Patent Application
20180078191
This invention relates to systems for determining health conditions.
Convenient ways to measure health data are often less accurate than more invasive alternatives. However, accuracy can be a challenge for certain body types or individuals with certain physical conditions that need to be monitored. This may be because the health parameter is often being inferred from the results of an analytical technique rather than directly measured. Additionally, health care providers sometimes simultaneously use multiple methods to infer an individual's health status, each associated with a different degree of accuracy and relevance to the individual, in an attempt to create a complex health assessment or to select a single diagnosis out of a lengthy differential diagnosis. The shortcoming of each measurement may be taken into account when interpreting the data generated by the measurement. Furthermore, many clinical measurements are merely snap shots of an individual's health status on a particular day. However, daily measurements of multiple physiological processes to create a complete health assessment, using only data that is likely to be valid, is often be prohibitive. A way to determine which measurement is the most accurate and meaningful to use in making assessments and decisions about an individual's health is needed. Furthermore, a method to conduct measurements of multiple physiological parameters daily, or multiple times each day, with an assessment of each measurement's validity is also needed.
We disclose a novel health metering device and methods of use thereof to identify which health measurements are accurate and relevant to assess a user's health. More specifically, we disclose a device and methods to collect multiple health data measurements, hereinafter, “metrics,” including a mechanism to combine, filter, and/or cull the collected metrics. The device includes a computer that is programmed to provide output calculations and reports that a healthcare provider may use to assess the user's health status. While a plurality of metrics may be collected at any one time, some metrics may be weighted relative to others, a process which indicates the relative validity of each metric. In addition, metrics may be calculated differently based on the body type or health status of the user, each of which may be identified by one or more of the metrics. Thus, the disclosed device may be used to individually tailor reported health data based on the body type or other physical parameters of the individual user. The most accurate and meaningful data is therefore reported or flagged as useful data. In contrast, less meaningful data may be omitted from the report or identified as not relevant to the particular user's health status. In the instant disclosure, the metrics include those that are conducted by a toilet that is a medical device. The toilet referenced herein measures multiple metrics then transmit the metrics to a computer that is programmed to process the metrics based on their validity and relevance to the individual user's health status.
Toilet, as used herein, means a device that collects biological waste products of a mammal including urine, feces, and vomit.
Metric, as used herein, means a system, method, or standard of measurement.
Data means information, numerical or otherwise, that is collected using one of a variety of health measurement methods.
Health status, as used herein, means the current physiological state of a mammal. In general, this term refers to the overall health of the mammal. However, individual parameters relating to a specific body part or biological system may be measured to identify disease states or physiological parameters that are outside of those known in the art to be within normal range. Such individual physiological parameters may be used to define the health status of the mammal with regard to a specific physiological system.
User, as used herein, means any mammal, human or animal, for which the toilet disclosed herein is being used to measure physiological functions.
While this invention is susceptible of embodiment in many different forms, there are shown in the drawings, which will herein be described in detail, several specific embodiments with the understanding that the present disclosure is to be considered as an exemplification of the principals of the invention and is not intended to limit the invention to the illustrated embodiments.
Disclosed herein is a health metering device and methods for use thereof which provides assessment of the validity and relevance of the metrics it collects. Multiple metrics which either directly indicate or infer a user's health status are collected. Some of these metrics may provide an indication of the validity of others. Each metric is assigned a weight value based on the values of other metrics taken at the same or different time points. Metrics that have been assigned a weight value below a threshold value may be flagged as invalid or excluded from multi-variable calculations that provide an assessment of the user's health status.
In the embodiments disclosed herein, the health metrics are collected as a user interacts with a toilet. These health metrics may be collected while the user is simply sitting on the toilet, standing in front of the toilet on a scale associated with a toilet, and or while the user is depositing bodily waste into the toilet. The toilet comprises multiple sub-devices which measure different physiological parameters then transfer the metrics to a computer for processing according to programming as disclosed herein.
Referring now to the figures,
The two or more metrics that toilet 101 may measure include, but are not limited to, body temperature, body weight, body composition (i.e. percent body fat, intracellular and/or extracellular water), heart rate, pedal pulse rate, blood pressure, blood oxygen saturation, electrocardiogram (EKG or ECG) measurement, urine constituents and parameters including urine color, glucose, urea, creatinine, specific gravity, urine protein, electrolytes, urine pH, osmolality, human chorionic gonadotropin (for detecting pregnancy), hemoglobin, white blood cells, red blood cells, ketone bodies, bilirubin, urobilinogen, free catecholamines, free cortisol, phenylalanine, and urine volume. The metrics may also include fecal analysis including fecal weight and volume, calprotectin, lactoferrin, and hemoglobin. Additionally, one or more of the flow, volume, and weight sensors may determine periods of excretion activity to measure, for instance, urination or defecation exertions, or selectively record metrics that were collected during periods of low exertion. These metrics are useful because some metrics are best performed after complete voiding of the bowel and bladder for maximum accuracy.
The heart rate data 220 and blood pressure data 230 collected for the individual shown in
The embodiment of toilet 400 shown in
The computer processor may be programmed to report the measured body weight after urination or defecation is complete. The flow or level meter data indicates when urination or defecation is complete or nearly complete by detecting that the level measured is approximately constant at that time or by detecting that the flow measured is small.
The invention disclosed herein may be used to compile an accurate trend of physiological changes over time. The health trend reporting system, for example, that disclosed in U.S. patent application Ser. No. 15/242,929 filed on Aug. 22, 2016 may combine multiple weight measurements to report the weight trend to the user or to the user's health care provider. The weighting of each measurement may be different depending on a second measurement parameter. The computer program that calculates and reports the body weight trend may preferentially weight measurements that were taken when the user's total body water level is within a defined range. As discussed above, total body water can be estimated by either bioimpedance. It may also be estimated by properties of the urine such as specific gravity, color, or urea or creatinine concentration.
In summary, the estimate of hydration level of a user by either urinalysis or bioimpedance may allow appropriate calculations to be selected to estimate changes in body fat or body weight over time by giving more weight to measurements taken when the user is properly hydrated. One of skill in the art will readily understand that the example of using urinalysis to assess bioimpedance metrics is merely an example and that the instant invention may be applied to other health metric sets in an analogous way.
In situations when the user does not input gender data, urine flow rate can predict the gender of the user as females tend to have a greater urination rate than males. The reported data may inform the user that gender was predicted using this method and that data was interpreted accordingly. If the individual interpreting the data notes that the urination rate measurement assigned an inaccurate gender to the user, the computer processor may include a mechanism to recalculate the data using the correct gender. The user's gender may then be included in metric analyses.
In addition to variations that occur due to the specific body parts used to collect bioimpedance metrics, it has been shown that bioimpedance measurements are also less accurate if the user is moving. In some embodiments, including those shown in
Collecting valid metrics may be especially important when the data suggests a serious pathology and either a false positive or a false negative could have serious consequences. For example, EKG measurements may suggest that the user is experiencing atrial fibrillation. The analysis system may provide a signal, such as a blinking light or a digital or verbal message, which tells the user to repeat the measurement.
Alternatively, the motion detection system may be used to determine what type of metric to collect. For example, the motion detection may be used to determine whether to make a fast, single frequency bioimpedance measurement or to make a potentially more accurate multi-frequency measurement based on whether the user is relatively motionless or continues to move during measurements. This could be useful when the user is a small child or incoherent adult for which measurements may be difficult to obtain while the user is relatively still. The computer processor could be programmed to include bioimpedance data in calculations when a defined number of measurements fail due to excessive user motion. Alternatively, user input could indicate that data should not be rejected due to motion, rather, the computer processor could be programmed to use the best possible available measurement and simply flag the data to indicate that the user was moving during the measurement.
In addition, bioimpedance measurements are more accurate after urination is complete. In embodiments that include a flow meter or liquid level meter to identify when urination is complete, the computer processor could be programmed to reject bioimpedance measurements taken before urine flow ceases. Accordingly, a more accurate bioimpedance measurement may be used to calculate health parameters that inform assessment of user health status.
The heart rate may also be measured using a photoplethysmography (PPG) sensor which may be a finger clip 516 as shown in
With these and other options for measuring heart rate, a method is needed for determining which measurement is the most relevant and accurate. Variables such as whether the user is wearing shoes, a thick jacket, holding the hand-held electrodes, or whether body fat in the thigh prevents an accurate PPG from the thigh may cause one method of measuring heart rate to be less effective than another. The computer processor may be programmed to ignore signals that are weak or inconsistent in favor of using data that is delivered by methods that provide better measurements. Furthermore, the computer processor may be programmed to process multiple metrics, including, but not limited to heart rate, over time and entered into an analysis system which builds a profile for the individual user. The analysis system may give priority to the most useful data and ignore the other when analyzing and combining data points and assembling a health status report. Over time, the analysis system may be programmed to ignore measurements from sources that have provided consistently poor data in the past.
In other examples, a user's fingers may be cold resulting in low blood perfusion in the fingers. Consequently, finger clip 516 may have difficulty detecting accurate PPG heart rate data. The analysis system may deprioritize this measurement in favor of another method of measuring the user's heart rate. Alternatively, if, on a particular day, bioimpedance measurements taken at low frequency (for example, approximately 1 kHz conduction) are indicative of a high resistance between two electrode contacts, the analysis system may ignore these measurements. In another example as described briefly above, a temperature sensor may be positioned near the stethoscope, for example, stethoscope 514 of
In other embodiments, measurement of a physiological function may indicate that a health-related metric may not be estimated or calculated from this specific data set, even though the data set represents the metric that would normally be used to calculate the health-related metric. For example, measurements from stethoscope 514 or from pressure sensors located in scale 405 may suggest that the user is breathing abnormally fast. In this situation, heart rate measurements will not be recorded as “resting heart rate.” In contrast, heart rate measurements collected at a time when there is no indication of rapid breathing will be defined as a measurement of “resting heart rate.”
Multiple measurements of the same physiological function over time may be combined to produce a trending analysis. Unlike a clinical evaluation in which the measurements may always be valid, a trending analysis may include selected data points while others, deemed to be of insufficient quality, may be ignored. The value of trending analysis lies in the elimination of less accurate data and it provides a means for monitoring changes in a user's physiological functions over longer periods of time than can be obtained in a clinical setting. In other words, the clinical setting may provide one or several snapshots of an individual's health status, each of which are often given equal weight. A trending analysis provides more data points over a period of time and includes only data points that are deemed to be valid.
Furthermore, metrics from a medical device other than the toilet may be entered into the computer and used in calculations. For example, a user's health care provider may order clinical laboratory tests that are conducted by a hospital laboratory or tests performed by any medical devices other than the toilet describe herein. The data from sources other than the toilet may be entered into the computer and used to perform calculations. The calculations may be performed by combining metrics collected by the toilet with those from other sources. Alternatively, the calculations may perform separate calculations using either the metric collected by the toilet or the metric collected by the other source. For example, an analysis of a user's urine glucose may be performed by the toilet and in a hospital laboratory. By performing separate calculations, the metrics from the two sources may be compared. The computer processor may be programmed to produce a report of the calculations performed using metrics from either or both sources and provide an indication of the source of the metric(s) used to perform each calculation.
While specific embodiments have been illustrated and described above, it is to be understood that the disclosure provided is not limited to the precise configuration, steps, and components disclosed. Various modifications, changes, and variations apparent to those of skill in the art may be made in the arrangement, operation, and details of the methods and systems disclosed, with the aid of the present disclosure.
Without further elaboration, it is believed that one skilled in the art can use the preceding description to utilize the present disclosure to its fullest extent. The examples and embodiments disclosed herein are to be construed as merely illustrative and exemplary and not a limitation of the scope of the present disclosure in any way. It will be apparent to those having skill in the art that changes may be made to the details of the above-described embodiments without departing from the underlying principles of the disclosure herein.
