardware of a circuit may include variably connected physical components (e.g., execution units, transistors, simple circuits, etc.) including machine-readable media that are physically modified (e.g., magnetically, electrically, movable arrangements of invariant assembled particles, etc.) to encode instructions for specific operations. In connecting the physical components, the underlying electrical properties of the hardware components are changed, for example, from an insulator to a conductor or vice versa. The instructions enable the embedded hardware (e.g., an execution unit or a loading mechanism) to create configurations of circuits within the hardware through variable connections to perform some of the specific operations during operation. Thus, in one example, the machine-readable media element is part of a circuit or is communicatively coupled to other components of a circuit when the device is operating. In one example, any of the physical components can be used in more than one component of two or more circuits. For example, during operation, an execution unit can be used in a first circuit of a first electrical circuit at one time and reused by a second circuit of the first electrical circuit, or reused by a third circuit of the second electrical circuit at a different time. Additional examples of these components with respect to machine 800 are provided below.

[0083] In alternative embodiments, machine 800 may operate as a standalone device or may be connected (e.g., networked) to other machines. In a networked arrangement, machine 800 may operate as a server machine, a client machine, or both in a server-client network environment. In one example, machine 800 may operate as a peer machine in 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, web appliance, network router, switch or bridge, or any machine capable of executing instructions (sequential or otherwise) that specify actions to be performed by the machine. Also, although only a single machine is shown, the term "machine" may be interpreted to include any collection of machines that individually or collectively execute a set (or sets) of instructions to perform any one or more of the methods described herein, such as cloud computing, software as a service (SaaS), other computer cluster configurations, etc.

[0084] The machine (e.g., computer system) 800 may include a hardware processor 802 (e.g., a central processing unit (CPU), a graphics processing unit (GPU), a hardware processor core, or any combination thereof), a main memory 804, a static memory (e.g., memory or storage for firmware, microcode, basic input / output (BIOS), unified extensible firmware interface (UEFI), etc.), some or all of the main memory 804, 806, and mass storage 808 (e.g., hard drives, tape drives, flash storage, or other block devices) may communicate with each other via an interlink (e.g., bus) 830. The machine 800 may further 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 one example, the display unit 810, the input device 812, and the UI navigation device 814 may be touch screen displays. The machine 800 may further include a signal generating 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. The machine 800 may include an output control device 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., a printer, a card reader, etc.).

[0085] The hardware processor 802, the main memory 804, the static memory 806, or the registers of the mass storage 808 may be or include a machine-readable medium 822 on which is stored one or more sets of data structures or instructions 824 (e.g., software) that embody or are utilized by any one or more of the techniques or functions described herein. Also, the instructions 824 may reside, completely or at least partially, within any of the hardware processor 802, the main memory 804, the static memory 806, or the registers of the mass storage 808 during their execution by the machine 800. In one example, a combination of any one or more of the hardware processor 802, the main memory 804, the static memory 806, or the mass storage 808 may constitute the machine-readable medium 822. Although the machine-readable medium 822 is illustrated as a single medium, the term "machine-readable medium" may 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.

[0086] The term "machine-readable medium" may include any medium capable of storing, encoding, or carrying instructions for execution by the machine 800 that cause the machine 800 to perform any one or more of the techniques of this disclosure, or capable of storing, encoding, or carrying data structures used by or associated with such instructions. Non-limiting examples of machine-readable media may include solid-state memory, optical media, magnetic media, and signals (e.g., radio frequency signals, other photon-based signals, audio signals, etc.). In one example, a non-transient machine-readable medium includes a machine-readable medium having a plurality of particles having a fixed (e.g., stationary) mass, and thus is a composition of matter. Thus, a non-transient machine-readable medium is a machine-readable medium that does not include a transitory propagating signal. Examples of non-transitory machine-readable media may 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, magnetic disks such as internal hard disks and removable disks, magneto-optical disks, and CD-ROM and DVD-ROM disks.

[0087] The instructions 824 may further be transmitted or received over a communications network 826 using a transmission medium via a network interface device 820 utilizing any one of a number of transport protocols (e.g., Frame Relay, Internet Protocol (IP), Transmission Control Protocol (TCP), User Datagram Protocol (UDP), Hypertext Transfer Protocol (HTTP), etc.). Exemplary communications networks may include local area networks (LANs), wide area networks (WANs), packet data networks (e.g., the Internet), mobile telephone networks (e.g., cellular networks), Plain Old Telephone (POTS) networks, and wireless data networks (e.g., the Institute of Electrical and Electronics Engineers (IEEE) 802.11 family of standards known as Wi-Fi®, the IEEE 802.16 family of standards known as WiMax®), the IEEE 802.15.4 family of standards, peer-to-peer (P2P) networks, among others. In one example, the network interface device 820 may include one or more physical jacks (e.g., Ethernet, coaxial, or telephone jacks) or one or more antennas for connecting to the communications network 826. In one example, the network interface device 820 may include multiple antennas for 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" shall be interpreted to include any intangible medium capable of storing, encoding, or carrying instructions for execution by the machine 800, including digital or analog communication signals or other intangible media for facilitating communication of such software. Transmission media are machine-readable media.

[0088] Various embodiments are illustrated in the figures described above. One or more features according to one or more of these embodiments may be combined to form other embodiments. The method examples described herein may be at least partially machine or computer implemented. Some examples may include computer readable or machine readable media encoded with instructions operable to configure an electronic device or system to perform the methods described in the above examples. Implementations of such methods may include code, such as microcode, assembly language code, high level language code, etc. Such code may include computer readable instructions for performing various methods. The code may form part of a computer program product. Additionally, the code may be tangibly stored on one or more volatile or non-volatile computer readable media during execution or at other times.

[0089] The foregoing detailed description is illustrative and not restrictive, and therefore the scope of the present disclosure should be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled.

Claims

1. 1. A medical device, comprising: means for receiving acceleration information of the patient; determining whether a value of the acceleration information exceeds an activity threshold; and in response to the value of the acceleration information exceeding the activity threshold, detecting patient walking within a measurement window using the acceleration information; Using the detected patient gait, determining a patient step count over said measurement window; determining a measurement of the patient's walking force in said measurement window; and an evaluation circuit configured as described above, The medical device, wherein the evaluation circuit is configured to determine a measure of patient weight using the determined patient step count and a measure of patient walking force.

2. The evaluation circuit includes: determining patient step counts and patient walking force measurements for a plurality of measurement windows; binning the determined patient walking force measurements into one of a set of bins corresponding to the determined patient step count in each of the measurement windows; determining a measure of the patient's weight using the determined patient walking force measure of one of the set of bins; The medical device of claim 1 , configured as follows:

3. The evaluation circuit includes: determining patient step counts and patient walking force measurements for said plurality of measurement windows across a plurality of days; determining a daily measurement of patient walking force in each bin of the set of bins having the determined measurements of patient walking force for each said day; determining a measure of the patient's weight using the determined daily measure of the patient's walking force for one of the set of bins; The medical device of claim 2 , configured as follows:

4. the measure of patient weight comprises a change in patient weight; The evaluation circuit includes: determining a measure of change over time in the determined patient walking force measure in one of the set of bins; and determining a change in the patient's weight using said determined change measurements. The medical device of claim 2 , configured as follows:

5. The evaluation circuit includes: a daily change in patient weight using the change in the determined patient walking force measurement in one bin of the set of bins occurring over the course of a day; a short-term change in patient weight using the change in the determined patient walking force measurement in one of the set of bins occurring over a first time period including a plurality of days; a long-term change in patient weight using a change in the determined patient walking force measurement in one of the set of bins occurring over a second time period that is longer than the first time period; and The medical device of claim 4 , configured to determine at least one of:

6. The evaluation circuit includes: binning the determined patient walking force measurements into one of the set of bins according to the determined patient step count in each of the measurement windows and at least one of a time of the measurement window and a length of the measurement window; determining a measure of the patient's weight using the determined patient walking force measure for a bin of the set of bins corresponding to at least one of a particular time and a particular length of the measurement window; The medical device of claim 2 , configured as follows:

7. the sets of bins correspond to different ranges of patient steps and different periods of the day; The set of bins comprises: a first bin corresponding to a first range of patient steps, a first period of a day, and a first length of the measurement window; at least one of the second bin, the third bin, the fourth bin, the fifth bin, and the sixth bin; the second bin corresponding to the first range of patient steps, the first period of a day, and a second length of the measurement window; the third bin corresponding to the first range of patient steps, a second period of a day, and the first length of the measurement window; the fourth bin corresponding to a second range of patient steps, the first period of a day, and the first length of the measurement window; the fifth bin corresponding to the first range of patient steps, the second period of a day, and the second length of the measurement window; the sixth bin corresponding to the second range of patient steps, the first period of a day, and the second length of the measurement window; and at least one of:

8. the first range of patient steps includes 40 to 60 steps / minute, and the second range of patient steps includes 60 to 90 steps / minute; The medical device of claim 7 , wherein the first period of a day comprises a morning period of a day and the second period of a day comprises an evening period of a day.

9. the sets of bins correspond to different ranges of patient step counts; The set of bins comprises: a first bin corresponding to a first range of patient steps; a second bin corresponding to a second range of patient steps greater than the first range; Including, 3. The medical device of claim 2, wherein the evaluation circuit is configured to determine the patient weight measurement using the determined patient walking force measurements for the first and second bins while prioritizing the determined patient walking force measurements for the first bin corresponding to the first range of patient steps that are less than the second range of patient steps.

10. The evaluation circuit includes: determining a patient walking speed over the measurement window using the determined patient step count over the measurement window; determining a measure of the patient's weight using the determined patient walking speed and a measure of the patient's walking force; The medical device of claim 1 , configured as follows:

11. The medical device of claim 1 , wherein the means for receiving the patient acceleration information comprises a signal receiving circuit configured to receive the patient acceleration information.

12. the medical device comprises an implantable medical device configured to be implanted within the patient's body; the implantable medical device comprises an acceleration sensor configured to sense acceleration information of the patient; The medical device of claim 11 , wherein the signal receiving circuit is configured to receive the acceleration information from the acceleration sensor.

13. the signal receiving circuitry is configured to receive at least one of impedance information of the patient and heart sound information of the patient; The medical device of claim 11 , wherein the evaluation circuitry is configured to determine an indication of fluid retention in the patient using the received impedance information and the determined measurement of patient weight.

14. the signal receiving circuitry is configured to receive heart sound information of the patient; The medical device according to any one of claims 11 to 13, wherein the evaluation circuit is configured to determine an indicator of heart failure using the received heart sound information and the determined measure of the patient's weight.

15. 1. A method comprising: receiving acceleration information of the patient; using an evaluation circuit to determine whether the value of the acceleration information exceeds an activity threshold over a measurement window; and in response to the value of the acceleration information exceeding the activity threshold over the measurement window, using the acceleration information to detect patient walking within the measurement window; determining a patient step count over the measurement window using the detected patient gait; determining a measurement of the patient's walking force in said measurement window; and determining, using said evaluation circuit, a measure of the patient's weight using said determined patient step count and a measure of the patient's walking force; A method for providing the above.

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