Improved goniometer

Abstract

A method, system, and apparatus, including a computer program encoded on a computer storage medium, for an improved goniometer. In some implementations, the method comprises obtaining a series of measurements based on one or more data points of an inspection, receiving input from a user initiating the measurements, receiving raw data from a measurement component, processing the raw data to exclude measurements corresponding to one or more axes, generating measurement results based on the processed raw data, and providing the measurement results for output.

Description

Technical Field

[0001] This specification generally describes an improved gonimeter.

Background Art

[0002] A gonimeter is a device used for precise measurement of angles. For example, a physician or a physical therapist can use a gonimeter to measure the angular range of movement of a patient's joint.

[0003] Currently, many companies, such as sports organizations, incorporate wellness programs aimed at reducing lifestyle markers such as high blood pressure, cholesterol levels, hemoglobin A1c (HA1c), and body weight. Devices worn by employees, officers, and athletes enable companies to track data such as sleep patterns, daily step counts, heart rate training, or respiratory rates.

[0004] In the sports world, keeping athletes on the field is related to overall organizational success. Many of the same wellness strategies that have been used by sports organizations have been incorporated into the corporate world, leading to a robust data-driven approach for tracking and using specific important data variables.

Summary of the Invention

[0005] In some implementations, the improved gonimeter of the present disclosure may be used to measure a patient's movement. For example, to accurately measure movement, the improved gonimeter may select one or more axes along which an angle is measured based on a particular movement. The gonimeter may then invalidate angle measurements corresponding to unselected axes and notify the user to proceed with the measurement of the movement. By separating angle measurements for a particular measurement of movement to only angles of interest, the improved gonimeter may improve the accuracy of the angle measurement and thereby improve the resulting diagnosis.

[0006] In some implementations, the improved goniometer may selectively filter or disable one or more measurement axes. For example, the improved goniometer may receive data measurements from an application programming interface (API), select one or more data measurements from the API, and calculate the angle for the specified measurement with respect to a specified axis.

[0007] In some implementations, the improved goniometer may measure an angle measurement based on one or more other angle measurements. For example, the device of the improved goniometer may be positioned at a specific angle with respect to a first axis. Based on the specific angle with respect to the first axis, the improved goniometer may determine one or more other angles measured with respect to one or more other axes in order to determine the angle with respect to the first axis.

[0008] In some implementations, the improved goniometer described herein is used within a motion analysis performance system (MAPS), which is a data-driven injury prevention and correction system. The improved goniometer may be used to capture biomechanical, qualitative, and quantitative data, as well as to help determine medical biomarkers. The improved goniometer may also be used to help track, ultimately predict, and treat musculoskeletal injuries.

[0009] In some implementations, the improved goniometer described herein is used in specific biomechanical tests. For example, a biomechanical test may include measurements of a limb or other part of the body with the aim of collecting relevant data to predict musculoskeletal injury and derive effective therapeutic solutions. The biomechanical test may include a predetermined set of movements measured by the improved goniometer. Each measurement may include details regarding which one or more axes the data should be captured with respect to. For example, data associated with a measurement may indicate that the measurement should be made with respect to the z-axis of the goniometer rather than the x-axis or y-axis. Each measurement may also be processed by a computing device corresponding to the improved goniometer to determine which axis to select to produce the measurement result, based on a given movement being measured.

[0010] According to one common implementation, an improved goniometer features a user interface that guides the physician through multi-point biomechanical examinations. The user interface includes images that provide the physician with information, such as how to perform each step in a biomedical examination. For example, for a particular biomedical examination, the user interface may show how the physician should position the goniometer on the patient or how to hold or move the goniometer in order to register accurate measurements.

[0011] The improved goniometer may be implemented in any suitable device capable of measuring one-dimensional, two-dimensional, or three-dimensional angles. To improve accuracy, measurements along certain axes may be disabled when performing measurements that do not require those axes to be measured, for example, by temporarily disabling certain hardware or by selectively filtering measurement data acquired from the measuring device. An indication of active and disabled axes may be shown within the user interface.

[0012] It is understood that methods conforming to this disclosure may include any combination of the embodiments and features described herein. That is, methods conforming to this disclosure are not limited to combinations of embodiments and features specifically described herein, but may include any combination of embodiments and features provided herein.

[0013] One innovative aspect of the subject matter described herein is embodied by a method comprising the steps of: acquiring a series of measurements measured based on one or more data points of an inspection; receiving input from a user to initiate a measurement; receiving raw data from a measurement component; processing the raw data to exclude measurements corresponding to one or more axes; generating measurement results based on the processed raw data; and providing the measurement results for output.

[0014] Other implementations of this embodiment and other embodiments include corresponding systems, devices, and computer programs configured to perform the operation of the method and encoded in a computer storage device. One or more computer systems can be configured by software, firmware, hardware, or a combination thereof installed on the system that causes the system to act during operation. One or more computer programs can be configured by having instructions that cause the device to act when executed by a data processing device.

[0015] Each of the above and other embodiments may optionally include one or more of the following features, either individually or in combination. For example, in some implementations, the raw data processing step may include: determining the current measurement among a set of measurements based on a predetermined order of the set of measurements to be measured; determining elements of data to be excluded based on the current measurement; and processing the raw data from the measurement component by excluding the determined elements of data.

[0016] In some implementations, the raw data processing step may include an analysis step that analyzes each measurement in a series of measurements, and a step that determines, based on the analysis step, one or more measurements corresponding to one or more axes to be excluded from the raw data.

[0017] In some implementations, the process may include outputting an image to a display that provides the user with information about how the measurement is performed. In some implementations, the image may include graphical information indicating where to position the goniometer device on the patient's body before starting the measurement.

[0018] In some implementations, the set of measurements may include a big toe extension measurement. In some implementations, the set of measurements includes a big toe extension measurement followed by a weighted dorsiflexion measurement.

[0019] Details of one or more implementations of this disclosure are described in the accompanying drawings and the following description. Other features and advantages of this disclosure will become apparent from the description and drawings, as well as from the claims. [Brief explanation of the drawing]

[0020] [Figure 1] A diagram showing an example of a conventional goniometer system. [Figure 2] A diagram showing an example of an improved goniometer system. [Figure 3] A diagram illustrating an example of performing multiple measurements using an improved goniometer system. [Figure 4] A diagram illustrating an exemplary processing flow of an improved goniometer system. [Figure 5] A flowchart illustrating an example of processing for an improved goniometer system. [Figure 6] A diagram of computer system components that can be used to implement an improved goniometer system. [Modes for carrying out the invention]

[0021] Like reference numerals and names in the various drawings indicate like elements. FIG. 1 is a diagram showing an example of a conventional gonioscope system 100. The system 100 includes a device 105 for measuring an angle in a dimensional space 110. The device 105 is capable of measuring an angle in one dimension, two dimensions, or three dimensions. In the specific example of FIG. 1, the device 105 measures an angle in the xy plane around the z-axis.

[0022] Stage A indicates the starting position of the device 105 during a given measurement, and stage B indicates the ending position of the device 105. From stage A to stage B, the device 105 rotates around the z-axis, but also turns (changes orientation) with respect to the centerline of the device 105. Such a turn during the measurement process can affect the reading of the device 105. As shown in the example of FIG. 1, the device 105 rotates 45 degrees around the z-axis, but due to the rotation around the centerline of the device 105, an angle of 40 degrees is calculated. A suitable user display of the device 105 can display information corresponding to items 107 and 120 that indicate the starting and ending angles of the current measurement.

[0023] In the example of FIG. 1, the device 105 cannot fully account for the turn of the device 105 during the measurement. As a result, an incorrect angle is shown to the user. When used in the medical profession, even a slight inaccuracy can significantly affect diagnosis and treatment. Considering the possibility that the user cannot keep the device 105 in an accurate plane throughout the course of a given measurement, the measurement results generated using the device 105 as a gonioscope are likely to include inaccuracies.

[0024] FIG. 2 is a diagram showing an example of an improved gonioscope system 200. The system 200 includes a device 205. The device 205 is capable of measuring angles in one dimension, two dimensions, or three dimensions. The device 205 is communicatively connected to a computing element 208. In some implementations, the computing element 208 is housed within the device 205. For example, the device 205 can be a certain type of smartphone designed with angle measurement capabilities (e.g., an accelerometer) as well as processing capabilities.

[0025] Similar to the example of FIG. 1, the device 205 measures the angle around the z-axis. At stage A, the device 205 starts parallel to the xy plane at an angle of 0 degrees, as shown by item 215. The device measures an angle 218 that rotates around the z-axis at 45 degrees with respect to the z-axis and corresponds to the angle 218. Similar to the device 105 of FIG. 1, the device 205 potentially turns during the measurement process due to an unintended rotation caused by the user and is no longer parallel to the xy plane at stage B.

[0026] Unlike the system 100, the system 200 can successfully compensate for the effect of the turn by selecting a subset of the measurements to be processed. For example, only the measurements corresponding to the angle measurements around the z-axis are processed by the computing element 208, and the system 200 can accurately determine that the angle measured by the device 205 is 45 degrees, as shown by item 230.

[0027] In some implementations, system 200 may warn the user based on the position of device 205. For example, system 200 may detect that device 205 is tilted by more than a predetermined degree with respect to a given axis, such as the z-axis, in dimensional space 210. System 200 may detect the tilt while measuring the angle in a measurement sequence. In response to a determination that device 205 is tilted beyond a predetermined amount, system 200 may prompt the user of system 200 that device 205 is tilted beyond a threshold, and system 200 may refuse to accept the angle with respect to device 205 in that orientation.

[0028] Figure 3 shows an example of a system 300 that performs multiple measurements using an improved goniometer. System 300 includes a device 305 that, like device 205, is capable of measuring angles in one, two, or three dimensions.

[0029] Device 305 performs three measurements as shown in stages A, B, and C. Device 305 measures a first angle 318 of 45 degrees, a second angle 319 of 53 degrees, and a third angle of 41 degrees. Each measurement corresponds to a single point in a multipoint biomechanical examination. Each measurement corresponds to big toe extension, where the patient's big toe extends upward relative to the xz plane shown in dimensional space 310, generating an angle. Device 305 can be used to measure the maximum angle generated by the big toe and the floor corresponding to the xz plane.

[0030] In the example shown in Figure 3, big toe extension is considered, but any other angular measurements of the multipoint biomechanical examination can be measured using multiple measurements stored in device 305. For example, the measurements may include, among others, weighted dorsiflexion, tibial rotation, femoral rotation, hip flexion, shoulder flexion, shoulder abduction, cervical rotation, cervical lateral flexion, wrist extension, wrist supination, and wrist pronation.

[0031] Device 305 is capable of displaying multiple measurements, which may be any number of measurements, on the appropriate display 306 of Device 305. The multiple measurements may be selectable items that can be saved by selecting the selected save button 306c. Each measurement may be read aloud to the user of Device 305 to determine the angle without removing the device from the measurement position. The measurement audio can be switched on or off using the audio toggle button 306b. For example, in some cases, the measurement audio may be switched on or off on the settings page of the corresponding application interface.

[0032] In some implementations, each sequential measurement is captured by device 305 if the user rotates device 305 after or during the activation of a user input element. For example, device 305 may have a button along one of its edges. To start a new measurement, the user may press one or more buttons along the edge of device 305.

[0033] In one example, the user may then release one or more buttons, rotate the device 305 according to the current measurement requirements, and then press one or more buttons again to stop the measurement. The button used to start the measurement may be the same as or different from the button used to stop the measurement.

[0034] In another example, the user may press one or more buttons along the edge of device 305 and continue to press one or more buttons throughout the measurement. After the measurement is complete, the user may release one or more buttons to terminate the measurement. A processing component corresponding to device 305 may then determine a value for the given measurement according to one or more methods of this disclosure.

[0035] In some implementations, rotational mismatches during the measurement process, such as the rotation of device 305 around its midline in stages A, B, and C, are at least partially caused by pressing one or more buttons along the edge of device 305 used to start or stop the measurement process. For example, the user may readjust their grip on the phone to press one or more buttons that may cause rotation around an axis other than the current measurement axis, such as the z-axis in Figure 3.

[0036] To ensure that rotational mismatches for arbitrary movements not directly related to the measurement of the patient's biomechanical movement (such as rotation of device 305 around the midline) do not result in inaccuracies in angle measurements, a computing component corresponding to device 305 can be used to exclude angle measurements corresponding to one or more axes. In the example in Figure 3, the angle is measured around the z-axis. Once it is determined that the angle measurement is measured around the z-axis based on a given measurement (e.g., big toe extension in particular), a computing component communicatively connected to device 305 can exclude measurements corresponding to the x-axis and y-axis.

[0037] Any given measurement can be displayed on the display of device 305. For example, part 306a of the display 306 displays all measurement values ​​corresponding to the current data point.

[0038] Figure 4 shows an exemplary processing flow 400 of an improved goniometer. The goniometer 415 receives measurement data 410 corresponding to a measurement sequence 405. The goniometer 415 also receives data from an application programming interface (API) 420. In some cases, the API 420 operates using components of the device corresponding to the goniometer 415. Based on the data 410 and the API 420, the goniometer 415 generates a measurement output 430 corresponding to a specific measurement in the measurement sequence 405.

[0039] Measurement sequence 405 may be consistent with a multipoint biomechanical examination in which each measurement in measurement sequence 405 is used to calculate one or more data points in the examination. Measurement sequence 405 shows several exemplary measurements, including big toe extension, weighted dorsiflexion, tibia medial / lateral, obturator internus, quadratus femoris, piriformis, and cervical lateral flexion.

[0040] The measurement sequence 415 can be stored locally in a component that is communicably connected to the goniometer 415, or remotely in another component, and transmitted to the goniometer 415 via one or more networks for data transfer.

[0041] In some implementations, the measurement sequence 405 is maintained on a server. For example, the server can store the measurement sequence 405 and communicate with the goniometer 415 so that when changes are made to the version maintained on the server, those changes are captured by the goniometer 415 and incorporated into the current set of measurements. In this way, when an update to the sequence is required, it is possible to push the update of the measurement sequence from the central local to the goniometer in the field.

[0042] The goniometer 415 may include a device used to acquire raw measurement data, such as device 205 or 305. The device may be some kind of smartphone with a display and internal processing components. The device may also perform API 420 operations, such as accelerometer measurements, among other things, to acquire raw data from multiple axes related to the angle measurement.

[0043] The goniometer 415 can use the measurement data 410 to determine how to process the raw data from the API 420. For example, the goniometer 415 can determine one or more axes for data acquisition and disable another set of axes to isolate a particular set of axes for measurement. The goniometer 415 may determine which axes or multiple axes to disable based on the measurement sequence 405. In particular, the measurement data 410 may be configured by the goniometer 415 or a third-party system to include one or more indications of one or more measurements in the measurement sequence 405. One or more indications may include alphanumeric characters configured for each measurement in the measurement sequence 405. Each measurement in the measurement data 410 can be analyzed by the goniometer 415. After analysis, the goniometer 415 can determine which axes or multiple axes to disable for a given measurement based on the determined measurement and the measurement axes determined for measurement. By separating the selected measurements based on the measurement data 410, the goniometer 415 can effectively compensate for unintended twisting of any component of the goniometer 415.

[0044] In some implementations, the goniometer 415 may track measurements to determine which measurement in the measurement sequence 415 is currently being measured. For example, the measurement data 410 may include at least the indices of a big toe extension measurement, followed by a weighted dorsiflexion measurement, followed by an intratibial measurement. Based on the measurement sequence 415, the goniometer 415 may determine which axes or multiple axes to disable for each measurement included in the measurement data 410.

[0045] In some implementations, the goniometer 415 may track each measurement to determine which measurement is being performed. For example, after a result for a big toe extension measurement is generated based on disabling one or more axes, the goniometer 415 determines the next measurement of weighted dorsiflexion based on the known order of the measurement sequence 415 contained in the measurement data 410, and automatically disabling the corresponding axis for weighted dorsiflexion. In some implementations, the goniometer 415 can determine the next measurement and which one or more axes to disabling in real time as the user readjusts to perform the next measurement. Thus, data extraction for biomechanical testing is not only more accurate but also more efficient, as the accuracy improvements partially enabled by axis disabling are automatically applied as the user performs each measurement according to the measurement sequence 415.

[0046] In some implementations, the measurement data 410 includes the measurement values ​​to be processed. For example, the measurement data 410 corresponding to big toe extension may include data indicating that the measurement of big toe extension involves processing only the angle measurement relative to the z axis, and that the angle measurements relative to the x and y axes are disabled. Based on the measurement data 410, the goniometer 415 can process the raw data from API 420 based on the angle measurement relative to the z axis.

[0047] In some implementations, the goniometer 415 determines which measurements to disable from the API 420 based on the measurement data 410. For example, without receiving explicit data indicating which measurements to disable, the goniometer 415 may parse the measurement sequence 405 corresponding to the measurement data 410 and determine which measurements to disable from the API 420 based on the name or other data corresponding to a given measurement.

[0048] In some implementations, data from components of the goniometer 415 is used to determine which measurements to disable. For example, the goniometer 415 device may use an onboard accelerometer to determine the device's starting position. The device can be a smartphone or other similar device. The starting position can be used, at least in part, to determine which measurements to disable from API 420. For example, if the device starts parallel to the xy plane, the goniometer 415 may disable the measurements corresponding to the x or y axis based on the determination that the measurement is likely to be an angular measurement around the z axis.

[0049] In some implementations, the name of a measurement can indicate that a particular angle is one-dimensional rather than multi-dimensional. For example, extension may indicate that the corresponding measurement is one-dimensional during analysis.

[0050] In some implementations, the goniometer 415 receives data from the API 420 that does not match the possible results for a given measurement. For example, in big toe extension, if the data from the API 420 corresponds to an angle greater than 180 degrees, indicating that the big toe could be extended 180 degrees from its resting position, the goniometer 415 can determine that the data from the API 420 is inaccurate. In some implementations, after determining that the data from the API 420 is inaccurate based on a given measurement shown in the measurement data 410, the goniometer can output to the display that the measurement was invalid and request the user to take the measurement again.

[0051] In some implementations, one or more tolerances are referenced by the goniometer 415. For example, the goniometer 415 may obtain data from API 420 and generate angle measurements based on the processing described herein, so as to determine whether the data for a given measurement is possible and not an error in the measurement system. After generating the angle measurements, the goniometer 415 may compare the generated angle measurements with one or more values ​​indicating tolerances for the measurements included in the measurement sequence 405. In some cases, the tolerances are indicated in the measurement data 410 and transmitted to the goniometer 415.

[0052] Figure 5 is a flowchart showing an example of a process 500 for an improved goniometer. The steps of process 500 may be carried out by one or more electronic systems, for example, system 200 or system 300.

[0053] Process 500 includes a step (502) of acquiring a series of measurements. For example, as shown in process flow 400, the goniometer 415 acquires measurement data 410 corresponding to the measurement sequence 405. In some cases, the measurement data 410 includes data indicating one or more measurements included in the measurement sequence 405.

[0054] Process 500 includes a step (504) of receiving input from the user to initiate the measurement. For example, as shown in Figure 2, the user may manipulate the device 205 and rotate it by an angle that matches the patient's movement. For example, to measure big toe extension, the user can move the device 205 from a baseline, such as a line parallel to the floor represented by the xz plane in dimensional space 210, to the angle of the extended big toe.

[0055] Process 500 includes a step (506) of receiving raw data from the measurement component. For example, as shown in process flow 400, the goniometer 415 receives data from API 420. In some cases, API 420 generates raw data based on at least one or more accelerometers. The accelerometers may be housed within the device of the goniometer 415, which is used to measure the angle of biomechanical motion. By measuring changes in acceleration, the accelerometers can determine the rotation angle corresponding to one or more rotation axes.

[0056] In some implementations, the accelerometer of the goniometer device is housed in the device in such a way that it is affected by unintended rotation of the device. For example, if the device used in the improved goniometer houses the accelerometer at the center of the device body, rotation around the edge of the device may cause the accelerometer to be positioned differently from the position desired for accurate measurement. Without further processing by the goniometer 415 as described herein, these unintended rotations may result in inaccuracies in the resulting angular measurements used at one or more data points in a biomechanical examination.

[0057] In some implementations, unintended rotation of the device may be captured and used to determine the actual position of the accelerometer relative to a given axis of rotation. For example, rotation around the z-axis may result in unintended rotation that rotates the device around its long edge. This rotation may affect the position of the accelerometer chip inside the device and, therefore, may affect the reading of angle measurements taken around an axis such as the z-axis.

[0058] To determine the actual position of the accelerometer, the rotation of the device may be recorded by a component such as API 420 and processed by the goniometer 415 to calculate the differential motion of the accelerometer chip with respect to the angle to be measured. In this way, the goniometer 415 can determine an accurate angle measurement even if the accelerometer rotates away from the measurement plane (e.g., the xy-plane around the z-axis in Figure 2) due to unintended rotation.

[0059] In some implementations, the user is asked to measure the angle with respect to the device using one edge of the device to ensure accuracy. For example, to compensate for unintended rotation, the user may be prompted by the user interface to ensure that one or more edges of the device, such as the edge of device 305, are parallel to a reference such as the xz plane and to a side of the human body being examined, such as thumb extension in the xy plane.

[0060] Thus, the improved goniometer may compensate for unintended movements that may result in the accelerometer chip of device 305 being higher, lower, to the left, or to the right of its precise position for measuring angles. Based on the recorded movements, a goniometer such as goniometer 415 can calculate what the position of the accelerometer chip of the corresponding device was when the user of device 305 did not unintentionally rotate the device. Using the known position of the accelerometer chip with reference to the body shape of the corresponding device for measurement, such as device 305, goniometer 415 can calculate the non-rotated position of the accelerometer chip based on the fact that one or more edges of device 305 are parallel to the side of the patient being measured, such as the big toe.

[0061] Process 500 includes a step (508) of processing the raw data to exclude axis information. For example, as shown in Figure 2, a particular goniometer comprises both a device 205 and a computing component 208. The computing component 208 excludes measurements corresponding to the x and y rotation axes, as shown in dimensional space 210. In this way, the effects of rotation around the midline of the device 205, or any other accidental twists of the device 205 during the measurement process, are mitigated, and the device 205 and computing component 208 are able to generate accurate measurements of angle 218.

[0062] The process 500 includes a step (510) of generating measurement results based on the processed raw data. For example, the goniometer 415 can generate measurement results using the exclusions applied to API 420. In some cases, the measurement results include angular measurements around a single axis, such as the z-axis. The z-axis can be relative to the patient, the measurement, or the surface of the device.

[0063] In some implementations, the goniometer 415 may determine what the current measurement is based on a known order contained in the measurement data 410, corresponding to the measurement sequence 405. Based on the current measurement determined based on the measurement sequence 405, the goniometer 415 may determine which one or more axes to disable in order to achieve an accurate result for the current measurement. The goniometer 415 may adjust which axes to disable for each measurement in the measurement sequence 405 so as to produce a measurement result for each measurement in the measurement sequence 405. Each measurement may have its own unique set of axes or other measurement data that are disabled in order to achieve an accurate measurement result.

[0064] The process 500 includes a step (512) of providing the measurement results for output. For example, the goniometer 415 may output measurement results generated based on the exclusion of one or more measurement axes to a display. For example, as shown in Figure 3, the device 305 includes a display 306. A portion 306a of the display 306 may be used to show one or more measurement results generated by a computing component communicably connected to the device 305.

[0065] Figure 6 shows a computer system component that can be used to implement an improved goniometer system. The computing system comprises a computing device 600 and a mobile computing device 650 that can be used to implement the techniques described herein. For example, one or more components of system 200, 300, or 400 can be an example of a computing device 600 or a mobile computing device 650, such as a computer system implementing device 205, computing component 208, device 305, or goniometer 415, among other things.

[0066] Computing device 600 is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants (PDAs), servers, blade servers, mainframes, and other appropriate computers. Mobile computing device 650 is intended to represent various forms of mobile devices, such as personal digital assistants (PDAs), cellular phones, smartphones, mobile embedded wireless systems, wireless diagnostic computing devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are intended to be examples only and not to limit the scope of such devices.

[0067] The computing device 600 comprises a processor 602, memory 604, a storage device 606, a high-speed interface 608 connected to memory 604 and multiple high-speed expansion ports 610, and a low-speed interface 612 connected to a low-speed expansion port 614 and the storage device 606. Each of the processor 602, memory 604, storage device 606, high-speed interface 608, high-speed expansion ports 610, and low-speed interface 612 may be interconnected using various buses and implemented on a common motherboard or by other means as appropriate. The processor 602 is capable of processing instructions to be executed within the computing device 600, including instructions stored in memory 604 or the storage device 606, to display graphical information for a GUI on an external input / output device such as a display 616 coupled to the high-speed interface 608. In other implementations, multiple processors and / or multiple buses may be used with multiple memories and multiple types of memory as appropriate. In addition, multiple computing devices may be connected, each providing part of the operation (e.g., as a server bank, a group of blade servers, or a multiprocessor system). In some implementations, the processor 602 is a single-threaded processor. In some implementations, the processor 602 is a multi-threaded processor. In some implementations, the processor 602 is a quantum computer.

[0068] Memory 604 stores information within the computing device 600. In some implementations, memory 604 is one or more volatile memory units. In some implementations, memory 604 is one or more non-volatile memory units. Memory 604 may also be another form of computer-readable medium, such as a magnetic disk or an optical disk.

[0069] Storage device 606 can provide large-capacity storage for computing device 600. In some implementations, storage device 606 is or may include computer-readable media such as floppy disk devices, hard disk devices, optical disk devices, or tape devices, flash memory or other similar solid-state memory devices, or an array of devices including devices in a storage area network or other configuration. Instructions can be stored in an information carrier. When executed by one or more processing devices (e.g., processor 602), instructions perform one or more actions, such as those described above. Instructions can also be stored by one or more storage devices, such as a computer or machine-readable media (e.g., memory 604, storage device 606, or memory on processor 602). The high-speed interface 608 manages bandwidth-intensive operations for computing device 600, and the low-speed interface 612 manages less bandwidth-intensive operations. Such function assignments are merely examples. In some implementations, the high-speed interface 608 is coupled to memory 604, a display 616 (e.g., via a graphics processor or accelerator), and a high-speed expansion port 610 that can accept various expansion cards (not shown). In some implementations, the low-speed interface 612 is coupled to a storage device 606 and a low-speed expansion port 614. The low-speed expansion port 614 may include various communication ports (e.g., USB, Bluetooth®, Ethernet®, Wireless Ethernet) and can be coupled to one or more input / output devices such as a keyboard, pointing device, or scanner, or to a networking device such as a switch or router (e.g., via a network adapter).

[0070] The computing device 600 may be implemented in several different forms, as shown in the figure. For example, the computing device 600 may be implemented multiple times as a standard server 620, or as part of a group of such servers. In addition, the computing device 600 may be implemented in a personal computer, such as a laptop computer 622. Alternatively, the computing device 600 may be implemented as part of a rack server system 624. Instead, components from the computing device 600 may be combined with other components in a mobile device, such as a mobile computing device 650. Each of such devices may contain one or more of the computing device 600 and the mobile computing device 650, and the entire system may consist of multiple computing devices communicating with each other.

[0071] The mobile computing device 650 includes, among other components, an input / output device such as a processor 652, memory 664, and display 654, a communication interface 666, and a transceiver 668. The mobile computing device 650 may be provided with a storage device such as a microdrive or other device to provide additional storage. Each of the processor 652, memory 664, display 654, communication interface 666, and transceiver 668 is interconnected using various buses, and some of the components may be implemented on a common motherboard or by other appropriate methods as needed.

[0072] The processor 652 is capable of executing instructions within the mobile computing device 650, including instructions stored in memory 664. The processor 652 may be implemented as a chipset consisting of multiple chips, each comprising a separate set of analog and digital processors. The processor 652 may also provide coordination for other components of the mobile computing device 650, such as the user interface, applications run by the mobile computing device 650, and control of wireless communication by the mobile computing device 650.

[0073] The processor 652 may communicate with the user via a control interface 658 and a display interface 656 coupled to the display 654. The display 654 may be, for example, a TFT (thin-film transistor liquid crystal display) display or an OLED (organic light-emitting diode) display, or other suitable display technology. The display interface 656 may include appropriate circuitry for driving the display 654 to present graphical and other information to the user. The control interface 658 may receive commands from the user and translate those commands for submission to the processor 652. In addition, an external interface 662 may provide communication with the processor 652 to enable short-range communication of the mobile computing device 650 with other devices. The external interface 662 may provide, for example, wired communication in some implementations and wireless communication in others, and multiple interfaces may be used.

[0074] Memory 664 stores information within the mobile computing device 650. Memory 664 can be implemented as one or more of one or more computer-readable media, one or more volatile memory units, or one or more non-volatile memory units. An expansion memory 674 is also provided and may be connected to the mobile computing device 650 via an expansion interface 672, which may include, for example, a SIMM (Single In-Line Memory Module) card interface. The expansion memory 674 may provide extra storage space for the mobile computing device 650, or it may store applications or other information for the mobile computing device 650. Specifically, the expansion memory 674 may include instructions for performing or supplementing the above processing, and may also include secure information. For example, the expansion memory 674 may be provided as a security module for the mobile computing device 650 and may be programmed with instructions that enable secure use of the mobile computing device 650. In addition, a secure application may be provided via the SIMM card, along with additional information, such as placing identification information on the SIMM card using a hack-proof method.

[0075] The memory may include, for example, flash memory and / or NVRAM memory (non-volatile random access memory), as described later. In some implementations, instructions are stored in an information carrier so that when the instructions are executed by one or more processing devices (e.g., processor 652), they perform one or more actions, such as those described above. Instructions can also be stored in one or more storage devices, such as a computer or machine-readable media (e.g., memory 664, storage device 674, or memory on processor 652). In some implementations, instructions can be received by a propagating signal, for example, via transceiver 668 or external interface 662.

[0076] The mobile computing device 650 may communicate wirelessly through a communication interface 666, which may in some cases include digital signal processing circuits. The communication interface 666 may provide communication under various modes or protocols, including, in particular, GSM® voice call (Global System for Mobile Communications), SMS (Short Message Service), EMS (Enhanced Messaging Service), or MMS messaging (Multimedia Messaging Service), CDMA (Code Division Multiple Access), TDMA (Time Division Multiple Access), PDC (Personal Digital Cellular), WCDMA (Wideband Code Division Multiple Access) (registered trademark), CDMA2000, or GPRS (General Purpose Packet Radio Service), LTE, 5G / 6G cellular, etc. Such communication may be performed, for example, by a transceiver 668 using radio frequencies. In addition, short-range communication may be performed using Bluetooth, Wi-Fi, or other such transceivers (not shown). In addition, the GPS (Global Positioning System) receiver module 670 may provide additional navigation-related and location-related radio data to the mobile computing device 650, which may be used as appropriate by applications running on the mobile computing device 650.

[0077] The mobile computing device 650 may also communicate audibly using an audio codec 660 that can receive information spoken by the user and convert it into usable digital information. The audio codec 660 may also generate audible sound for the user, for example, through the speaker in the handset of the mobile computing device 650. Such sound may include sounds from voice calls, recorded sounds (e.g., voice messages, music files, etc.), and sounds generated by applications running on the mobile computing device 650.

[0078] The mobile computing device 650 may be implemented in several different forms, as shown in the figure. For example, the mobile computing device 650 may be implemented as a mobile phone 680. The mobile computing device 650 may also be implemented as part of a smartphone 682, a personal digital assistant (PDCA), or other similar mobile device.

[0079] According to one common implementation, this specification describes an improved goniometer with a user interface that guides a physician through multi-point biomechanical examination. The user interface includes images that provide the physician with information, such as how to perform each step in the biomedical examination. For example, for a particular biomedical examination, the user interface may show how the physician should position the goniometer on the patient or how to hold or move the goniometer in order to register accurate measurements.

[0080] In some implementations, the goniometer device displays a user interface on the device's display. For example, in Figure 3, the display 306 of device 305 can be used to display a user interface that guides a physician or user through multipoint biomechanical testing. The physician or user can view the user interface on display 306 and then proceed to perform biomechanical motion measurements based on the tutorial displayed on the user interface. The measurements may include one or more angular measurements, as shown in stages A-C of Figure 3.

[0081] The improved goniometer may be implemented in any suitable device capable of measuring one-dimensional, two-dimensional, or three-dimensional angles. To improve accuracy, measurements along certain axes may be disabled, for example, by temporarily disabling certain hardware, when performing measurements that do not require those axes to be measured. An indicator of active and disabled axes may be shown within the user interface.

[0082] The improved techniques and devices described herein address musculoskeletal injuries that burden companies with millions of dollars annually in worker compensation claims and health insurance costs, and, in the case of sports organization time, significant loss of player time due to players on the invalidation list.

[0083] Regarding the workforce, the World Health Organization states that "the lifetime prevalence of nonspecific (common) back pain is estimated to be 60% to 70% in developed industrial countries." The American Academy of Orthopaedic Surgeons reports the following: "In 2004, 25.9 million people lost an average of 7.2 days of work due to back pain. A total of 186.7 million days of work were lost that year."

[0084] The Bureau of Labor Statistics reports that "fatigue and physical reactions" accounted for the largest percentage of lost work, particularly among workers, cargo, stock and material movers, and nursing assistants. Specifically, the Bureau of Labor Statistics states that "of the 443,560 cases of sprains, strains, and tears reported in 2012, 63% were the result of fatigue and physical reactions." Of that 63%, the most common was the back (36%), followed by the shoulder (13%) and knee (12%).

[0085] Regarding sports organizations, according to 2016 statistics, as of October 7, there were 113 players on the invalidation list, with salaries totaling $396 million, or 12.4 percent of MLB's total payroll.

[0086] 2018 Statistics: As of February 12, 3,798 games have been lost due to injury, a 42 percent increase across the NBA compared to the same percentage of games last season. 2019 Statistics: A total of 50.9% of all NHL players lost one or more games during a season of play, and injuries accounted for approximately $218 million in total payroll costs annually. Head / neck injuries and leg / foot injuries were the most expensive in terms of overall costs, while head / neck and shoulder injuries had the highest average costs.

[0087] An average NFL team loses $11,500,000 per season just on the base salaries of injured athletes, and after initially spending $70,800,000 to win one game, each additional win requires an additional $2,300,000 on available players.

[0088] Injuries play a significant role in a team's potential for success. Given that we know certain injuries are preventable and numerous modifiable risk factors exist, this highlights the importance of not only demonstrating problems but also using appropriate management and analysis to resolve them.

[0089] The improved techniques and devices described herein generate risk mitigation / operational cost reduction strategies and injury prevention models based on biomechanical testing, along with medical biomarkers and qualitative and quantitative questioning. The testing may yield data to be used in treatment / exercise-based models to prevent or treat assessed injuries and reduce time losses due to injuries that cost workers compensation claims, health insurance costs, and, in the case of sports organizations, millions of dollars to teams.

[0090] Corporate wellness programs incorporating nutritional guidance, in-house gyms and exercise classes, and alternatives such as wearable devices designed to track data including sleep patterns and steps are being implemented with the hope of improving the overall health of employees and preventing conditions like heart attacks, strokes, and diabetes.

[0091] The drawbacks of these alternatives may include the fact that the collected data is not necessarily used to generate a specific and personalized health approach for that employee or athlete. While these alternatives may improve an employee's overall health and / or reduce their chances of injury if the employee / athlete is responsible and self-motivated, they do not help predict, avoid, or treat specific non-traumatic musculoskeletal injuries. Non-traumatic injuries account for a large portion of compensation claims for company workers and, globally, account for a large portion of sports time spent on the disabled list, as opposed to trauma-induced or acute illnesses such as heart attacks and strokes, among others.

[0092] Embodiments described herein, including improved goniometers and methods using such improved goniometers, can be used to predict and address non-traumatic musculoskeletal injuries. As described above, non-traumatic musculoskeletal injuries, such as lower back pain, hip pain, and repetitive stress injuries, account for a large portion of the time lost in workers' compensation claims and invalidation lists. The impact of such musculoskeletal injuries represents a significant expense for businesses and / or organizations.

[0093] Biomechanical screening, at least in part, based on biomechanical testing, collects data directly related to the biomechanics of the musculoskeletal structures involved in the movement behind the daily routine tasks that employees and athletes need to perform. Any abnormalities in this data indicate injuries that have already occurred or predict future injuries. Treatment approaches are directly related to the data collected from this screening and are monitored to ensure that the data returns to the normal range.

[0094] According to one exemplary implementation, the improved technique described herein includes a detailed 16-point biomechanical examination. This group of 16 data points may include one or more of the following ranges of motion: big toe extension, weighted dorsiflexion, tibial internal and external rotation, obturator internus, quadriceps femoris, piriformis, thoracic / lumbar junction, shoulder flexion, shoulder external rotation, shoulder external rotation with flexion, wrist pronation, wrist supination, wrist flexion, wrist extension, neck rotation / extension, and neck lateral flexion.

[0095] One or more of the ranges of motion in a 16-point biomechanical test can be measured by an improved goniometer using the method described herein. For example, the improved goniometer can be used to measure the angle of the toe in order to obtain data relating to the big toe extension data point of a 16-point biomechanical test.

[0096] This grouping of data points was discovered over years of treating thousands of athletes and clients. This particular set of data points has been demonstrated to be inherently highly predictive for multiple musculoskeletal injuries.

[0097] Next, each data point collected by a hardware tool, such as one or more components of an improved goniometer, is organized using a software tool and then processed by an algorithm that emphasizes a specific color (e.g., red, yellow, or green).

[0098] The color associated with each data point is based on a key performance indicator (KPI). The KPI for each data point is based on several years of empirically collected data, currently calculated via an algorithm provided by the software platform.

[0099] In some implementations, the software platform can be a component of the improved goniometer. For example, when a smartphone is used as a component of the improved goniometer, the smartphone can be used as a software platform to process data for assigning KPIs to a given data point based on the acquired data.

[0100] In some implementations, the software platform can be a server communicatively connected to the improved goniometer. For example, the improved goniometer can acquire raw data from data points of a biomechanical examination. The improved goniometer can then send the data to a server that partially functions as a software platform, so that the server assigns KPIs based on the data acquired by the improved goniometer for a given data point.

[0101] In this example, in a software platform, green highlighting indicates data points within the range considered normal, representing optimal joint mechanism and establishing that the athlete is least likely to suffer non-traumatic injury. Yellow highlighting indicates data points outside the range considered normal but smaller than the optimal joint mechanism, indicating a higher probability of non-traumatic injury. Red highlighting indicates data points outside the range considered normal, indicating a higher probability of non-traumatic injury.

[0102] KPIs not only determine when to take action regarding treatment, but also what types of treatment and exercise are needed to better modify the data. The data is then monitored by the platform throughout the treatment / intervention and corrected according to how the data points / colors change during re-examination.

[0103] Anatomically speaking, the kinetic chain refers to the interconnected groups of body segments, joints, and muscles that work together to perform a movement, as well as the parts of the spine to which they connect. These movements comprise the everyday tasks, leading up to the more complex movements seen in professional sports.

[0104] The upper kinetic chain includes the fingers, wrists, forearms, elbows, upper arms, shoulders, scapulae, and spine. The lower kinetic chain includes the toes, feet, ankles, lower limbs, knees, upper limbs, buttocks, pelvis, and spine. In both chains, each joint can perform a variety of movements independently. Depending on whether the distal end of the chain is fixed or moves freely without restriction, each movement is classified as either closed or open.

[0105] To efficiently complete movement, each joint and muscle working together must not only move symmetrically, but also have a specific range of motion to maintain the most efficient and long-term movement patterns of each segment. From the toes to the upper torso, a lack of proper mobility, strength, and / or stability can lead to improper movement patterns. The term "compensation" comes to mind. Over time, compensatory patterns, including improper range of motion, strength, and stability, begin to stress the body. This stress can lead to chronic pain, discomfort, and / or even musculoskeletal injuries.

[0106] Synovial joints allow the body to move over a very wide range of motion. Each movement in a synovial joint results from the contraction or relaxation of muscles attached to the bones on either side of the joint. The type of movement that can be produced in a synovial joint is determined by its structural type. Ball-and-socket joints give the maximum range of motion in individual joints, but in other areas of the body, several joints can work together to produce specific movements. Overall, each type of synovial joint is necessary to provide the body with its great flexibility and mobility. There are many types of movements that can occur in synovial joints. Types of movement are generally paired, with one being the opposite of the other.

[0107] In terms of physiology and neurology, compensatory patterns develop in human movement for a number of reasons. From injury to "activities of daily living," the human body is constantly being formed and remodeled through mechanotransduction, a process in which biomechanical forces, combined with biochemical reactions and energy flows, literally "deform" (or change the shape of) every single cell.

[0108] Furthermore, mechanotransduction manipulates and modifies corresponding strands of DNA. In other words, human movement continuously shapes and reshapes the human body. Compensatory patterns are the body's attempts to fill a deficiency in movement in one area by adding new movements. More specifically, compensatory patterns are neuromuscular strategies of including "new" firing sequences (e.g., motor units and muscles) and / or utilizing structural dependencies to supplement or avoid other firing sequences and / or structural dependencies (e.g., bones, ligaments, tendons, fascia, and joint structures).

[0109] To perform any movement precisely (whether it means reaching for a glass of water without tipping it over, or skating across an ice rink without falling), the brain needs to learn exactly which muscles to activate and how.

[0110] Regarding core concepts of movement, including mutual inhibition, mutual correlation, and the medial vestibular pathway, mutual inhibition is a neuromuscular reflex. Increased neural drive of a muscle or muscle group decreases the neural activity of a functional antagonist. This plays a crucial role in improving the efficiency of the human motor system and creating ideal joint kinematics, e.g., the movement of joint forces. This more nuanced definition encompasses the role of mutual inhibition in more complex problems of human movement science. Perhaps the most important point made in this definition is the use of the terms "increase" and "decrease," meaning that mutual inhibition is not a simple "on or off" function.

[0111] For example, postural dysfunction resulting in adaptive shortening and hypertonicity inhibits the functional antagonist (tight lumbar-inhibiting gluteus maximus), but does not reduce neural drive to the gluteus maximus complex, allowing for full (though not optimal) movement and function.

[0112] Regarding cross-connection, the neural communication that works to simultaneously generate asymmetrical movements is the integration of the left and right hemispheres of the brain, with both hemispheres working in partnership. For example, contralateral movement is when a limb on one side of the body performs something different from the limb on the other side, but it can also include any movement that crosses the midline, such as the right hand touching the left knee, and problems with left-right brain communication for full cognitive function. Developmental disorders and abnormal information processing (e.g., autism and schizophrenia) are associated with "integrative dysfunction between nervous systems," which suggests that an optimal balance between the cerebral hemispheres is essential.

[0113] Regarding neuroplasticity, our brains are constantly reshaping through experience. With each repetition of thought, emotion, and movement, we compel new neural pathways in the brain to support stronger cortical pathways. Neuroplasticity refers to the muscle building of the brain, and through repetition, proper motor control, and symmetry, it is possible to fix and / or alter muscular imbalances, thereby reducing the chances of musculoskeletal injury.

[0114] Regarding the medial vestibular pathway, the medial vestibulospinal tract is the pathway through which input from the vestibular sensory apparatus is used to adjust the orientation of the head and body in space. The vestibular system senses the angular and linear acceleration of the head in three dimensions and generates vestibular-ocular and vestibular-spinal reflexes that stabilize the visual image on the retina during head movement and adjust posture (respectively).

[0115] However, this sensory system also plays a role in cognition. Our interaction with our environment arises from our five senses. Whether we are completing daily tasks at the highest level of sports or not, we are constantly trying to interpret the world we inhabit. Brain and behavior are terms used to describe the interactions we have with the world around us as human beings. The mechanisms behind taking in information stem from our bodily awareness in space and time. Motor skills and / or motor learning are the body's ability to complete / learn tasks given the information at hand.

[0116] The vestibulospinal pathway significantly influences the activation of the pelvic floor muscles. When the vestibular system is activated by head and eye movements, the ipsilateral pelvic floor muscles are activated. For example, when rotating the head to the left, the left cerebellum, the left vestibulospinal pathway, and the left pelvic floor muscles are activated.

[0117] Analysis of the vestibular system may include the following: a. Rotation and (R-VOR)-rotational vestibular reflex i. Horizontal rotation (left or right) ii. Vertical rotation (flexion or extension) b. Translational (T-VOR) - translational vestibulo-ocular reflex i. Spheroid 1.Up and down 2. Before and after ii. Utricular sac 1. Straight line horizontal left or right 2. Head tilt c. Notes i. Horizontal rotation can also stimulate the utricle. ii. Flexion and extension can stimulate the saccule. The utricle is part of the linear vestibular region. a. The left utricle is activated by the tilt of the left temporal region. b. Rotation of the left head c. A straight horizontal movement to the left, like a skater with their eyes fixed on a target. d. The left utricle has a significant influence on the vestibulospinal pathway. e. The left vestibulospinal pathway has a significant impact on the left pelvic floor muscles. The analysis may include the following "looking at the head" procedure:

[0118] a. If the head is tilted to the left and the left eye is lower than the right eye, the left utricle is weak. b. To correct leftward tilt of the head, vertical head movement, and vertical tracking movement. i. Correct both T-VOR (translational VOR). c. Next, have the client perform horizontal head movements or tracking eye movements to the right. The analysis may include the following "looking at Romberg" procedure:

[0119] a. If the head is tilted to the left with a leftward sway and the left eye lower, it indicates a weak utricle on the left, a weak left vestibulospinal pathway on the left, and compensation for the left pelvic floor muscles and spine such as multifidus. b. Also, having a reduced range of motion in internal rotation of the hip. The left cerebellar and left vestibulospinal pathways may be improved by one or more of the following: a. Head movement b.Eye movements c. Skaters with visual fixation then d. The following will be improved. i. Activate the left pelvic floor muscles. ii. Left pelvic stability iii. Improved range of motion in the left hip joint In another common implementation, the improved technique described herein may include a 19-point biomechanical examination, and / or the improved device described herein may assist a physician in performing this examination. In some implementations, the improved technique described herein may include a 21-point biomechanical examination, including femoral internal rotation and shoulder extension. Generally, the number of points used for evaluation may depend on the sports or physical roles that the person can perform.

[0120] For example, an improved goniometer may be used to measure angles associated with one or more data points of a given biomechanical test, including a 19-point biomechanical test. In general, it is possible to generate a biomechanical test using any number of points based on the requirements of a given test.

[0121] The 19-point biomechanical examination may include the following: Data point 1- Thumb toe extension Big toe extension affects the lateral sling and gluteus medius firing of the lower limb. Differential diagnosis: plantar fasciitis, IT band syndrome, low back pain, lateral meniscus.

[0122] Data point 2 - Weighted dorsiflexion Differential diagnosis: Ankle injury, shin splints, potential Achilles tendon injury, hamstring pain. Data points 3 and 4 - Tibial rotation. Internal and external. Tibial rotation can reveal the relationship between the hip and ankle, potential meniscal problems, the pes anserinus, and, most importantly, the integrity of the knee.

[0123] Data point 5 - External rotation of the femur In some implementations, femoral external rotation may be performed in conjunction with extension. For example, the patient may flex their contralateral hip joint, extend the opposite hip joint, and externally rotate the opposite leg. Measurement may include measuring the opposite leg or the flexed leg from a given starting position, depending on the implementation.

[0124] In some implementations, the examination may include femoral internal rotation. In some implementations, femoral internal rotation may be performed in conjunction with extension. For example, the patient may flex their contralateral hip joint, extend the opposite hip joint, and internally rotate the opposite leg. The measurement may include measuring the opposite leg or the flexed leg from a given starting position, depending on the implementation.

[0125] Data point 6 - Piriformis muscle Differential diagnosis: Sciatica, lower back pain, herniated disc, hip joint dysfunction (labral laceration, arthritis, cam lesion), and sports hernia.

[0126] Data point 7 - Quadratus femoris muscle Differential diagnosis: Upper hamstring injury, gluteus medius firing. Power 8 - Obturator Internus Differential diagnosis: hip joint integrity, cam lesion, lumbar spine facet integrity, low back pain, herniated disc, sports herniation.

[0127] Data point 9 - Hip extension Differential diagnosis: Camel lesion, herniated disc, facet syndrome, abdominal laceration / sports hernia, low back pain, hip flexor bursitis, rectus femoris laceration.

[0128] Data point 10 - Hip flexion Data point 11 - Thoracolumbar junction Differential diagnosis: Oblique tension, lower back pain, chest pain, ipsilateral shoulder pain.

[0129] Data point 12 - Shoulder flexion. Differential diagnosis: Shoulder impingement syndrome, scapular dysfunction, ipsilateral latissimus dorsi muscle tension, shoulder bursitis.

[0130] Data point 13 - Shoulder abduction and external rotation at 30 degrees Differential diagnosis: Impingement syndrome, capsule inflammation, mild pectoral muscle tension. Data point 14 - Shoulder flexion and external rotation (modified Apley shoulder test) Differential diagnosis: shoulder impingement, anterior translation of the scapula, ipsilateral neck pain, scapular dysfunction.

[0131] Data point 15 - Cervical rotation (left and right). Data point 16 - neck rotation Differential diagnosis: Cervical disc herniation, TOS, nerve plexus compression, previous head trauma.

[0132] Data point 17 - Wrist extension Differential diagnosis: flexor muscle injury, carpal tunnel syndrome / nerve compression. Data point 18 - Wrist supination Differential diagnosis: Flexor muscle injury, carpal tunnel syndrome.

[0133] Data point 19 - Wrist pronation Differential diagnosis: Contralateral supinator muscle (deep branch of the radial nerve), flexion, stretching of the superficial branch of the radial nerve, compression of the median nerve.

[0134] Several implementations are described. Nevertheless, it is understood that various modifications may be made without deviating from the intent and scope of this disclosure. For example, the various forms of the flow shown above may be used with steps rearranged, added, or removed.

[0135] All embodiments of the present invention and the functional operations described herein may be implemented by digital electronic circuits, or by computer software, firmware, or hardware, or one or more combinations thereof, including the structures disclosed herein and their structural equivalents. Embodiments of the present invention can be implemented as one or more modules of computer program instructions encoded on a computer-readable medium for execution by one or more computer program products, for example, for use by a data processing device, or for controlling the operation of a data processing device. The computer-readable medium can be a machine-readable storage device, a machine-readable storage substrate, a memory device, a composition that provides a machine-readable propagating signal, or one or more combinations thereof. The term “data processing device” encompasses all devices and machines for processing data, including, for example, a programmable processor, a computer, or multiple processors or computers. In addition to hardware, a device can include code that generates an execution environment for the computer program, for example, processor firmware, a protocol stack, a database management system, an operating system, or code that constitutes one or more combinations thereof. A propagating signal is an artificially generated signal, for example, a machine-generated electrical signal, optical signal, or electromagnetic signal generated to encode information for transmission to a suitable receiver device.

[0136] Computer programs (also known as programs, software, software applications, scripts, or code) can be written in any form of programming language, including compiled or interpreted languages, and can be deployed in any form, including as standalone programs or as modules, components, subroutines, or other units suitable for use in a computing environment. Computer programs do not necessarily correspond to files in a file system. A program can be stored in a single file dedicated to it, as part of a file that holds other programs or data (e.g., one or more scripts stored in a markup language document), or in multiple collaborative files (e.g., a file that stores one or more modules, subprograms, or parts of code). Computer programs can be deployed to run on a single computer, or on multiple computers located in one site or distributed across multiple sites and interconnected by a communication network.

[0137] The processing and logic flows described herein can be performed by one or more programmable processors that execute one or more computer programs to function by operating on input data and generating outputs. The processing and logic flows can also be performed by dedicated logic circuits, such as FPGAs (Field-Programmable Gate Arrays) or ASICs (Application-Specific Integrated Circuits), and the devices can also be implemented as dedicated logic circuits, such as FPGAs or ASICs.

[0138] Processors suitable for executing computer programs include, for example, both general-purpose and dedicated microprocessors, as well as any one or more processors in any type of digital computer. Generally, a processor receives instructions and data from read-only memory, random-access memory, or both. Essential elements of a computer are a processor for executing instructions and one or more memory devices for storing instructions and data. Generally, a computer also includes one or more mass storage devices (e.g., magnetic, magneto-optical disks, or optical disks) for storing data, or is operablely coupled to them to receive data from them, transfer data to them, or both. However, a computer is not required to have such devices. Furthermore, a computer can be incorporated into another device, for example, a tablet computer, a mobile phone, a personal digital assistant (PDA), a mobile audio player, or a Global Positioning System (GPS) receiver. Computer-readable media suitable for storing computer program instructions and data include, for example, all forms of non-volatile memory, media, and memory devices, including semiconductor memory devices (e.g., EPROM, EEPROM, and flash memory devices), magnetic disks (e.g., internal hard disks or removable disks), magneto-optical disks, and CD-ROM and DVD-ROM disks. Processors and memory can be complemented by or incorporated into dedicated logic circuits.

[0139] To provide user interaction, embodiments of the present invention can be implemented on a computer having a display device for displaying information to the user, such as a CRT (cathode ray tube) or LCD (liquid crystal display) monitor, and a keyboard and pointing device, such as a mouse or trackball, on which the user can provide input to the computer. Other types of devices can also be used to provide user interaction, for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback), and the input from the user can be received in any form, including acoustic, voice, or tactile input.

[0140] Embodiments of the present invention can be implemented by a computing system comprising a backend component (e.g., as a data server), or a middleware component (e.g., an application server), or a frontend component (e.g., a client computer having a graphical user interface or a web browser on which a user can interact with an implementation of the present invention), or any combination of one or more such backend, middleware, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include local area networks ("LANs") and wide area networks ("WANs") (e.g., the Internet).

[0141] A computing system can consist of clients and servers. Clients and servers are generally geographically separated and typically interact through a communication network. The relationship between a client and a server arises from computer programs running on each computer that have a client-server relationship with each other.

[0142] This specification contains many details, which should not be construed as limitations on the scope of the invention or the claims, but rather as descriptions of features specific to particular embodiments of the invention. Certain features described herein in the context of separate embodiments may also be implemented in combination in a single embodiment. In contrast, various features described in the context of a single embodiment may also be implemented separately or in any suitable subcombinations in multiple embodiments. Furthermore, features may be described as acting in a particular combination and may be initially claimed as such, but one or more features from a claimed combination may be removed from the combination in some cases, and the claimed combination may cover subcombinations or variations of subcombinations.

[0143] Similarly, although the operations are shown in a specific order in the drawings, this does not mean that such operations must be performed in a specific or sequential order shown, or that all shown operations must be performed, in order to achieve the desired result. In certain situations, multitasking and parallel processing may be advantageous. Furthermore, the separation of various system components in the embodiments described above does not mean that such separation is required in all embodiments, and it is understood that the described program components and systems can generally be integrated together into a single software product or packaged into multiple software products.

[0144] In each example where an HTML file is mentioned, other file types or formats may be substituted. For example, an HTML file may be replaced by XML, JSON, plain text, or other types of files. Furthermore, where a table or hash table is mentioned, other data structures (such as a spreadsheet, relational database, or structured file) may be used.

[0145] Specific embodiments of the present invention are described. Other embodiments are within the scope of the following claims. For example, the steps described in the claims can be performed in a different order, and the desired results can still be achieved.

Claims

1. A method for generating angle measurements, It is a goniometer, An accelerometer configured to output angular orientation values ​​for each of three different axes, wherein each angular orientation value is raw data representing the angle of the goniometer with respect to the corresponding axis among the three different axes, (i) sequence data showing a sequence of multiple angle measurements for a biomechanical examination, and (ii) data showing a subset of the three different axes related to each angle measurement, wherein the subset of axes related to different angle measurements in the sequence is a database having different axes. An input unit for receiving a start user input indicating that the user will start an angle measurement when the goniometer is held at a given start position for angle measurement, and an end user input indicating that the user will end the angle measurement when the goniometer is held at a given end position for angle measurement, A goniometer comprising a display unit for outputting the angle measurement value calculated for each angle measurement in the sequence, For each angle measurement in the sequence, until angle measurements are obtained for all angle measurements in the sequence, in the order specified by the sequence data stored in the database. The process of receiving the aforementioned start user input, The process of obtaining the respective angular orientation values ​​for each of the three different axes with respect to the aforementioned starting position, The process of receiving the aforementioned termination user input, The process of obtaining the respective angular orientation values ​​for each of the three different axes for the aforementioned end position, An angle orientation value generation step, comprising: generating angle orientation values ​​processed for the start position and the end position based on data representing the subset of the three different axes related to the angle measurement, wherein the processed angle orientation values ​​exclude one or more angle orientation values ​​for the start position and the end position corresponding to axes not related to the angle measurement; A step of calculating the angle measurement for the angle measurement based on the angle orientation values ​​processed for the start position and the end position, A step of providing the calculated angle measurement value to the display unit for output, A method for performing the steps of providing the display unit with an output command indicating how to move the goniometer.

2. The angle orientation value generation step is as follows: A step of determining the current measurement in the sequence of angle measurements based on the above order, The method according to claim 1, comprising the step of determining an element of data to be excluded based on the current measurement.

3. The angle orientation value generation step is as follows: The method according to claim 1, further comprising the step of analyzing each measurement in the sequence of angle measurements.

4. The method according to claim 1, further comprising the step of outputting an image to the display unit that provides the user with information on how to perform the measurement.

5. The method according to claim 4, wherein the image includes graphical information indicating the location on the patient's body where the goniometer is positioned before the measurement is started.

6. The method according to claim 1, wherein the sequence of angle measurements includes measuring big toe extension.

7. A non-temporary computer-readable medium storing one or more instructions, wherein the instructions are used by a computer system. It is a goniometer, An accelerometer configured to output angular orientation values ​​for each of three different axes, wherein each angular orientation value is raw data representing the angle of the goniometer with respect to the corresponding axis among the three different axes, (i) sequence data showing a sequence of multiple angle measurements for a biomechanical examination, and (ii) data showing a subset of the three different axes related to each angle measurement, wherein the subset of axes related to different angle measurements in the sequence is a database having different axes. An input unit for receiving a start user input indicating that the user will start an angle measurement when the goniometer is held at a given start position for angle measurement, and an end user input indicating that the user will end the angle measurement when the goniometer is held at a given end position for angle measurement, A goniometer comprising a display unit for outputting the angle measurement value calculated for each angle measurement in the sequence, For each angle measurement in the sequence, until angle measurements are obtained for all angle measurements in the sequence, in the order specified by the sequence data stored in the database. The process of receiving the aforementioned start user input, The process of obtaining the respective angular orientation values ​​for each of the three different axes with respect to the aforementioned starting position, The process of receiving the aforementioned termination user input, The process of obtaining the respective angular orientation values ​​for each of the three different axes for the aforementioned end position, An angle orientation value generation step, comprising: generating angle orientation values ​​processed for the start position and the end position based on data representing the subset of the three different axes related to the angle measurement, wherein the processed angle orientation values ​​exclude one or more angle orientation values ​​for the start position and the end position corresponding to axes not related to the angle measurement; A step of calculating the angle measurement for the angle measurement based on the angle orientation values ​​processed for the start position and the end position, A step of providing the calculated angle measurement value to the display unit for output, A medium capable of performing an operation comprising the steps of providing the display unit for output instructions indicating how to move the goniometer.

8. The angle orientation value generation step is as follows: A step of determining the current measurement in the sequence of angle measurements based on the above order, The medium according to claim 7, comprising the step of determining an element of data to be excluded based on the current measurement.

9. The angle orientation value generation step is as follows: The medium according to claim 7, comprising the step of analyzing each measurement in the sequence of angle measurements.

10. The medium according to claim 7, further comprising the step of outputting an image to the display unit that provides the user with information on how to perform the measurement.

11. The medium according to claim 10, wherein the image includes graphical information indicating the location on the patient's body where the goniometer is positioned before the measurement is started.

12. The medium according to claim 7, wherein the sequence of angle measurement includes big toe extension measurement.

13. It is a system, It is a goniometer, An accelerometer configured to output angular orientation values ​​for each of three different axes, wherein each angular orientation value is raw data representing the angle of the goniometer with respect to the corresponding axis among the three different axes, (i) sequence data showing a sequence of multiple angle measurements for a biomechanical examination, and (ii) data showing a subset of the three different axes related to each angle measurement, wherein the subset of axes related to different angle measurements in the sequence is a database having different axes. An input unit for receiving a start user input indicating that the user will start an angle measurement when the goniometer is held at a given start position for angle measurement, and an end user input indicating that the user will end the angle measurement when the goniometer is held at a given end position for angle measurement, A goniometer comprising a display unit for outputting the angle measurement value calculated for each angle measurement in the sequence, One or more computers, The system comprises one or more computer memory devices that are interconnected and operable with one or more computers, and each having a machine-readable medium that stores one or more tangible, non-temporary instructions, wherein, when the instructions are executed by the one or more computers, the goniometer, For each angle measurement in the sequence, until angle measurements are obtained for all angle measurements in the sequence, in the order specified by the sequence data stored in the database. The process of receiving the aforementioned start user input, The process of obtaining the respective angular orientation values ​​for each of the three different axes with respect to the aforementioned starting position, The process of receiving the aforementioned termination user input, The process of obtaining the respective angular orientation values ​​for each of the three different axes for the aforementioned end position, An angle orientation value generation step, comprising: generating angle orientation values ​​processed for the start position and the end position based on data representing the subset of the three different axes related to the angle measurement, wherein the processed angle orientation values ​​exclude one or more angle orientation values ​​for the start position and the end position corresponding to axes not related to the angle measurement; A step of calculating the angle measurement for the angle measurement based on the angle orientation values ​​processed for the start position and the end position, A step of providing the calculated angle measurement value to the display unit for output, A system that performs one or more operations, comprising the steps of: providing the display unit for output an instruction indicating how to move the goniometer.

14. The angle orientation value generation step is as follows: A step of determining the current measurement in the sequence of angle measurements based on the above order, The system according to claim 13, comprising the step of determining an element of data to be excluded based on the current measurement.

15. The angle orientation value generation step is as follows: The system according to claim 13, further comprising the step of analyzing each measurement in the sequence of angle measurements.

16. The system according to claim 13, further comprising the step of outputting an image to the display unit that provides the user with information on how to perform the measurement.

17. The system according to claim 16, wherein the image includes graphical information indicating the location on the patient's body where the goniometer is positioned before the measurement is started.

18. The system according to claim 13, wherein the sequence of angle measurement includes big toe extension measurement.

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