Method and device for measuring and monitoring child growth

Abstract

A measurement system for assessing growth of a patient, including a horizontal platform having a length and a width; a length measuring device including a headboard and at least one footboard, the headboard and the at least one footboard being coupled to the horizontal platform along the length of the horizontal platform; one or more load cells in contact with the horizontal platform; a retractable measuring tape spooled around a cartridge having a rotatable axis; and processing circuitry configured to determine a height of the patient based on a distance between the headboard and the at least one footboard, a weight of the patient based on a weight applied to the one or more load cells, and a head circumference of the patient based on an exposed length of the retractable measuring tape.

Description

METHOD AND DEVICE FOR MEASURING AND MONITORING CHILD GROWTHBACKGROUNDCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] The present application claims priority to U.S. Provisional Application No. 63 / 514,724, filed July 20, 2023, which is incorporated herein by reference in its entirety for all purposes.FIELD OF THE DISCLOSURE

[0002] This disclosure relates to methods, devices, and systems for measuring, monitoring, analyzing, and reporting the physical characteristics of an individual.DESCRIPTION OF THE RELATED ART

[0003] Routine growth screening is recommended in the United States at birth and during every health checkup until age three. This can lead to around 11 visits in the first few years of a child's life in the United States. Routine growth screening is also performed worldwide. However, pediatricians and parents face challenges when measuring the heads, lengths, and weights of moving and crying infants.

[0004] The foregoing Background description is for the purpose of generally presenting the context of the disclosure. Work of the inventors, to the extent it is described in this background section, as well as aspects of the description which may not otherwise qualify as prior art at the time of the filing, are neither expressly or impliedly admitted as prior art against the present disclosure.SUMMARY

[0005] The foregoing paragraphs have been provided by way of general introduction, and are not intended to limit the scope of the following claims. The described embodiments, together with further advantages, will be best understood by reference to the following detailed description taken in conjunction with the accompanying drawings.

[0006] In one embodiment, the present disclosure is directed to a measurement system for assessing growth of a patient, including a horizontal platform having a length and a width; a length measuring device including a headboard and at least one footboard, the headboard and the at least one footboard being coupled to the horizontal platform along the length of the horizontal platform; one or more load cells in contact with the horizontal platform; a retractable measuring tape spooled around a cartridge having a rotatable axis; and processing circuitry configured to determine a height of the patient based on a distance between the headboard and the at least one footboard, a weight of the patient based on a weight applied to the one or more load cells, and a head circumference of the patient based on an exposed length of the retractable measuring tape and to determine whether the growth of the patient is within a predetermined normal range based on the height, the weight, and / or the head circumference.

[0007] In one embodiment, the present disclosure is directed to a method for assessing growth of a patient, comprising determining, via processing circuitry, a height of the patient based on a distance between a headboard positioned at a head of the patient and a footboard positioned at a foot of the patient; determining, via the processing circuitry, a weight of the patient based on one or more load cells underneath the patient; determining, via the processing circuitry, a head circumference of the patient based on a length of a retractable measuring tape wrapped around a head of the patient; and determining, via the processing circuitry, whether the growth of the patientis within a predetermined normal range based on the height, the weight, and / or the head circumference.

[0008] In one embodiment, the present disclosure is directed to a non-transitory computer- readable storage medium for storing computer-readable instructions that, when executed by a computer, cause the computer to perform a method for assessing growth of a patient, the method comprising determining a height of the patient based on a distance between a headboard positioned at a head of the patient and a footboard positioned at a foot of the patient; determining a weight of the patient based on one or more load cells underneath the patient; determining a head circumference of the patient based on a length of a retractable measuring tape wrapped around a head of the patient; and determining whether the growth of the patient is within a predetermined normal range based on the height, the weight, and / or the head circumference.BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The skilled artisan will understand that the drawings primarily are for illustrative purposes and are not intended to limit the scope of the inventive subject matter described herein. The drawings are not necessarily to scale; in some instances, various aspects of the inventive subject matter disclosed herein may be shown exaggerated or enlarged in the drawings to facilitate an understanding of different features. Certain features of the disclosure may be shown in somewhat schematic form and some details of conventional elements may not be shown in the interest of clarity and conciseness. In the drawings, like reference characters generally refer to like features (e.g., functionally similar and / or structurally similar elements).

[0010] A more complete appreciation of the invention and many of the attendant advantages thereof will be readily obtained as the same becomes better understood by reference to thefollowing detailed description when considered in connection with the accompanying drawings, wherein:[OH] FIG. 1 is a schematic of a measurement system, according to one embodiment of the present disclosure;

[0012] FIG. 2 is an illustration of a measurement system, according to one embodiment of the present disclosure;

[0013] FIG. 3 is an illustration of a head circumference measurement device, according to one embodiment of the present disclosure;

[0014] FIG. 4 is an illustration of a head circumference measurement device, according to one embodiment of the present disclosure;

[0015] FIG. 5 is an illustration of a head circumference measurement device, according to one embodiment of the present disclosure;

[0016] FIG. 6 is an illustration of a head circumference measurement device, according to one embodiment of the present disclosure;

[0017] FIG. 7 is an illustration of a length measurement device, according to one embodiment of the present disclosure;

[0018] FIG. 8 is an illustration of a length measurement device, according to one embodiment of the present disclosure;

[0019] FIG. 9 is an illustration of a weight measurement device, according to one embodiment of the present disclosure;

[0020] FIG. 10 is a schematic of a weight measurement device, according to one embodiment of the present disclosure;

[0021] FIG. 11 is a pressure distribution map, according to one embodiment of the present disclosure;

[0022] FIG. 12A is an illustration of a measurement system, according to one embodiment of the present disclosure;

[0023] FIG. 12B is an illustration of a measurement system, according to one embodiment of the present disclosure;

[0024] FIG. 13A is an illustration of a measurement system, according to one embodiment of the present disclosure;

[0025] FIG. 13B is an illustration of a measurement system, according to one embodiment of the present disclosure;

[0026] FIG. 14 is an illustration of a measurement system, according to one embodiment of the present disclosure;

[0027] FIG. 15 is an illustration of a growth chart, according to one embodiment of the present disclosure;

[0028] FIG. 16 is a schematic of a measurement system, according to one embodiment of the present disclosure;

[0029] FIG. 17 is a schematic of a measurement system, according to one embodiment of the present disclosure;

[0030] FIG. 18A is a growth chart, according to one embodiment of the present disclosure;

[0031] FIG. 18B is a growth chart, according to one embodiment of the present disclosure;

[0032] FIG. 18C is a growth chart, according to one embodiment of the present disclosure;

[0033] FIG. 18D is a growth chart, according to one embodiment of the present disclosure;

[0034] FIG. 19A is a growth chart, according to one embodiment of the present disclosure;

[0035] FIG. 19B is a growth chart, according to one embodiment of the present disclosure;

[0036] FIG. 20 is a growth chart, according to one embodiment of the present disclosure;

[0037] FIG. 21 is a probability distribution of length measurements, according to one embodiment of the present disclosure;

[0038] FIG. 22 is a graph of medical condition probabilities, according to one embodiment of the present disclosure;

[0039] FIG. 23 is a schematic of a method for determining medical condition probabilities, according to one embodiment of the present disclosure;

[0040] FIG. 24 is a growth report, according to one embodiment of the present disclosure; and

[0041] FIG. 25 is a method for generating a growth report, according to one embodiment of the present disclosure.DETAILED DESCRIPTION

[0042] The present disclosure includes embodiments of various forms. Specific embodiments are described in detail and depicted in the drawings, with the understanding that the present disclosure serves as an exemplification of the principles of the invention. It is not intended to restrict the invention solely to what is illustrated and described herein. It should be fully recognized that the different teachings of the embodiments discussed below may be utilized separately or in any suitable combination to achieve desired results. The various features and characteristics described in greater detail below will be readily apparent to those skilled in the art upon reading the following description of illustrative embodiments of the disclosure, and by referring to the accompanying drawings.

[0043] The terms “a” or “an”, as used herein, are defined as one or more than one. The term “plurality”, as used herein, is defined as two or more than two. The term “another”, as used herein, is defined as at least a second or more. The terms “including” and / or “having”, as used herein, are defined as comprising (i.e., open language). Reference throughout this document to "one embodiment", “certain embodiments”, "an embodiment", “an implementation”, “an example” or similar terms means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. Thus, the appearances of such phrases or in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments without limitation.

[0044] In one embodiment, the present disclosure provides systems, methods, and devices for measuring the physical characteristics of a person. In one embodiment, the present disclosure provides systems and methods for measuring, monitoring, and analyzing a person’s growth, including taking measurements of the length, weight, and head circumference of a person, and monitoring, analyzing, and reporting a person’s growth according to the measurements.

[0045] Measurements of a child’s dimensions (e.g., length, weight, head circumference) can be graphed over time individually or in combination in a growth curve to indicate a rate of development. A growth curve can be compared to aggregated data that reflects average or expected growth and development of children over time. For example, the World Health Organization(WHO) Child Growth Standards (CGS) include growth curves for length / height for age, weight for age, weight for length / height, body mass index (BMI) for age, head circumference for age, etc.A child whose growth deviates from the WHO CGS may require further attention for medical conditions and / or or environmental factors that are affecting the child’s growth.

[0046] Traditional measurement systems can be inconsistent and inaccurate for measuring children and tracking their growth. There is a lack of repeatability in traditional measurement systems, and some users may be unaware of the correct way of obtaining a child’s dimensions. It can also be difficult to measure children due to their size and frequent movement. There is a need for automating measurement of children using tools that are adapted for children’s bodies. In addition, there is a need for better systems for graphing a child’s measurements for easy and accurate interpretation and identification of potential abnormalities and issues, including, but not limited to, macrocephaly, microcephaly, short stature, obesity, or being underweight, crossing or not crossing into a centile, etc.

[0047] Misinterpretation of a growth curve, especially in the context of WHO growth curves, can lead to misdiagnosis, including false positives and false negatives. For example, not all patients with macrocephaly or interval crossing of percentiles across different growth curves have a growth disease, and some patients without obvious and dramatic growth patterns may have a growth disease that is missed. Even when a pediatrician or care provider possesses expertise, parents whose infant's growth is measured at the pediatrician's office are not provided with a clear summary report. Currently, there is no standard way for parents or medical providers to receive an interpretation of a child’s measurements or growth curves, nor is there a standard procedure for indicating a course of action (e.g., referral to a specialist) when measurements raise clinical concern. These limitations underscore the prevailing deficiencies in the current methodology. The present disclosure provides systems, methods, applications, and tools for measurement and reporting that address these unmet needs.

[0048] FIG. 1 is a schematic of a smart scale measurement device or measurement system 100 according to one embodiment of the present disclosure. The measurement system 100 includes a platform 110 configured to provide support for a patient (e.g., a child) placed in a horizontal position on the platform. The platform 110 can include a length measuring device 111 for measuring the length of the child placed thereupon. Additionally, the measurement system 100 can include a weight measurement device 120. The weight measurement device 120 can be operatively coupled to the platform 110. The weight measurement device 120 is configured to measure the weight of the child while the child is positioned horizontally on the platform 110. The measurement system 100 can further include a head circumference measurement device 130. The head circumference measurement device 130 can be operatively coupled to the platform and can be configured to measure the largest circumference of the head of the child when the child is positioned horizontally on the platform. In one embodiment, the measurement system 100 can include an integration module 140. The integration module 140 can be configured to receive data from at least one of the length measuring device 111, the weight measuring device 120, and / or the head circumference measuring device 130. In one embodiment, the integration module 140 can be configured to process the received data.

[0049] In one embodiment, the system can include an interface 150 configured to display the processed data obtained by the integration module 140 via an output interface 151. In one embodiment, the interface 150 can further include an input interface 152, which can provide various ways for a user (e g., a medical professional) to interface with the measurement system 100. For example, the interface 150 can include various interface elements (e.g., a touch screen having various graphical user interface (GUI) elements, buttons, levers, or any other suitableelements) for the user to provide requests to the measurement system 100 or to input information into the measurement system 100, as further described below.

[0050] The measurement system 100 can improve the efficiency and accuracy of measurement and interpretation of child growth for continuous monitoring. In one embodiment, the measurement system 100 can measure children between the ages of 0-2 years. In one embodiment, the measurement system 100 can measure children older than two years old. The measurement system 100 can measure pre-term and full-term children. In one embodiment, the measurement system 100 can determine growth parameters (e.g., dimensions and / or metrics based on dimensions of a child) that can be compared with World Health Organization (WHO) growth data (e g., growth curves), which can be used to diagnose disease and formulate treatment strategies through monitoring, analyzing, and reporting child growth.

[0051] The WHO growth curves require significant expertise to interpret. There are a number of comparisons and metrics that be indicative of growth issues. For example, a baseline analysis of a child’s head size can include determining whether the circumference is greater than two standard deviations above a mean head circumference or less than two standard deviations below the average head circumference. Macrocephaly can be defined as a condition in which the head circumference is greater than two standard deviations above a mean and / or in the 97th-98thcentile. Microcephaly can be defined as a condition in which the head circumference is less than two standard deviations below a mean and / or in the 2lld-3ldcentile. The mean and centile circumferences are based on the age of the child.

[0052] For interval analysis, the rate of growth is very important to consider. In general, a child’s growth over time can follow a trajectory that can be graphed as a growth curve. The growth curve can fall within a percentile for standard growth curves (e.g., WHO growth curves). When a childgrows abnormally quickly or abnormally slowly, the trajectory of their growth curve can change dramatically and can cross into higher or lower percentiles rather than following an expected path within the same percentile. If a measurement (head circumference, length, or weight) crosses two major percentiles (e.g., 5th, 10th, 25th, 50th, 75th, 90th, 95thpercentiles) on the WHO curves, it is recommended that pediatricians consider closer inspection, and if there is significant acceleration, a referral to a specialist may be needed. Unfortunately, the exact period of time or interval within which “crossing two percentiles” is problematic has not been defined, and there are difficulties with accurately determining when and whether a growth curve crosses two percentiles. Moreover, crossing two percentiles is not the only metric for assessing a growth curve. A varying a growth curve can be compared to standard deviations to determine whether the growth is a cause for concern. The likelihood of urgent concern when comparing a patient’s growth curve with a standard growth curve can be easily and accurately conveyed according to the systems and methods of the present disclosure.

[0053] In one embodiment, the measurement system 100 offers a tool for triage alerting when a patient’s growth curve deviates from standard growth curves and for predicting a type of growth issue that may cause the deviation based on the patient’s dimensions. For example, if a patient has macrocephaly (a large head) and an interval velocity (rate of change in dimension over time within an interval of time, e.g., an interval corresponding to the patient’s age) that is indicative of extreme head growth, the patient may have hydrocephalus. If a patient has extreme macrocephaly but stable head growth, the patient is more likely to have a neurogenetic disorder. The system can be used therefore as a triage tool to decide whether to refer a patient to neurosurgery (e.g., for a patient with interval hydrocephalus) versus genetics (e.g., for a patient with significant macrocephaly but normal interval growth). In addition, when patients present with intermediate macrocephaly, themacrocephaly (large head) is more likely familial or benign, and the measurement system 100 can suggest measuring parental head circumferences as the next step. In one embodiment, the measurement system 100 can determine and / or output a designation of a dimension or growth as being extreme, intermediate, mild, stable, etc.

[0054] The measurement system 100 can measure dimensions of a patient including the length, weight, and head circumference of the patient using the length measurement device 111, the weight measurement device 120, and the head circumference measurement device 130, respectively. In one embodiment, the measurement devices of the measurement system 100 can provide automated digital measurements and can simultaneously and accurately measure length, weight, and head circumference. The measurement data can then be plotted with historical measurement data as growth curves. In one embodiment, the growth curves can be overlaid on standard growth curves and interval velocity curves for each metric. The standard growth curves and interval velocity curves can include WHO curves and additional or alternative clinically relevant curves. The standard growth and interval velocity curves can include curves for healthy children, for children with abnormal growth patterns, or for children with one or more shared characteristics, e.g., genetic factors, location, medical condition, environmental condition, demographic characteristic. Comparing a patient’ s growth curve to standard growth curves can be critical for detecting growth- related diseases and conditions, as well as malnutrition, obesity, short stature, too tall stature, microcephaly, macrocephaly, being overweight, and being underweight simultaneously while a patient is measured. Furthermore, the measurement system 100 can be used to establish a common measurement baseline for a patient to reduce measurement error and help identify more subtle growth abnormalities.

[0055] In one embodiment, the measurement data and analytical results obtained by the measurement system 100 can be uploaded to electronic medical records (EMR) and / or a database (e.g., a cloud-hosted external database) to store and obtain the overall growth pattern. A growth pattern can include change in different dimensions over time in parallel or in sequence with each other. For example, if a patient has a relatively large head and low weight with interval weight deceleration (slower weight gain or weight loss) followed by length deceleration (slower growth in height), the patient is most likely suffering from malnutrition. If a patient has microcephaly, is underweight, and is short with steady interval growth but remains small in all dimensions, the patient could be more likely to have a genetic or syndromic etiology. If a patient is extremely tall, this could be more likely a disorder of connective tissue such as Marfan syndrome. Once again, depending on the severity of the deviation, short or tall stature may be familial. However, at extreme deviations, it can be more likely that both the parent and child carry a genetic disorder. Therefore, the system can triage patients by medical risk based on growth patterns for multiple dimensions.

[0056] The measurement data obtained by the measurement system 100 can be used to determine various medical conditions including the conditions that can cause macrocephaly, microcephaly, head acceleration, or head deceleration, skeletal dysplasia, limb length discrepancy, being overweight, being underweight, malnutrition, and / or obesity. In one embodiment, the measurement system 100 can be used to analyze whether the child is at risk for other conditions that can affect growth, including tumors, cysts, trauma, accumulation of blood, infection, injuries, or genetic disorders. Furthermore, the interface 150 of the measurement system 100 can be used to summarize findings and abnormalities related to growth pattern and intervals and report the findings and abnormalities. In one embodiment, the measurement system 100 can provide growthinformation in a growth screening report. The measurement system 100 can provide reassurance for normal growth and risk assessment growth abnormalities based on a degree of abnormality and stratified (zoned) risk levels. The risk assessment can be based on a deviation from a normal range.

[0057] Severe growth abnormalities are more likely to indicate a serious medical problem. For example, patients with skeletal dysplasia are usually three standard deviations below the mean for a measurement, which can be flagged as being within a high-risk zone of deviation. The interval velocity can be slow but steady, and these patients can remain underdeveloped (small) in all measurements from birth. In one example, a patient can have a length within a low-risk zone but can acquire a new cause of growth deceleration. The deceleration in growth within an interval can be flagged as being in a high-risk zone based on the rate of deceleration.

[0058] The measurement system 100 can be used to measure the head circumference, weight, and body length of a subject electronically and analyze growth patterns, which provides the advantages of increasing the accuracy of measurements as well as provide growth data in real time. In one embodiment, the measurement system 100 can generate an alert when a patient’s dimensions are outside of a normal range. If the patient does not actually appear to be outside of a normal size range, the alert can encourage a user to re-measure the patient, thus reducing or eliminating the effect of measurement errors. In one embodiment, the measurement system 100 can measure each limb (e.g., each leg) individually and can detect and report limb length discrepancies, which can be medically significant.

[0059] FIG. 2 is a top view of the platform 110 of the measurement system 100 according to one embodiment of the disclosure. The platform 110 can include a flat or approximately flat horizontal surface having a length LN and a width WD. A patient can be placed on the horizontal surface. In one embodiment, the platform 110 can include raised sides (e.g., side walls) for preventing a childfrom rolling off the horizontal surface. In one embodiment, the platform 110 can form a surface of a bed, a crib, a mat, etc. In one embodiment, the platform 110 can include a soft surface to provide comfortable support for the patient’s body. The soft surface can be formed from an anti-biofouling material (e.g., a fluoropolymer) or have an anti-biofouling coating (e.g., copper-based coatings, silicon-based coatings, zinc oxide coatings, silver-based coatings, polytetrafluoroethylene coatings, etc.).

[0060] As shown in FIG. 2, a patient can be positioned horizontally (lying down) onto the platform 110, such that the head of the patient is placed on a head support 131. The head support 131 can be a flat surface and can be cushioned. In one embodiment, the head support 131 can be a raised platform to elevate the patient’s head and keep the patient’s neck straight. The head support 131 can include a head circumference measurement device 130. The length measurement device 111 can include a headboard 115. The headboard 115 can be positioned in contact with the top of the patient’s head. In one embodiment, the position of the headboard 115 along the length of the platform can be adjustable. The length measurement device 111 can include a footboard 11 IB. The footboard 11 IB can be positioned at the feet of the patient when the patient is positioned horizontally on the platform 110. In one embodiment, the position of the footboard 11 IB along the length of the platform can be adjustable. In one embodiment, the headboard 115 and the footboard 11 IB can be mounted on a track or rail running along the length LN of the platform, wherein the headboard 115 and the footboard 11 IB can slide along the track or rail. The headboard 115 and the footboard 11 IB can be mounted on a shared track or separate tracks. The distance between the headboard 115 and the footboard 11 IB can be used to determine the length L of the patient. In one embodiment, the footboard 11 IB can be positioned along the body of the patient to determine a distance between the top of the patient’s head and any body part or feature of thepatient, e.g., the chin, the torso. Similarly, the headboard 1 15 can be positioned along the body of the patient to determine a length of any part of the patient’s body that is between the headboard 115 and the footboard 11 IB.

[0061] FIG. 3 is an illustration of a measurement system 800 having a platform 810 and a head circumference measurement device 830. The head circumference measurement device 830 can include a head circumference tape 835 attached to a head support 831. The head support 831 can include a covered cutout or shutter 831 A, wherein the head circumference tape 835 can be threaded through the covered cutout or shutter 831 A to be secured in place. The cutout 831 A can be covered with a panel that is attached to a hinge on one side of the cutout 831 A. The panel can rotate around the axis of the hinge to open the cutout 831 A so that the tape 835 can be threaded through the cutout. A headboard 815 can be positioned at the top of the head support 831. The head support can be flat, curved, cushioned, etc.

[0062] Measuring a patient’s head circumference has historically been achieved by using a fabric clothing tape measure wrapped around the largest part of the head, similar to how a tailor measures someone's waist. This method can be prone to error when measuring an uncooperative patient, and the manual nature of wrapping the tape measure around the head can lead to dramatic differences in measurement. The head circumference measurement device 830 described herein can reduce measurement error and improve precision of measurement.

[0063] FIG. 4 is an illustration of the underside of the head circumference measurement device 830. Portions of the head circumference measurement device 830 can be located on the underside of the head support 831 and inside the body of the platform. The head circumference measurement device 830 can include a head circumference measuring tape 835, a head support 831 with a first covered cutout 831 A and a second covered cutout 83 IB, a multiturn encoder 833, and a spring-loaded cartridge 834. The tape 835 can be spooled in the spring-loaded cartridge 834. When a pulling force is applied to the tape 835, the tape 835 can unspool from the cartridge 834 and the spring can extend. When the pulling force is no longer applied to the tape 835, the spring can contract to its original state, causing the tape 835 to automatically retract. In one embodiment, a patient’s head can be placed on the head support 831 and the tape 835 can be unspooled and / or retracted to wrap snugly around the patient’s head. The tape 835 can be exposed at the top surface of the platform via the cutouts 831 A, 83 IB. In one embodiment, the spring-loaded cartridge 834 and the encoder 833 can slide in one or more dimensions along the underside of the head support 831 to adjust the position of the tape 835 at the top surface of the platform.

[0064] The spring-loaded cartridge 834 can be connected via a shared axle to the encoder 833. The encoder 833 can be an absolute multitum rotary encoder, including at least one rotary sensor. The sensors of the encoder can rotate along with the axle of the spring-loaded cartridge, which rotates when the tape 835 is unspooled and spooled. The sensors can output an angle of rotation, e g., as a 14-bit binary value. When the encoder 833 is a multiturn encoder, the angle can be greater than 360° if a sensor makes one or more full rotations.

[0065] The angle of rotation of the sensor can be converted to an unspooled length of the head circumference measuring tape 835. The unspooled length can correspond to a head circumference for a head that is enclosed (wrapped) by the measuring tape 835. In one embodiment, the angle of rotation can be converted to a head circumference via a calibrated lookup table. The calibrated lookup table can map angles of rotation of the one or more rotary sensors to lengths of the measuring tape 835 that are unspooled in order to generate those angles of rotation. The calibrated lookup table can be generated using one or more validated circumference measurements. In oneembodiment, the encoder 833 can include a serial peripheral interface (SPI) for transmitting data, e.g., rotation data or circumference data, to the interface module 140.

[0066] FIG. 5 is an illustration of a patient’s head placed on a head support 931 according to one embodiment of the present disclosure. In one embodiment, a head circumference measurement device 930 can be separate from the head support 931. For example, as illustrated in FIG. 5, the head circumference measurement device 930 can include a measurement tape 935 that can be wrapped around the patient’s head on top of the head support 931. The head circumference measurement device 930 can include an encoder 932, the encoder 932 being similar to or the same as the encoder 833 described with reference to FIG. 4. The head circumference measurement device 930 can be more mobile and can be used independently of the head support 931 and surrounding measurement system.

[0067] FIG. 6 is an illustration of the head circumference measurement device 930. The head circumference measurement device 930 can include the measurement tape 935 spooled in a cartridge around an axle 933. The axle 933 can be shared with one or more rotary sensors of the encoder 932. In one embodiment, the measurement tape 935 can be unspooled from one side of the cartridge or from two sides of the cartridge. In one embodiment, two ends of the measurement tape 935 can meet at a seam 936. In one embodiment, the two ends of the measurement tape 935 can be attached to each other at the seam 936 to secure the measurement device 930 on the patient’ s head. The unspooled length of the one or two ends of the measurement tape 935 can be calculated based on the rotation of the encoder 932 to determine the circumference of the patient’s head.

[0068] FIG. 7 is an illustration of a measurement system 200 including a platform 211, according to one embodiment of the present disclosure. The platform 211 can include one or more raised side walls 214A, 214B to enclose a patient. The measurement system 200 can include a headcircumference measurement device 230 on a head support 231 and a headboard 215 positioned at the top of the head support 231. The position of the headboard 215 can be fixed or can be adjustable. The measurement system 200 can include one or more force sensors 220 embedded in, on top of, or otherwise coupled to the platform 211. In one embodiment, the one or more force sensors 220 can be load cells.

[0069] The measurement system 200 can include a right leg measurement assembly 212 and a left leg measurement assembly 213. The right leg measurement assembly 212 can include a footboard 212C. The footboard 212C can be a paddle that is mounted on a belt 212B and / or on the wall 214A of the platform. In one embodiment, the footboard 212C can be mounted on the belt 212B and / or on the wall 214A of the platform via a bracket 212D. The bracket 212D can fit around the wall 214A and can be attached to the belt 212B. The footboard 212C can slide along the belt 212B. The right leg measurement assembly 212 can include an encoder 212A, e.g., an absolute multiturn rotary encoder. The encoder 212A can be configured to determine a distance between the headboard 215 and the right footboard 212C. For example, when the footboard 212C is moved away from the encoder 212A, a rotating element of the encoder 212A can rotate at a fixed speed corresponding to the displacement of the footboard 212C (e.g., a number of rotations per unit of displacement). The encoder can convert the rotation of the rotating element to a distance between the headboard 215 and the footboard 212C. The distance can correspond to the height of the patient as measured from their right foot. The encoder 212A can include a serial peripheral interface (SPI) for communicating a distance between the headboard 215 and the right footboard 212C to the integration module 140.

[0070] The left leg measurement assembly 213 can include a footboard 213C. The footboard 213C can be a paddle that is mounted on a belt 213B and / or on the wall 214B of the platform. In oneembodiment, the footboard 213C can be mounted on the belt 213B and / or on the wall 214B of the platform via a bracket 213D. The bracket 213D can fit around the wall 214B and can be attached to the belt 213B. The footboard 213C can slide along the belt 213B. The right leg measurement assembly 213 can include an encoder 213A, e.g., an absolute multiturn rotary encoder. The encoder 213 A can be configured to determine a distance between the headboard 215 and the left footboard 213C. The distance can correspond to the height of the patient as measured from their left foot. The encoder 213A can include a serial peripheral interface (SPI) for communicating a distance between the headboard 215 and the left footboard 213C to the integration module 140.

[0071] FIG. 8 is an illustration of a leg length measurement mechanism, including a bearing standoff 311, a bearing 312, a pulley 313, a belt 314, a carriage 315, a track 316 and a rotary encoder 317. The leg measurement mechanism can be used as the right leg measurement assembly 212 and / or the left leg measurement assembly 213.

[0072] On the top (upper) side of the platform, two footboards are attached to brackets that extend over the side walls of the platform and then into the body of the platform. The internal electronics can be protected within the body of the platform. Each bracket can be connected to a tracked belt system 314 that runs along the length of the platform. The teeth in the belt 314 can prevent slipping or snagging from the large torque imparted when moving the paddle. The belt 314 can be coupled to a pulley as a rotating element. Other mechanisms, such as linear tracks, slide rails, etc. are also compatible methods and structures for moving the paddle. At one end of the belt, the toothed axle wheel of the pulley 313 shares a shaft with a multiturn absolute rotary encoder 317. Thus, when the foot paddle moves back and forth, the linear motion of the belt is converted to rotary motion of the pulley and concentric encoder. The angle of rotation of the rotary sensors in the encoder 317 can be converted into a displacement of the foot paddle along the belt and / or a distance betweenthe foot paddle and the headboard via a previously calculated calibration as described herein with reference to the head circumference measurement device. The distance between the foot paddle and the headboard can be used as a length measurement of the patient.

[0073] FIG. 9 illustrates an embodiment of a measurement device or measurement system 700 having a weight measurement device 720. The features of the measurement system 700 can combined with any of the measurement systems and features thereof described herein. For example, in one embodiment, the measurement system 100 can include the weight measurement device 720 illustrated in FIG. 9. The measurement system 700 can be similar in structure and / or in function to the measurement systems 100-600 described herein. In one embodiment, the weight measurement device 720 can be positioned below and adjacent to a platform 710. In one embodiment, the weight measurement device 720 can be tens of centimeters in length (e.g., 80, 90, 100, 110, etc. centimeters in length). In one embodiment, the weight measurement device 720 can have a length ranging between approximately 40 to approximately 120 centimeters. In one embodiment, the weight measurement device 720 can be tens of centimeters in width (e.g., 20, 30 40, 50, etc. centimeters in width). In one embodiment, the weight measurement device 720 can have a width ranging between approximately 20 to approximately 60 centimeters.

[0074] In one embodiment, the weight measurement device 720 can include one or more load cells configured to determine the weight of a patient placed horizontally on a weigh table or platform 10. Multiple load cells can be useful in determining the total weight of a patient’s body and the weight distribution of a patient’s body. For example, weight values determined by different load cells can be combined to obtain the total weight of the patient.

[0075] FIG. 10 is a schematic of a weight measurement device, according to one embodiment of the present disclosure. In one example, as shown in FIG. 10, several (e.g., four) load cells supportthe entire platform 710 at equally spaced locations under the platform 710. One or more load cells can include a flexing metal bar coupled to a strain gauge sensor, which is controlled by a load cell amplifier board. The load cell amplifier board can receive strain gauge data from the strain gauge sensor and can convert the strain gauge data to weight data. The load cell amplifier board can apply a calibration to the strain gauge data or weight data to filter out noise associated with the movement of the patient on top of the strain platform 710. In one embodiment, the weight measurement device 720 can apply a tare to the scale and can apply filtering to the strain gauge data or weight data to smooth the data.

[0076] It should be noted that any number of load cells can be used to determine the overall weight of the patient, and any suitable data processing methods can be used to process the weight data and / or filter the weight data, e.g., to remove noise associated with the movement of the patient (e.g., a low-pass filter, an averaging filter, etc.). In one embodiment, different data processing methods can be applied to data obtained from different load cells. For example, the first weight data from a first set of load cells located in the proximity of a patient’s head can be processed using a first data processing method, while the second weight data obtained from a second set of load cells located in the proximity of patient’s legs can be processed using a second data processing method. For instance, the first weight data can be averaged over a first time window (e.g., over a few seconds, a few tens of seconds, a minute, and the like), while the second weight data can be averaged over a second time window different from the first time window. For example, the second time window can be longer than the first time window, e.g., tens of seconds, a minute, a few minutes, and the like. In one embodiment, the first weight data from the first set of load cells can be filtered using a first type of data filter, while the second weight data from the second set of load cells can be filtered using a second type of data filter. In one embodiment, load cells of the weightmeasurement device 720 can be combined into sets, subsets and the like, and data obtained from each set, subset, and the like may be processed using any suitable method. For example, in one implementation, load cells towards the center of the platform 710 can form a first set of load cells and can be processed using a first data processing method, while load cells at the sides of the platform 710 can form a second set of load cells and can be processed using a second data processing method.

[0077] FIG. 11 is an illustration of a pressure distribution map 621 that can be generated based on the weight measurement device 720, according to one embodiment of the present disclosure. Due to the utilization of multiple load cells, the weight measurement device 720 can be configured to generate a pressure distribution map 621 of the patient positioned horizontally on the platform 710. The different pressures can be depicted by pressure contours 721. The pressure distribution map 621 can enable the assessment of weight distribution across a patient’s body.

[0078] The weight measurement system 700 can be configured to measure the weight of any patient that can fit on the platform 710. For example, a patient can be a newborn infant, a toddler, or an older child. In one embodiment, weight measurement systems described herein can be used to weigh children from 0 to 20 kg. In one embodiment, the weight measurement system 700 can be used for measuring various physical characteristics of a teenager or an adult patient.

[0079] FIG. 12A is an illustration of a measurement system 100, according to one embodiment of the present disclosure. The measurement system 100 can include an overhang 6510 extending upwards from the platform 1 10. The overhang 6510 can include a vertical wall 651 1 along the length of the platform 110 and extending upwards from the platform 110 and an angled cover 6512 extending from the vertical wall 6511. The angled cover 6512 can cover any portion of the platform 110, including the entire platform 110. The angled cover 6512 can include a lip 6515, the lip 6515being approximately parallel to the platform 110. In one embodiment, the overhang 6510 can be fixed in place. In one embodiment, the position of the overhang 6510 can be adjustable. For example, the vertical wall 6511 can be coupled to the platform 110 via a rotatable hinge. In one embodiment, the vertical wall 6511 can be coupled to the angled cover 6512 via a rotatable hinge or joint. The angle of the cover 6512 relative to the vertical wall 6511 can be adjusted. FIG. 12B is top view of a measurement system 100 including the overhang 6510, according to one embodiment of the present disclosure.

[0080] FIG. 13A is an illustration of a measurement system 100 having an overhang 6510, according to one embodiment of the present disclosure. In one embodiment, one or more cameras 655A, 655B, 655C, 655D can be attached to measurement system 100. In one embodiment, one or more cameras 655A, 655D can be attached to the internal walls of the platform 610. In one embodiment, one or more cameras 655B, 655C can be attached to the overhang 6510. In one embodiment, the one or more cameras can be configured to approximate the volume of a person's body. For example, the one or more cameras can capture image data of a patient, wherein the image data can be used to determine physical parameters of a patient’s body. The physical parameters can include, for example, an approximate shape, size, and / or volume of the patient’s body. In one embodiment, the image data can be used to determine physical parameters of parts of the patient’s body. In one embodiment, the image data and / or dimensions of a patient can be input into a body shape prediction algorithm to determine the overall shape and volume of the patient’s body. In one embodiment, the body shape prediction algorithm can take into account characteristics of a patient such as their age, gender, race, or any other relevant factors that can aid in accurately modeling a patient’s body shape. In one embodiment, physical parameters such as a body mass index (BMI) can be determined based on the volume and weight of a patient.

[0081] FIG. 13B is an illustration of a measurement system 600 having an overhang 6 10 and one or more cameras 655B, 655C, according to one embodiment of the present disclosure. In one embodiment, the overhang 6510 can include a panel 651. In one embodiment, the panel 651 can be an illumination panel including one or more lights. In one embodiment, the panel 651 can be a transparent panel (window).

[0082] In one embodiment, the measurement system can include graphical information that can be printed, inserted, or otherwise attached to the measurement system 100 for analyzing the physical characteristics of a patient. For example, FIG. 14 shows a growth chart 1670 placed over a surface of a platform of a measurement system 100. FIG. 15 is an illustration of the growth chart 1670, according to one embodiment. The growth chart 1670 can include a scale indicating expected length measurements (e.g., based on WHO standards) for female and male patients at different ages. The growth chart 1670 can also indicate the expected range of length measurements for female and male patients at each age. Expected measurements for different genders can be differentiated by color or any visual indicator, including text. The expected ranges can be illustrated as actual length values on the growth chart 1670. The lengths of the growth chart are represented by markings arranged in a staircase formation. Each marking indicates a length of a patient of a particular age and a particular gender. For example, marking 1671 indicates that a 13- month-old girl is expected to be in a range of about 70 to about 80.5 centimeters, while a 13- month-old boy is expected to be in a range of about 72 to about 82 centimeters. Thus, the growth chart 1670 can be easily used for female and male patients within a range of ages (e.g., 0 to 2 years).

[0083] A patient can be placed horizontally on their back on top of the growth chart 1670 with their head at the 0 cm mark and their body extending across the length of the growth chart 1670.The growth chart 1670 can indicate a length of a patient based on the position of the patient’s feet relative to the scale of the growth chart when the patient is placed on the chart. In this manner, the patient’s length can easily be compared to the expected length for the patient’s age and gender based on a visual inspection. The growth chart 1670 also indicates whether the patient’s length falls within or outside of an expected range. When using the growth chart 1670, a user does not have to first determine the patient’s length and then separately plot the length on a growth curve, which may or may not be to scale, to compare the length to standard values. The growth chart 1670 can be used to simultaneously measure a patient’s length and determine whether the patient’s length is normal or abnormal for patients of various ages and genders. Using the growth chart 1670 while measuring a patient can improve measurement accuracy because any abnormalities in the measurement will be indicated by the growth chart in real time while the patient is being measured. A patient can then be repositioned or remeasured when the abnormal length measurement does not match a visual assessment of the patient. In one embodiment, a patient can be measured over time, and each length measurement can be indicated on the growth chart 1670 to form a growth curve. The visualization of historical length measurements can be used to determine when growth acceleration or deceleration occurs and for how long the acceleration or deceleration persists.

[0084] As described above, the growth curve 1670 can be overlaid onto the surface of a platform of a system 100 for determining physical characteristics of a patient, facilitating evaluation of growth and comprehension of whether a patient of a particular age is tracking within the expected length range. In one embodiment, the growth curve 1670 can be rendered as an image suitable for placement on various surfaces, such as a mat, changing pad, tray, medical examination paper, scale, yoga mat, vinyl mat, floor mat, and the like. This growth chart 1670 can empower providers and caregivers to visualize and comprehend a patient’s physical growth trajectory, especiallyduring the patient’s early years. In one embodiment, the age range of the growth curve 1670 can be adjusted. For example, a first growth curve can include expected lengths of patients from 0 to 1 years of age, and a second growth curve can be larger and can include expected lengths of patients from 0 to 2 years of age. In one embodiment, a growth curve can include expected lengths of preterm infants or of patients having a specific growth-related syndrome or genetic condition such as Down syndrome, Williams syndrome, etc.

[0085] FIG. 16 shows an embodiment of a measurement system 1100 that includes an integration module 1140, an interface module 1150, as well as a length measurement device 1111, a weight measurement device 1120, and a head circumference measurement device 1130. As depicted in FIG. 16, the data from the devices 1111-1130 is communicated to the integration module 1140 for further analysis and processing. In one embodiment, the integration module 1140 can include a processor 1141 for processing and analyzing data received from the devices 1111-1130. The processor 1141 can be any suitable processor including processing circuitry, such as an Atm el ATMega328, a Field Programmable Gate Array (FPGA), a system on chip (SoC), a Programmable Intelligent Computer (PIC), or any other appropriate processor. The type of processor 1141 can be selected based on requirements for power, cost, and speed. The processor 1141, along with its associated processing circuitry and connectors, can be located on a printed circuit board (PCB) positioned at any suitable location in the system 1100 (e.g., below the platform of the system 1100). In one embodiment, the processor can include interfaces for interacting with other devices, such as hard drives, universal serial bus (USB) interfaces, and the like. For instance, the processor 1141 can incorporate interfaces for wired or wireless communications (e.g., Bluetooth, NFC, WiFi, Ethernet, and others) with external devices (e.g., tablets, smartphones, laptops, desktops, servers,and similar devices). Additionally, the processor 1 141 can contain a USB converter chip for transmitting data to and from the processor 1141.

[0001] Each of the functions of the described embodiments can be implemented by one or more processing circuits / processing circuitry (may also be referred to as a controller). The one or more processing circuits / processing circuitry may or may not be part of the integration module 1140 and / or the interface module 1151 of FIG. 16. A processing circuit includes a programmed processor (for example, a CPU) as a processor includes circuitry. A processing circuit can also include devices such as an application specific integrated circuit (ASIC) and circuit components arranged to perform the recited functions.

[0086] The processor 1141 can be configured to run any software, including custom firmware that executes various functions for analyzing data from the devices 1111-1130. In one embodiment, the firmware can be coded in Arduino C, C++, Java, or any other appropriate computer language. The role of the firmware can include transmitting the combined data obtained from the devices 1111-1130 in an easy-to-parse format to a connected device over a wired or wireless connection. As an example, the two length measurements for the left and right leg, along with head circumference and weight, can be transmitted in a delimited format: $BGP,ww.www,hh.hhh, 111.11, rr.rrr, CS / r / n, where ww.www represents the decimal weight in kilograms, hh.hhh represents the decimal head circumference in centimeters, and 11.111 and rr.rrr represent the decimal lengths in centimeters of the left leg (11.111) and the right leg (rr.rrr). Herein, the CS can be a checksum, which improves data fidelity. This human-readable format is important in diagnostics.

[0087] In one embodiment, the processor 1 141 can control the power state of the devices 1111 - 1130. For example, the processor 1141 can prevent devices 1111-1130 from collecting data when the patient is not present on the platform of the system 1100.

[0088] The system 1100 can include any suitable electrical power supply (e.g., alternating current (AC) power supply, battery-based power supply, or a combination thereof) for providing electrical power to any of the devices / modules in the system 110 that require electrical power.

[0089] The integration module 1140 can include a data storage device 1142 for storing any suitable data received from the devices 1111-1130. In one embodiment, the data storage device 1142 can be configured to store any other data that can be used for analysis and data processing (e.g., computer instructions, data related to previously performed measurements, and the like). In one embodiment, the processor 1141 and / or the data storage device 1142 of the integration module 1140 can comprise a computer, server, user device, or similar device.

[0090] In one embodiment, the integration module 1140 can transmit data to computer resources 1160 and receive data from the computer resources 1160. The computer resources 1160 can include computers, user devices including mobile phones and tablets, servers, databases, and the like. In one embodiment, a user device can be used to send commands to the integration module 1140 and receive data from the integration module 1140. Further, when the computer resources 1160 include a database, data from the database can be uploaded to the integration module. For example, data related to measurements of children having a particular medical condition can be uploaded to the integration module 1 140. In one embodiment, the integration module 1140 can be configured to access a server, and the server can be configured to interact with other servers or databases.

[0091] In one embodiment, the integration module 1140 can be in wired or network communication with a remote device, such as a user device, computer, or similar computing device used for interacting with the system 100 designed for measuring an individual's physical attributes. For instance, a mobile device can be used to manage system input, observe output, and even configure data presentation. This user-controlled customization extends to how the data is presented. Communication between the remote device and the system can occur through communication protocols such as WIFI, Bluetooth, NFC, and others.

[0092] In one embodiment, a wired connection can link the remote device to the system. The interface module can be used to display measurements such as a child's length, weight, and head circumference in real time. In one embodiment, the interface module can lock and / or store measurement data. These measurements can then be plotted on growth charts and used to generate growth reports and can also be archived in a database. This setup enables users to promptly assess the most recent measurement within the context of previous ones, facilitating the monitoring of a patient’s developmental progress and the early identification of potential concerns.

[0093] In one embodiment, an integration module from any of the embodiments discussed herein (for example, the integration module 1140) can be configured to compare the measurements of a patient of a specific age and gender with aggregated or expected measurements for a patient of the same age and gender. Such measurements can include length, weight, and head circumference, which can be obtained using any of the respective length measurement devices, weight measurement devices, and head circumference measurement devices described herein. In one embodiment, the integration module can compare the measurements to aggregated or expected measurements based on additional characteristics of the patient, such as nationality, race, medicalhistory, etc. In one embodiment, the comparison of measurements can include a comparison of a growth curve or a portion of a growth curve.

[0094] FIG. 17 shows an example embodiment of a measurement system 1200 according to one embodiment of the present disclosure. The system 1200 can include a microcontroller 1241, wherein the microcontroller can include one or more components of the integration module 1140 of FIG. 16. The system 1200 can include a head circumference absolute multiturn encoder 830 having a serial peripheral interface (SPI) for communicating data to / from the microcontroller 1241. The head circumference absolute multiturn encoder 830 can be configured to determine a head circumference of a patient and transmit the head circumference data to the microcontroller 1241 for further processing. The system 1200 can include a right leg absolute multiturn encoder 212A having an SPI for communicating data to / from the microcontroller 1241. The right leg absolute multiturn encoder 212A can be configured to determine the distance between the top of the patient’s head and the patient’s right toe. The system 1200 can include a left leg absolute multiturn encoder 213 A having an SPI for communicating data to / from the microcontroller 1241. The left leg absolute multitum encoder 213 A can be configured to determine the distance between the top of the patient’s head and the patient’s left toe. The system 1200 can include a weight table load cell controller 720 configured to measure a weight of a patient and to communicate the weight data to the microcontroller 1241. The microcontroller 1241 can be powered by an alternating current (AC) or direct current (DC) power source and can include a battery, e.g., a rechargeable battery. In one embodiment, the microcontroller 1241 can exchange data with a serial USB or serial Ethemet / WIFI converter.

[0095] FIGs. 18A-18D are examples of growth curves that can be generated by the integration module or interface module based on measurements by the measurement system for comparisonand assessment of a patient’s growth. FIG. 18A is a growth curve for a female patient’s length from 0-12 months of age. FIG. 18B is a growth curve for a female patient’s weight from 0-12 months of age. FIG. 18C is a growth curve for a female patient’s head circumference from 0-12 months of age. FIG. 18D is a growth curve for a female patient’ s weight given the patient’ s length. The integration module or interface module can generate the growth curves by plotting a patient’s measurements that have been collected at different time points over time. The growth curve for a patient can then be overlayed over standard growth curve data. In one embodiment, the integration module or interface module can determine a position of a patient’s growth curve relative to the standard growth curve data. For example, the integration module or interface module can determine whether a patient’s growth curve follows a normal or abnormal trajectory based on the standard growth curve data. In one example, the integration module or interface module can determine whether a patient’s growth curve crosses two percentile lines, which can be indicative of a growth-related medical condition.

[0096] The standard growth curve data can refer to growth data for healthy patients or growth data for patients with growth-related conditions or risk factors. In one embodiment, the standard growth curve data can refer to growth data for a population having a shared characteristic, such as a demographic characteristic, environment, location, genetics, medical condition, etc. The standard growth data can be retrieved from a single source or from more than one data source. In one embodiment, the integration module or interface module can use machine learning to determine a growth curve and / or to identify growth patterns based on a patient’s growth data. The growth patterns can include an interval velocity or an interval acceleration. In one embodiment, the system 100 can analyze standard growth data to identify patterns. The integration module or interface module can then identify growth patterns in a patient’s data that match patterns of standard growthdata in order to identify a growth -related condition. The integration module or interface module can thus generate a prediction for a growth-related condition that the patient may have based on their growth pattern. In one embodiment, the prediction can include a probability of the condition and / or a severity of the condition. The growth pattern can be based on the patient’s growth (change in a dimension) or based on the patient’s actual measurements. In one embodiment, the integration module or interface module can predict future measurements for a patient based on their growth pattern.

[0097] The growth curves can illustrate ranges of dimensions and a level of medical concern or disease risk associated with each range. In one embodiment, the level of disease risk can be illustrated using a color-coded mechanism. For example, as illustrated in FIGs. 18A-18D, a normal or typical range can be green, a moderately abnormal (too large / too small) range can be yellow, and a severely abnormal (too large / too small) range can be red. The color coding of the ranges can be continued through the entire growth chart so that it is easy to determine where a patient’ s growth curve falls. For example, in FIGs. 18A and 18B, the growth curves for the patient’s length and weight are within a typical range at all data points. In FIG. 18C, the patient’s head circumference is initially larger than expected and within a severe macrocephaly range. The patient’s head circumference continues to grow and reaches an extreme macrocephaly range at seven months of age.

[0098] In one embodiment, the thresholds for typical, mild risk, severe risk, extreme risk, etc. ranges of a dimension can be established based on standard growth curves, e g., WHO growth curves. In one embodiment, the thresholds for the ranges can be based on standard deviations from an average dimension or can be based on percentiles. For example, a typical range for a dimension can be between the 25thand 75thpercentile; a mild risk range can be between a 12thand 25thpercentile or between a 75thand 87thpercentile; a severe risk range can be between a 1stpercentile and a 12thpercentile or between an 87thpercentile and a 97thpercentile; and an extreme risk range can be less than a 1stpercentile or greater than a 97thpercentile. The thresholds can thus be clinically relevant and accurate assessments of a patient’s growth.

[0099] FIGs. 19A and 19B are examples of growth curves for a patient’s weight. In FIG. 19A, the standard growth curves for various percentiles are illustrated as solid lines. The sample growth curve for a patient is illustrated as a dotted line. The weight of the patient is consistently greater than an average weight at each age. However, it is difficult to determine the level of risk associated with the weight of the patient based on the growth curves of FIG. 19A. In FIG. 19B, the standard growth curves are used to determine zones or ranges of weights, including extremely overweight, severely overweight, overweight, typical, underweight, severely underweight, and extremely underweight. The zones are also color-coded, with the high-risk zones (severely overweight and severely underweight) being red, the medium-risk zones (overweight and underweight) being yellow, and the no-risk zones (typical weight) being green. In this manner, it is easy to determine that the patient is consistently severely overweight and that the patient’s growth curve tracks within the severely overweight range. Visualizing the patient’s growth curve relative to the zones defined by standard growth curves can be helpful in determining whether the patient’s growth is accelerating, decelerating, or following a stable trajectory. Visualizing the patient’s growth curve relative to the zones as illustrated in FIG. 19B can make it easier to determine when a patient’s growth curve crosses two centiles, which can be an indication of a medical condition affecting growth.

[0100] FIG. 20 is an example of an interval growth curve that can be generated by the integration module or the interface module. The interval velocity or interval growth velocity of a dimension(e g., change in head circumference over two months) can be graphed as a function of the patient’s age. The interval used to determine the interval velocity can vary, e.g., in months or in years. The integration module or interface module can determine ranges of interval velocities for a dimension corresponding to extreme acceleration, severe acceleration, significant acceleration, average or normal growth, significant deceleration, severe deceleration, and extreme deceleration. In one embodiment, the thresholds for the range can be based on standard deviations or percentiles of standard velocity curves. The standard velocity curves can be for healthy patients or can be associated with growth-related conditions or risk factors. In one embodiment, the zones can be colored to provide an easy visual indication of corresponding risk. In this manner, the velocity of the patient’s growth can be assessed in addition to or in place of the patient’s size at a fixed point in time. The growth chart of FIG. 20 can be particularly useful for identifying growth patterns that may not be as evident on traditional growth charts that display only single measurements at specific ages.

[0101] Interval growth velocity can be used to detect trends such as growth spurts, stunted growth, or abnormal changes in growth patterns, which could indicate underlying health issues. This information can aid in diagnosing and managing conditions that affect a child's growth and development. Interval growth velocity can also be used to monitor conditions where growth is a key indicator, such as certain endocrine disorders or nutritional deficiencies.

[0102] In one example, the growth curves generated by the measurement system 100 can be used for early diagnosis of a baby with rickets. Severe length deceleration is an indication of rickets. A deceleration in growth is typically not detectable by conventional growth screenings until the baby is twelve months of age. The color-coded zones of the growth curves, as presented in FIGs. 18A- 18D, 19B, 20, can be used to easily identify length deceleration and specifically severe lengthdeceleration. Thus, a baby can be diagnosed with rickets between 6-9 months of age, resulting in earlier treatment.

[0103] Expected measurements of patients can be described by a probability distribution based on aggregated patient measurements. The probability distribution can be any suitable probability distribution, such as, for example, a normal probability distribution. An example of a normal probability distribution 1320 for a length of an eight-month-old boy is shown in FIG. 21. A median, expected length of an eight-month-old boy can be Lmed. For instance, Lmedcan be about 70 centimeters. About 50% of eight-month-old boys are expected to be shorter than Lmedand 50% of eight-month-old boys are expected to be longer than Lmed. If a length of a child is within a range of 15% to 85% of all expected lengths for the child’ s age, the length can be considered to be within a relatively normal range and can be given a Z-score between -1 to 1, as indicated in FIG. 21. A Z-score of 0 correspond to a length of a child equal to Lmed. Furthermore, a Z-score between -2 to 2 can be assigned to a length of a child falling within and including 3% of children’s lengths or above or equal to 97% of children’s lengths. A Z-score between -3 to 3 can be assigned to a length of a child falling within and including 0.5% of children’s lengths or above or equal to 99.5% of children’s lengths. Larger Z-scores are assigned for children whose length is less than 0.5% of children’s lengths or more than 99.5%. For example, a Z-score between -4 to 4 can be assigned for a length of a child falling within and including 0.1% of children’s lengths or above or equal to 99.9% of children’s lengths.

[0104] In one embodiment, an integration module (e.g., the integration module 1140) can be configured to calculate a Z-score for a particular measurement and use that Z-score to determine a probability of a medical diagnosis for a patient. For example, FIG. 22 is a graph of the probability (Pl, P2, P3) of a patient having a condition (Cl, C2, C3) given a Z-score for a measurement (e.g.,the length) of the patient. For a medical condition Cl the probability can be Pl , for medical condition C2 the probability can be P2, and for medical condition C3 the probability can be P3. In an example embodiment, if Z = -3 for a head circumference measurement, the medical condition Cl can be microcephaly and the probability Pl of microcephaly can be above 0.6. If the Z-score for a weight measurement is calculated to be -3, the medical condition Cl can be malnutrition, the medical condition C2 can be growth hormone deficiency, and the medical condition C3 can be celiac disease. The probability corresponding to each condition can vary based on how much the weight measurement deviates from an expected (e.g., median) weight. It should be noted that the integration module 1140 can be configured to calculate probabilities for any suitable number of medical conditions. In one embodiment, the integration module 1140 can provide recommendations for a medical professional regarding what type of tests can be performed to confirm a medical diagnosis. In one embodiment, the integration module 1140 can be configured to prompt for and receive additional information such as ethnicity, nationality, diet, video / image data associated with the patient, imaging data (e.g., X-ray scans, CT scans, MRIs, and the like), blood test data, urine test, or any other suitable medical data to further determine the medical diagnosis for the patient.

[0105] FIG. 23 is an illustration of a system for determining a probability of a medical diagnosis. In one embodiment, an integration module can utilize an artificial intelligence (Al) application 1520 for determining probabilities for various medical diagnoses. In one example, the Al application 1520 can receive a data input 1510 which can include a weight measurement, a length measurement, and a head circumference measurement for a patient. Additional data 1512 can be included as a part of the data input 1510. The additional data 1512 can include any suitable medical test data (e g., blood test data) for a patient, any suitable imaging data (e.g., a CT scan, and thelike), or any medical other data related to the patient (e.g., information about previous injuries, illnesses, surgeries or treatments experienced by the patient). The Al application 1520 can be used to determine respective probabilities Pl, P2, P3 for medical conditions Cl, C2, C3 based on a patient’s Z-score(s) for measurements 1510 and additional data 1512.

[0106] In one embodiment, the integration module or interface module can generate a growth curve for a patient and can assess expected versus actual anthropometric measurements of the patient for both baseline measurements and interval growth. While conventional growth curves simply show an overall trend, the interface module can triage the degree of concern based on a general pattern of growth. In one embodiment, as further described below, the interface module can generate a novel report for a risk assessment based on a patient’s measurements, the report including a red-colored indicator, a yellow-colored indicator, or a green-colored indicator. The color of the indicator can represent a level of concern or risk associated with the patient’s measurements, e.g., red for high concern, yellow for medium concern (e.g., an indication to monitor the patient), and green for low concern. This unique interface module can help caregivers and parents triage babies with relevant concerns quickly and accurately.

[0107] The interface module 1150 can generate reports and alerts regarding concerns of a patient’s head circumference, length, and weight and other growth parameters, such as derivative or interval changes. Furthermore, the interface module can receive data from the integration module for providing guidance for disease diagnosis and / or treatment. In one embodiment, generating a report can include generating a growth curve for dimensions including head circumference, length, and weight, comparing the generated growth curves with standard growth curves, analyzing the patient’s growth, comparing the patient’s growth with pathologic patterns (e.g., growth curves or models indicative of disease), and providing guidance for disease diagnosis and / or treatment basedon the comparison between the patient’s growth curves and the pathologic patterns. In one embodiment, the system 1100 can provide real-time automated reporting and risk stratification. The growth curves can include all growth data collected for a patient or portions of growth data collected for a patient. For example, the growth curves can include interval velocity curves of measurements within a specific time period (e.g., age of a patient).

[0108] The automated report can indicate whether a child is at low risk, intermediate risk, or high risk for growth-related conditions such as macrocephaly, microcephaly, short stature, low weight, or a condition that causes growth acceleration or deceleration. In one embodiment, the automated report can be presented by the interface module 1150 via a growth dashboard that offers pattern analysis to guide differential diagnosis. In one embodiment, the interface module 1150 can access and display data from a database that enables collection and analysis of data to improve predictive modeling and incorporate artificial intelligence and tools. The reports can automatically flag macrocephaly (heads larger than considered normal), microcephaly (heads significantly smaller than considered normal), short stature (length lower than normal), underweight, overweight, and / or growth acceleration or deceleration that is abnormal and signifies cause for medical concern. The reports can be used to identify conditions that cause acquired macrocephaly including hydrocephalus, brain tumors, fluid filled cysts, or other conditions that cause dilation of the fluid filled areas of the brain, and genetic conditions or infection or injury or trauma that cause acquired head deceleration. The report can be particularly applicable for analyzing hydrocephalus or risk of increased fluid in the brain.

[0109] The integration module or interface module can categorize a level of severity of a growth abnormality based on a deviation of the patient’s dimensions from average values. Growth abnormalities or large or small sizes can be familial but can also be cause for medical concern,especially in severe cases with greater standard deviation from the mean. In one embodiment, the level of severity can be determined based on the patient’s medical history. For example, if certain diagnostic codes in a patient’s medical history are associated with smaller heads, then the head of a patient for a particular syndrome may in fact be normal and may not trigger acute concern. Conditions that can cause acquired abnormal head growth acceleration can include, but are not limited to, tumors, fluid-filled cysts, trauma, bleeding, and infection. Conditions that can cause acquired decreases in head growth with a slower rate than expected of head growth can include, but are not limited to, infection, brain injuries, genetic disorders such as Rett syndrome, Down syndrome, and other chromosomal disorders.[HO] In one embodiment, the integration module or interface module can provide real-time analysis of growth patterns. In one embodiment, growth patterns can be analyzed for a group of patients sharing one or more traits related to demographic data, geographic data, and / or lifestyle data. For example, growth patterns can be analyzed within ethnic groups or within zip codes or other geographic areas based on geo-mapping. Collecting and analyzing aggregate growth data based on these factors can be useful for identifying concerns within a geographic region or a demographic. In one embodiment, the integration module or interface module can be used to detect potential healthcare disparities based on indicators such as microcephaly or macrocephaly. For example, if certain zip codes or geo-mapped areas have increased levels of one of the measurements such as derivative changes in growth including head circumference, the system will be able to alert the user. Statistically significant parameters can be generated based on certain mathematical models according to data saved on a server. The server can store aggregate data collected from multiple users in real time.[Hl] In one embodiment, when an individual is screened as positive for abnormal growth, the method and system can be used for characterization of abnormal growth and comprise (1) a step of conveying growth baseline measurements compared to standard and interval measurements in a three-dimensional image; (2) a step of generating risk levels of medical conditions, (3) a step of generating alerts based on the risk levels, and / or (4) a step of risk stratification to guide the decision of whether more urgent specialty care, referral, or non-urgent care is needed. In one embodiment, a more urgent specialty care referral includes neurosurgery and / or neurogenetic referral. In addition, the system can be helpful for neurosurgeons, neurologists, geneticists, and other specialists to automate their processes and make growth assessment faster, more accurate, more consistent, and more efficient.

[0112] The input interface 1151 can receive input from a user, such as a medical service provider. For example, the input can include pressing buttons, interacting with a touch screen, typing on a keyboard, and interacting with a connected device to transmit data wirelessly or via a wired connection to the interface module 1150. It should be understood that any input can also include user gestures, mouse movements, and the like. Further input can include transmitting data to the interface module 1150 such as test data or imaging data for a patient.

[0113] Further, the output interface 1152 can generate any suitable visual, audio, or tactile output. For example, a visual output can include light indicators, a terminal configured to display graphical information, an LCD screen, a touch screen, a smartphone screen, and the like.

[0114] The auditory output aspect of the interface can include a variety of sound signals (such as alarm signals, voice user interface responses, and similar) that are facilitated through speakers, microphones, and related components. Meanwhile, the tactile output facet of the interface caninvolve tactile signals such as vibrations (akin to those found in smartphones) or other forms of haptic or physical feedback.

[0115] Data processed by an integration module (e.g., the integration module 140, 1140) can be processed and reported to a user via an interface module (e.g., the interface module 150, 1150) using any suitable graphical formal. In some cases, the interface module can generate and / or display a “traffic light” report, as illustrated in FIG. 24. The report can include the measurements for the patient, as well as an identification of a range for each measurement (e.g., typical, short, moderate loss / gain, etc.). The measurements can include dimensions (e.g., head circumference, weight, length), metrics based on dimensions (e.g., BMI), and growth metrics (e.g., interval velocities). The report can further include color-coded indicators of a range associated with each measurement. For example, if a measurement is in an average or typical range, the color-coded indicator can be green to indicate that there is no cause for concern. If the measurement is higher or lower than the average range, the color-coded indicator can be orange, yellow, or red to indicate an amount of deviation from the average range. The amount of deviation can be indicative of a level of risk associated with the patient’s measurements. For example, if the patient is short for their age and / or gender, the color-coded indicator can be yellow to indicate that their length is outside of an average range and that the patient is not severely short.

[0116] It can be appreciated that any other suitable measurements can be reported using the traffic light reports. For example, BMI, size of hands, a distance between a maximum head circumference and the toes, a distance between the eyes of a patient, a distance between the top of a patient’s head and the chin, etc. can be reported. Dysmorphology measurements can be incorporated and automated with the same methodology as needed.

[0117] FIG. 25 shows an illustrative process 1701 for determining the colors for “traffic light” indicators shown by a suitable interface of a system for analyzing the physical characteristics of a person. At step 1711, a measured value (e.g., a measured length value, weight value, or head circumference value) is transmitted to an integration module, and the integration module is configured to calculate a Z-score of the measured value at step 1712 of process 1701. At step 1714, a range for Z-scores is determined. For example, if the Z-score is less than or equal to a minimum Z value Zmin, then dark red can be assigned to a traffic light indicator 1728. If the Z-score is within a range of Zm< Z < Z1;red can be assigned to the traffic light indicator 1728. If the Z-score is within a range of Z1< Z < Z2, orange can be assigned to the traffic light indicator 1728. If the Z- score is within a range of Z2< — Z3, yellow can be assigned to the traffic light indicator 1728. If the Z-score is within a range of Z3< Z < Z4, green can be assigned to the traffic light indicator 1728. If the Z-score is within a range of Z4< Z < Z5, yellow can be assigned to the traffic light indicator 1728. If the Z-score is within a range of Zs< Z < Z6, orange can be assigned to the traffic light indicator 1728. If the Z-score is within a range of Z6< Z < Zpred can be assigned to the traffic light indicator 1728, and if the Z-score is larger than the maximum value Zp, dark red can be assigned to the traffic light indicator 1728. The interface module then is configured to report the type of dimension 1726 (e.g., length, weight, or head circumference), a value for the dimension 1727 (e.g., 70 centimeters, 4.4 kg, or 35 centimeters), and a traffic light color 1728. In one example, Zmcan be about -4 or below, Z4can be about -3, Z2can be about -2, Z3can be about -1, Z4can be about 1, Z5 can be about 2, Z6can be about 3, Zpcan be about 4. Different colors or shaded areas can be output for users with colorblindness or different visual preferences. In one embodiment, the color assignments can be presented using an audio output.

[0118] In general, the red color of the traffic light report can indicate concern, yellow can indicate cautious observation, and green can indicate reassurance. This reporting mechanism proves invaluable for caregivers and parents, enabling swift prioritization of babies requiring focused attention. In one embodiment, the measurement data can be aggregated and analyzed using machine learning techniques, including the use of artificial intelligence. This is aimed at enhancing accuracy in identifying clinically significant abnormalities across various growth patterns. The interface module can furnish immediate alerts during measuring if abnormalities are suspected, thus encouraging prompt re-evaluations. The benefits of this interface module include enhanced efficiency, lucid communication, and clinical effectiveness, contributing to a reduction in measurement errors.

[0119] In various cases, the users have the option to view growth charts or comprehensive reports pertaining to individual patients. Furthermore, given the vast array of genetic syndromes, the interface module can aggregate data for diverse syndromes, thereby automatically formulating statistically significant growth curves for any condition including rare conditions. These curves can be consistently updated to ensure precision in disease-specific populations. Consequently, in cases of abnormal growth, the interface module can automatically contrast patient data against growth patterns associated with specific disorders. If desired, users can receive notifications about potential conditions that are generated by the interface module. Moreover, for children with specific diagnoses, such as hydrocephalus, growth curves are constructed and compared in instances of abnormal interval head growth.

[0120] It is to be understood that the present invention is not to be limited to the exact description and embodiments as illustrated and described herein. To those of ordinary skill in the art, one or more variations and modifications will be understood to be contemplated from the presentdisclosure. Accordingly, all expedient modifications readily attainable by one of ordinary skill in the art from the disclosure set forth herein, or by routine experimentation therefrom, are deemed to be within the true spirit and scope of the invention as defined by the appended claims.

[0121] While this specification contains many specific implementation details, these should not be construed as limitations on the scope of what may be claimed, but rather as descriptions of features that may be specific to particular embodiments.

[0122] Certain features that are described in this specification in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable sub-combination. Moreover, although features may be described above as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can in some cases be excised from the combination, and the claimed combination may be directed to a sub-combination or variation of a sub-combination.

[0123] Similarly, while operations are depicted in the drawings in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In certain circumstances, multitasking and parallel processing may be advantageous. Moreover, the separation of various system modules and components in the embodiments described above should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.

[0124] Particular embodiments of the subject matter have been described. Other embodiments are within the scope of the following claims. For example, the actions recited in the claims can be performed in a different order and still achieve desirable results. As one example, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some cases, multitasking and parallel processing may be advantageous.

[0125] Embodiments of the present disclosure my also be set forth in the following parentheticals.

[0126] (1) A measurement system for assessing growth of a patient, comprising a horizontal platform having a length and a width; a length measuring device including a headboard and at least one footboard, the headboard and the at least one footboard being coupled to the horizontal platform along the length of the horizontal platform; one or more load cells in contact with the horizontal platform; a retractable measuring tape spooled around a cartridge having a rotatable axis; and processing circuitry configured to determine a height of the patient based on a distance between the headboard and the at least one footboard, a weight of the patient based on a weight applied to the one or more load cells, and a head circumference of the patient based on an exposed length of the retractable measuring tape and to determine whether the growth of the patient is within a predetermined normal range based on the height, the weight, and / or the head circumference.

[0127] (2) The measurement system of (1), wherein the at least one footboard is coupled to a belt of a pulley running along the length of the horizontal platform and a position of the at least one footboard is adjustable via movement of the belt of the pulley.

[0128] (3) The measurement system of (1) to (2), wherein the processing circuitry is configured to determine the distance between the headboard and the at least one footboard based on a rotation of the pulley during the movement of the belt.

[0129] (4) The measurement system of (1) to (3), wherein the at least one footboard includes a first footboard coupled to a first side of the horizontal platform and a second footboard coupled to an opposing side of the horizontal platform.

[0130] (5) The measurement system of (1) to (4), wherein the one or more load cells are evenly distributed across a surface of the horizontal platform.

[0131] (6) The measurement system of (1) to (5), wherein the processing circuitry is configured to determine the exposed length of the retractable measuring tape based on a rotation of the rotatable axis.

[0132] (7) The measurement system of (1) to (6), wherein the horizontal platform includes a head support and wherein the retractable measuring device is coupled to the head support.

[0133] (8) The measurement system of (1) to (7), further comprising one or more cameras configured to capture image data of a patient on the horizontal platform, wherein the processing circuitry is further configured to process the image data from the one or more cameras to determine a measurement of a size of the patient.

[0134] (9) The measurement system of (1) to (8), wherein the horizontal platform includes a length indicator on a surface of the horizontal platform.

[0135] (10) The measurement system of (1) to (9), wherein the processing circuitry is further configured to determine a difference between the height of the patient and an average height of patients having an age and a gender of the patient.

[0136] (1 1) The measurement system of (1) to (10), wherein the processing circuitry is further configured to determine a difference between the weight of the patient and an average weight of patients having an age and a gender of the patient.

[0137] (12) The measurement system of (1) to (11), wherein the processing circuitry is further configured to determine a difference between the head circumference of the patient and an average head circumference of patients having an age and a gender of the patient.

[0138] (13) The measurement system of (1) to (12), wherein the processing circuitry is configured to determine a change in the height of the patient, a change in the weight of the patient, and / or a change in the head circumference of the patient.

[0139] (14) The measurement system of (1) to (13), wherein the processing circuitry is configured to determine an interval growth velocity of the height of the patient, an interval growth velocity of the weight of the patient, and / or an interval growth velocity of the head circumference of the patient.

[0140] (15) The measurement system of (1) to (14), wherein the processing circuitry is further configured to determine a risk level associated with the growth of the patient based on the height of the patient, the weight of the patient, and / or the head circumference of the patient.

[0141] (16) The measurement system of (1) to (15), further comprising a display, wherein the processing circuitry is configured to display a growth curve of the height of the patient, the weight of the patient, and / or the head circumference of the patient.

[0142] (17) A method for assessing growth of a patient, comprising determining, via processing circuitry, a height of the patient based on a distance between a headboard positioned at a head of the patient and a footboard positioned at a foot of the patient; determining, via the processing circuitry, a weight of the patient based on one or more load cells underneath the patient;determining, via the processing circuitry, a head circumference of the patient based on a length of a retractable measuring tape wrapped around a head of the patient; and determining, via the processing circuitry, whether the growth of the patient is within a predetermined normal range based on the height, the weight, and / or the head circumference.

[0143] (18) The method of (17), further comprising determining, via the processing circuitry, a height difference between the height of the patient and an average height of patients having an age and a gender of the patient, a weight difference between the weight of the patient and an average weight of the patients having the age and the gender of the patient, a head circumference difference between the head circumference of the patient and an average head circumference of the patients having the age and the gender of the patient, and a level of risk associated with the growth of the patient based on the height difference, the weight difference, and / or the head circumference difference.

[0144] (19) The method of (17) to (18), further comprising displaying, via the processing circuitry, a growth curve of the height of the patient, the weight of the patient, and / or the head circumference of the patient.

[0145] (20) A non-transitory computer-readable storage medium for storing computer-readable instructions that, when executed by a computer, cause the computer to perform a method for assessing growth of a patient, the method comprising determining a height of the patient based on a distance between a headboard positioned at a head of the patient and a footboard positioned at a foot of the patient; determining a weight of the patient based on one or more load cells underneath the patient; determining a head circumference of the patient based on a length of a retractable measuring tape wrapped around a head of the patient; and determining whether the growth of thepatient is within a predetermined normal range based on the height, the weight, and / or the head circumference.

[0146] Obviously, numerous modifications and variations of the present invention are possible in light of the above teachings. It is therefore to be understood that within the scope of the appended claims, the invention may be practiced otherwise than as specifically described herein.

Claims

CLAIMS1. A measurement system for assessing growth of a patient, comprising: a horizontal platform having a length and a width; a length measuring device including a headboard and at least one footboard, the headboard and the at least one footboard being coupled to the horizontal platform along the length of the horizontal platform; one or more load cells in contact with the horizontal platform; a retractable measuring tape spooled around a cartridge having a rotatable axis; and processing circuitry configured to determine a height of the patient based on a distance between the headboard and the at least one footboard, a weight of the patient based on a weight applied to the one or more load cells, and a head circumference of the patient based on an exposed length of the retractable measuring tape and to determine whether the growth of the patient is within a predetermined normal range based on the height, the weight, and / or the head circumference.

2. The measurement system of claim 1, wherein the at least one footboard is coupled to a belt of a pulley running along the length of the horizontal platform and a position of the at least one footboard is adjustable via movement of the belt of the pulley.

3. The measurement system of claim 2, wherein the processing circuitry is configured to determine the distance between the headboard and the at least one footboard based on a rotation of the pulley during the movement of the belt.

4. The measurement system of claim 1 , wherein the at least one footboard includes a first footboard coupled to a first side of the horizontal platform and a second footboard coupled to an opposing side of the horizontal platform.

5. The measurement system of claim 1, wherein the one or more load cells are evenly distributed across a surface of the horizontal platform.

6. The measurement system of claim 1, wherein the processing circuitry is configured to determine the exposed length of the retractable measuring tape based on a rotation of the rotatable axis.

7. The measurement system of claim 1, wherein the horizontal platform includes a head support and wherein the retractable measuring device is coupled to the head support.

8. The measurement system of claim 1, further comprising one or more cameras configured to capture image data of a patient on the horizontal platform, wherein the processing circuitry is further configured to process the image data from the one or more cameras to determine a measurement of a size of the patient.

9. The measurement system of claim 1 , wherein the horizontal platform includes a length indicator on a surface of the horizontal platform.

10. The measurement system of claim 1 , wherein the processing circuitry is further configured to determine a difference between the height of the patient and an average height of patients having an age and a gender of the patient.

11. The measurement system of claim 1, wherein the processing circuitry is further configured to determine a difference between the weight of the patient and an average weight of patients having an age and a gender of the patient.

12. The measurement system of claim 1, wherein the processing circuitry is further configured to determine a difference between the head circumference of the patient and an average head circumference of patients having an age and a gender of the patient.

13. The measurement system of claim 1, wherein the processing circuitry is configured to determine a change in the height of the patient, a change in the weight of the patient, and / or a change in the head circumference of the patient.

14. The measurement system of claim 13, wherein the processing circuitry is configured to determine an interval growth velocity of the height of the patient, an interval growth velocity of the weight of the patient, and / or an interval growth velocity of the head circumference of the patient.1 . The measurement system of claim 1 , wherein the processing circuitry is further configured to determine a risk level associated with the growth of the patient based on the height of the patient, the weight of the patient, and / or the head circumference of the patient.

16. The measurement system of claim 1, further comprising a display, wherein the processing circuitry is configured to display a growth curve of the height of the patient, the weight of the patient, and / or the head circumference of the patient.

17. A method for assessing growth of a patient, comprising: determining, via processing circuitry, a height of the patient based on a distance between a headboard positioned at a head of the patient and a footboard positioned at a foot of the patient; determining, via the processing circuitry, a weight of the patient based on one or more load cells underneath the patient; determining, via the processing circuitry, a head circumference of the patient based on a length of a retractable measuring tape wrapped around a head of the patient; and determining, via the processing circuitry, whether the growth of the patient is within a predetermined normal range based on the height, the weight, and / or the head circumference.

18. The method of claim 17, further comprising determining, via the processing circuitry, a height difference between the height of the patient and an average height of patients having an age and a gender of the patient, a weight difference between the weight of the patient and an average weight of the patients having the age and the gender of the patient, a head circumference difference between the head circumference of the patient and an average headcircumference of the patients having the age and the gender of the patient, and a level of risk associated with the growth of the patient based on the height difference, the weight difference, and / or the head circumference difference.

19. The method of claim 17, further comprising displaying, via the processing circuitry, a growth curve of the height of the patient, the weight of the patient, and / or the head circumference of the patient.

20. A non-transitory computer-readable storage medium for storing computer- readable instructions that, when executed by a computer, cause the computer to perform a method for assessing growth of a patient, the method comprising: determining a height of the patient based on a distance between a headboard positioned at a head of the patient and a footboard positioned at a foot of the patient; determining a weight of the patient based on one or more load cells underneath the patient; determining a head circumference of the patient based on a length of a retractable measuring tape wrapped around a head of the patient; and determining whether the growth of the patient is within a predetermined normal range based on the height, the weight, and / or the head circumference.

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