Ergonomics enhancement system with wearable sensors, and related methods

Abstract

To provide a wearable ergonomics improvement system, and a related method.SOLUTION: An ergonomics improvement system of embodiments comprises a membrane which has a first frame comprising a plurality of first notches for defining a first pattern 314. The system also comprises a sensor which includes a second frame comprising a plurality of second notches for defining a second pattern 324 and the sensor is coupled to the membrane. The first pattern supplements the second pattern.SELECTED DRAWING: Figure 3D-3E

Description

[Technical Field]

[0001]

[0001] This disclosure relates in general to wearable sensors, and more particularly to ergonomics enhancement systems having wearable sensors, and related methods. [Background technology]

[0002]

[0002] Users in warehouses and manufacturing facilities perform a variety of physical and / or repetitive tasks. Such physical tasks may include lifting and / or holding relatively heavy objects for extended periods and / or processes requiring numerous repetitive movements (such as manually polishing structures by repeatedly moving a polishing tool in a circular motion). At times, performing physical tasks can be high-intensity activities. [Overview of the Initiative]

[0003]

[0003] The exemplary ergonomics enhancement systems disclosed herein include wearable ergonomics enhancement systems. The exemplary ergonomics enhancement system includes a membrane having a first frame, the first frame having a plurality of first notches defining a first pattern. The system includes a sensor attached to the membrane, having a second frame, the second frame having a plurality of second notches defining a second pattern, the first pattern complementing the second pattern.

[0004]

[0004] Another exemplary system disclosed herein for tracking the movement of limbs of the body includes a first membrane sensor connected to the shoulder of the body. The first membrane sensor generates an output in response to shoulder movement to detect at least one of the position or rotation of the shoulder. The system includes a second membrane sensor connected to the elbow of the body to generate a second output in response to elbow movement to detect at least one of the position or rotation of the elbow. The system further includes a third membrane sensor connected to the wrist of the body to generate a third output in response to hand movement to detect at least one of the position or rotation of the hand.

[0005]

[0005] The exemplary methods disclosed herein include tracking the movement of limbs of a body. The system includes determining the position of the limb relative to the body based on a first output from a first membrane sensor, a second output from a second membrane sensor, and a third output from a third membrane sensor. The system includes determining the position of the limb relative to the body based on the received first, second, or third output. The system includes receiving a second output from a load sensor attached to the body. The system includes determining the load on the body based on the received second output. The system includes receiving a third output from a step scanner attached to the body. The system includes determining the position of the foot by detecting the position of the body's left foot relative to the position of the body's right foot based on a third output from a pressure sensor. The system includes comparing the determined limb position with position thresholds associated with the determined load and the determined foot position. The system includes determining whether the determined position exceeds the position threshold. If the determined position exceeds the position threshold, the system includes generating a warning signal. [Brief explanation of the drawing]

[0006] [Figure 1]

[0006] This is an example of an ergonomic improvement system based on the teachings disclosed in this book. [Figure 2A]

[0007] Figure 1 shows a magnified view of an exemplary upper body sensor in an ergonomics enhancement system. [Figure 2B]

[0008] Figure 2A is a schematic diagram of the exemplary output of the upper body sensor shown in the example. [Figure 3A]

[0009] This is a side view of a portion of an exemplary membrane sensor disclosed herein, which may be used to implement the exemplary upper body sensor shown in Figures 1 and 2A. [Figure 3B-3C]

[0010]

[0011] Figure 3B is a top view of the exemplary membrane of the exemplary membrane sensor shown in Figure 3A, and Figure 3C is a magnified view of the exemplary membrane in Figure 3B. [Figure 3D-3E]

[0012]

[0013] Figure 3D is a top view of the exemplary membrane sensor shown in Figure 3A, and Figure 3E is a magnified view of the exemplary sensor shown in Figure 3D. [Figure 4A]

[0014] This is a side view of a portion of another exemplary membrane sensor disclosed herein, which may be used to implement the exemplary upper body sensor shown in Figures 1 and 2A. [Figure 4B-4C]

[0015]

[0016] Figure 4B is a top view of the exemplary membrane of the exemplary membrane sensor shown in Figure 4A, and Figure 4C is a magnified view of the exemplary membrane shown in Figure 4B. [Figure 4D-4E]

[0017]

[0018] Figure 4D is a top view of the exemplary membrane sensor shown in Figure 4A, and Figure 4E is a magnified view of the exemplary sensor shown in Figure 4D. [Figure 5]

[0019] These are schematic diagrams of exemplary displacement and load distribution for the baseline membrane sensor, the exemplary membrane sensors shown in Figures 3A to 3E, and the exemplary membrane sensors shown in Figures 4A to 4E. [Figure 6A]

[0020] Another exemplary membrane sensor 600a disclosed herein is shown, which may be used to implement the exemplary upper body sensor of the exemplary ergonomic enhancement system in Figures 1 and 2. [Figure 6B] Another exemplary membrane sensor 600b disclosed herein is shown, which may be used to implement the exemplary upper body sensor of the exemplary ergonomic enhancement system in Figures 1 and 2. [Figure 6C] Another exemplary membrane sensor 600c disclosed herein is shown, which may be used to implement the exemplary upper body sensor in the exemplary ergonomic enhancement system of Figures 1 and 2. [Figure 6D]Another exemplary membrane sensor 600d disclosed in this book that can be used to implement an exemplary upper body sensor of the exemplary ergonomics improvement system of FIGS. 1 and 2 is shown. [Figure 7A]

[0021] It is an exemplary lower body sensor system of the exemplary ergonomics improvement system of FIG. 1. [Figure 7B]

[0022] It is another exemplary lower body sensor system disclosed in this book that can be used to implement the exemplary ergonomics improvement system of FIG. 1. [Figure 8A]

[0023] It is a schematic diagram of an exemplary output of the exemplary lower body sensor system of FIG. 7A. [Figure 8B] It is a schematic diagram of an exemplary output of the exemplary lower body sensor system of FIG. 7A. [Figure 9]

[0024] It is a block diagram of an exemplary controller of the exemplary ergonomics improvement system of FIG. 1. [Figure 10]

[0025] It is an example of a flowchart representing an exemplary method that can be implemented by an exemplary controller of FIG. 9 of the exemplary ergonomics improvement system of FIG. 1. [Figure 11]

[0026] It is an example of a flowchart representing an exemplary method for calibrating an exemplary upper body sensor system of the exemplary ergonomics improvement system of FIG. 1. [Figure 12]

[0027] It is an exemplary diagram representing an exemplary sensor calibration position disclosed in this book that can be used to implement the exemplary calibration of FIG. 11. [Figure 13]

[0028] It is a block diagram of an exemplary processing platform constructed to execute the instructions of FIGS. 10 and 11 to implement an exemplary controller of the exemplary ergonomics improvement system disclosed in this book.

Mode for Carrying Out the Invention

[0007]

[0029] The drawings are not proportional to the actual size. Instead, the thickness of layers or regions may be enlarged in the drawings. Generally, the same reference numeral is used throughout the drawings(s) and specification to refer to the same or similar parts. Where used in this patent application, any statement that any part (e.g., layer, membrane, area, region, or plate) exists on another part (e.g., placed, positioned, arranged, formed, etc.) in any way indicates that the referred part is in contact with the other part, or that the referred part exists above the other part with one or more intermediate parts positioned between them. References to connections (attached, coupled, connected, joined, etc.) should be interpreted broadly and, unless otherwise indicated, may include intermediate members between sets of elements and relative motion between elements. Thus, references to connections do not necessarily imply that two elements are directly connected and have a fixed relationship with one another. The statement that any part is "in contact" with another part means that there is no intermediate part between the two parts. In the diagram, layers and regions are illustrated with clear lines and boundaries, but some or all of these lines and / or boundaries may be idealized. In reality, boundaries and / or lines may be unobservable, mixed, and / or irregular.

[0008]

[0030] In this book, descriptive terms such as “first,” “second,” and “third” are used to identify multiple elements or components that may be referred to separately. Unless otherwise specified or understood based on the context in which they are used, such descriptive terms are not intended to represent priority, physical order or arrangement in an enumeration, or temporal order, but are simply used as symbols to refer to multiple elements or components separately in order to facilitate understanding of the disclosed examples. In some examples, the descriptive term “first” may be used to refer to an element in a “mode for carrying out the invention,” while in the claims, the same element may be referred to using different descriptive terms such as “second” or “third.” In such examples, it should be understood that such descriptive terms are used simply to facilitate reference to multiple elements or components.

[0009]

[0031] Manufacturing processes often require users to perform various types of repetitive physical tasks and / or lift relatively heavy objects. Performing repetitive physical tasks in certain manufacturing processes can pose undesirable risks to the users performing such tasks. For example, repetitive physical tasks can lead to muscle and / or tendon fatigue over time. Muscle fatigue can reduce muscle strength, and / or tendon fatigue can reduce the structural capacity of tendons.

[0010]

[0032] To improve ergonomics awareness, ergonomic enhancement systems have been developed that monitor and / or quantify musculoskeletal performance during repetitive physical tasks or manufacturing processes. Generally, prior art focuses on collecting postural and / or movement information to address injuries. For example, some known systems use sensors to monitor musculoskeletal performance to capture data during repetitive movements. A known system simulation of a person performing a physical task over several cycles is run by a computer system using a musculoskeletal model of this person and at least one of task performance data and task description data. This computer-simulated model can be used to track and / or analyze detected movements. Some known ergonomic enhancement systems use one or more sensors to capture data used with the simulation model. Such sensors can sense force and / or movement. However, the sensors in such known ergonomics enhancement systems do not detect or sense the stress and / or strain applied to one or more joints (e.g., shoulder, elbow, or wrist) of a user performing a physical task.

[0011]

[0033] The exemplary ergonomics enhancement systems disclosed herein use motion, load measurement, and / or foot positioning to determine the load and / or strain on the limbs, limb joints, and / or body when a user performs one or more tasks (e.g., physical tasks involving repetitive movements). The exemplary ergonomics enhancement systems disclosed herein use one or more wearable sensors to track limb movement and / or detect the load and / or strain on the limb joints when a user performs repetitive physical tasks. The exemplary wearable sensors disclosed herein, when combined with the ergonomics enhancement systems, provide a tracking system for tracking limb movement. In some examples, the wearable sensors disclosed herein may include exemplary upper body sensor systems, lower body sensor systems, and / or combinations of upper body and lower body sensor systems. Data from the exemplary wearable sensors disclosed in this book (e.g., upper body sensor systems and / or exemplary lower body sensor systems) may be used to measure (e.g., collectively or individually) the position of a limb relative to the body, the movement of an entire limb relative to the body, the load and / or strain on the joints of a limb, and / or any movement(s) or angle(s) of a limb, body part (e.g., upper back and lower back), and / or joint(s) relative to the body.

[0012]

[0034] The exemplary wearable sensors disclosed herein include wearable sensors formed from one or more membranes (e.g., one or more metamembranes). The membranes may be one or more appliqués or patches that can be attached to clothing, may be formed as clothing (e.g., a shirt), and / or may be part of clothing (e.g., a sleeve). In some examples, the wearable sensors disclosed herein include exemplary membranes having Kirigami patterns. In some examples, the wearable sensors disclosed herein include exemplary membranes having Auxetic patterns. The Kirigami patterns and / or Auxetic patterns vary (e.g., increase) the flexibility of the sensor to enable it to adapt to a wider range of operations (e.g., more than with another pattern, and / or a sensor with a solid surface without a pattern). In some examples, the Kirigami patterns and / or Auxetic patterns may increase durability and / or resistance to cracking over time. However, the technical advantages are not limited to the examples given above. In some examples, the wearable sensors disclosed herein may include any other type of metafilm and / or membrane having a different pattern. For example, the ergonomic enhancement systems disclosed herein may use various types of wearable sensors and / or metafilms (e.g., kirigami, biaxial kirigami, authentic hexagon, etc.) that can output signals that can be used to track limb movement, load, and strain and / or to acquire limb position data. In some examples, the exemplary wearable sensors disclosed herein may be attached to (e.g., mounted on) one or more limbs of the body and / or positioned across both sides of one or more joints to measure load and / or strain on the limbs of the body. For example, the wearable sensors disclosed herein may be mounted on a user's arm to detect load on the user's shoulder, elbow, and / or wrist. In some cases, wearable sensors may be attached to the user's legs, hips, knees, upper back, and / or lower back to detect load and / or strain in areas such as the knees, hips, neck, upper back, and / or lower back.In some cases, the wearable sensor may be used to measure or detect the position and / or joint angle of a joint associated with the wearable sensor (e.g., the shoulder joint or wrist joint), and for this purpose may be attached proximally to each joint of the limb.

[0013]

[0035] The exemplary ergonomics enhancement systems disclosed herein utilize a lower body sensor system to measure the load supported by the user and to detect the position of the user's feet. The exemplary lower body sensor system disclosed herein may use load cells, pressure sensors, and / or other arbitrary sensors for measuring load and / or weight to measure the load. The exemplary lower body sensor system disclosed herein may use Lider sensors, pressure pads and / or pressure scanning sensors, and / or other arbitrary suitable positioning sensors to detect the position of the feet during physical tasks. The exemplary lower body sensor system disclosed herein may be attached to and / or housed in footwear (e.g., shoes or work boots) worn by the user performing the physical task. In some examples, the exemplary lower body sensors disclosed herein may be located in and / or within the sole of the footwear. Data from the exemplary lower body sensors disclosed herein may be aggregated with data collected from the exemplary upper body sensor system disclosed herein to determine limb movement and / or position. However, in some cases, the ergonomics enhancement systems disclosed herein may use the exemplary upper body sensor system disclosed herein to detect the position of the limbs relative to the body and / or the joint angles of the joints, without using the exemplary lower body sensor system disclosed herein.

[0014]

[0036] The exemplary ergonomics enhancement systems disclosed herein use a controller to process data from the exemplary wearable sensors disclosed herein (e.g., exemplary upper body sensor system and lower body sensor system). For example, during operation, the exemplary controller disclosed herein may receive outputs from the wearable sensors. In some examples, the exemplary controller disclosed herein may compare data from the exemplary wearable sensors with a user baseline threshold. For example, this baseline may be a default value based on the user's first and second conditions. For example, the first condition may be the total amount of load the person is supporting, and the second condition may be the position of the user's feet when the supported load is detected. For example, if a person is standing in a stable (brace) position (e.g., the user's feet are in the stable position shown in Figure 8A) and supporting a weight of 50 pounds, the baseline threshold will not exceed the baseline threshold. However, if the user's feet are in an unstable position (see, for example, Figure 8B) and it is detected that the user is supporting a weight of 50 pounds, this baseline threshold may be exceeded. In some examples, the exemplary controllers disclosed herein may trigger an alarm when wearable sensor data exceeds a user's baseline threshold. The exemplary alarms disclosed herein include, but are not limited to, visual alarms (e.g., light), auditory alarms (e.g., speaker), haptic feedback (e.g., vibration), combinations thereof, and / or any other alarm(s). In some examples, the type of alarm(s) may be selected based on the user's environment (e.g., industrial or manufacturing environment). For example, if the environment may be noisy or busy, or if the task being performed should not be interrupted by a sudden or abrupt alarm, the selected alarm type (e.g., haptic feedback) may be changed among the above-mentioned options and / or other types of alarms.

[0015]

[0037] In some examples, the exemplary controller disclosed herein compiles the output from wearable sensors and transmits the data to a central processing system located remotely from the controller and / or the user. In some of these examples, the exemplary central processing system aggregates the data received from the controller and compares this data to the user's baseline threshold. If the exemplary central processing system determines that the data from the wearable sensors exceeds the user's baseline threshold, it instructs the controller to activate an exemplary alarm (e.g., by sending a warning signal to the controller). The exemplary ergonomic enhancement systems disclosed herein use a power source to provide power to the controller and / or the wearable device. In some examples, the exemplary power source may include a battery. In some examples, the exemplary power source may include smart fabric and / or other electricity-generating devices. As used in this book, the term “smart cloths” may include any fabric or device that generates energy for powering one or more wearable devices and / or controllers, including: kinetic energy-generating fabrics; fabrics containing integrated circuits that can generate electricity from sweat and / or friction (e.g., exercise); frictional forms of human bioenergy; and fabrics or devices that generate energy for powering one or more wearable devices and / or controllers (e.g., fabric piezoelectric nanogenerators that capture human mechanical motion and convert it into energy).

[0016]

[0038] The exemplary ergonomic enhancement systems disclosed herein may track the movement of the upper body (e.g., shoulders, elbows, wrists / hands, forearms, lower back, etc.) and / or the movement of the lower body (e.g., hips, knees, feet, etc.). For example, to track leg movement, one or more exemplary wearable sensors (e.g., metamembrane(s)) may be attached (e.g., to the skin or clothing) to the hip joint, knee joint, ankle joint, lower back, ankle joint, etc. In some examples, the ergonomic enhancement systems disclosed herein may track the movement of any limb or part of the body (e.g., neck, lower back, upper back, etc.) to determine the load and / or strain the body experiences when a user performs a physical task and / or activity.

[0017]

[0039] Figure 1 shows an exemplary ergonomics enhancement system 100 as disclosed in this book. The illustrated example ergonomics enhancement system 100 can detect strain and / or load on the body when performing a particular work task, including repetitive physical tasks. The illustrated example ergonomics enhancement system 100 tracks and / or detects the movement of limbs 102 (e.g., arms 102a) and / or joints of limbs 102 (e.g., joint angles, shoulder joint 128, wrist joint 130, elbow joint 132) relative to body 106 (e.g., torso of the body) to detect strain and / or load on the body (or, e.g., joints of the body).

[0018]

[0040] The illustrated example ergonomics enhancement system 100 includes an exemplary controller 108, an exemplary limb sensor 110, an exemplary load sensor 112, an exemplary position sensor 114, an exemplary warning device 116, and an exemplary power device 118. The limb sensor 110, load sensor 112, position sensor 114, and warning device 116 are communicably connected to the controller 108, for example, via a bus, wired connection, wireless communication protocol, Bluetooth, and / or any other preferred communication protocol(s).

[0019]

[0041] The illustrated example ergonomics enhancement system 100 uses a limb sensor 110 (e.g., a tracking system or upper body sensor) to track and / or detect the movement of a limb 102 and / or joint. The limb sensor 110 in Figure 1 is a tracking system that may be connected to (e.g., directly attached) a limb 102 and / or joint of a body 106 and / or attached to the clothing of a user 106a in order to acquire data associated with the movement of a limb 102 and / or joint as the user performs one or more physical tasks (e.g., physical tasks involving repetitive movements). The ergonomics enhancement system 100 includes a limb sensor 110 (also referred to as a metamembrane system or sensor) connected to a limb 102 of a body 106, which generates a first output used to determine the position of the limb 102 relative to the body 106 (e.g., angular position and / or rotational position) in response to the movement of the limb 102 relative to the body 106. In the illustrated example, the limb sensor 110 is an upper body sensor system 111a attached to the arm 102a of the body 106. However, in other examples, the limb sensor 110 may be connected to the legs, shoulder joint 128, wrist joint 130, elbow joint 132, knee joint, hip joint, lower back, and / or any other part of the body 106. For example, the limb sensor 110 can be connected to or attached to the arm 102a, legs, waist, knee, neck, lower back, upper back, and / or any combination thereof to track the movement of one or more limbs and / or joints of the body 106a while the user 106a is performing physical activity. In some examples, multiple limb sensors 110 (e.g., tracking systems and upper body sensors) may be used to detect the movement of multiple limbs or joints of the body 106 while the user 106a is performing physical activity.

[0020]

[0042] The illustrated example ergonomics improvement system 100 includes a load sensor 112 to detect and / or measure the load on a body 106. The load sensor 112 generates a second output representing the load supported by the body 106. The load sensor 112 in Figure 1 may be a load cell, pressure sensor, pressure pad, and / or any other sensor(s) for measuring the load and / or weight of the body 106.

[0021]

[0043] The ergonomics enhancement system 100 in Figure 1 uses a position sensor 114 to detect and / or otherwise determine the foot position (e.g., foot placement) of a user 106a performing a physical task. The position sensor 114 generates a third output representing the position of the body's right foot relative to the position of the body's left foot. The position sensor 114 in Figure 1 can detect and / or otherwise determine whether the user is standing in a stable or supportive position (e.g., with one foot separated in front of the other) or in an unstable or unsupportive position (e.g., the user 106a is standing with both feet separated but the left and right feet substantially in a line) while performing a physical task(s). In some examples, the ergonomics enhancement system 100 in Figure 1 can determine whether the user's foot position is stable or optimal for supporting a detected load (e.g., an object 119 such as a box) by determining the position of each of the user 106a's feet using the position sensor 114. The load sensor 112 and position sensor 114 in the illustrated example provide the lower body sensor system 111b of the ergonomics improvement system 100.

[0022]

[0044] The ergonomics enhancement system 100 includes a controller 108 to determine the load and / or strain experienced by limbs 102 (e.g., human limbs), joints, and / or body 106 (e.g., upper back and lower back) during a physical task. The controller 108 in Figure 1 is configured to determine, based on one or more limb sensor outputs 120, load sensor outputs 122, and / or position sensor outputs 124 received by the controller 108, whether one or more physical tasks or activities performed by user 106a are being performed with undesirable or inappropriate movements.

[0023]

[0045] The illustrated example ergonomics enhancement system 100 uses a warning device 116 to alert user 106a if the controller 108 determines that an inappropriate or undesirable movement (e.g., non-ergonomic movement) has been detected by user 106a. The controller 108 controls the operation of the warning device 116 (e.g., via a warning signal 126) based on data provided to the controller 108 by limb sensors 110, load sensors 112, and / or position sensors 114. The illustrated example warning device 116 may include, but is not limited to, light, audible alarms, tactile feedback, and / or any other warning(s). The warning device 116 may be attached to the controller 108 (for example, the housing of the controller 108), may be attached to the user 106a's clothing, may be attached to the body 106, may be attached to or integrated with the footwear worn by the user 106a, and / or may be attached to a work hat, gloves, and / or any other tool that the user 106a may use.

[0024]

[0046] Alternatively, in some examples, the controller 108 in Figure 1 may be configured to receive one or more limb sensor outputs 120, load sensor outputs 122, and / or position sensor outputs 124, and to transmit or communicate this data (e.g., via a transmitter) to a remote location (e.g., a remote server, a central processing computer, a control room, etc.). The remote computer may process the data provided by the limb sensors 110, load sensors 112, and / or position sensors 114 to determine whether this data represents user activity that has exceeded an activity threshold. If the remote computer determines that the activity has exceeded the threshold, it may then communicate (e.g., transmit) a command to the controller 108 to activate the warning device 116.

[0025]

[0047] The exemplary ergonomics enhancement system 100 disclosed in this document uses a power device 118 (e.g., a power supply) to provide power to a controller 108 and / or a wearable device or sensor. In Figure 1, the power device 118 provides power to the controller 108, limb sensor 110, load sensor 112, position sensor 114, and / or warning device 116. In some examples, the power device 118 provides power only to the controller 108 and / or warning device 116. For example, the controller 108, power device 118, limb sensor 110, load sensor 112, position sensor 114, and warning device 116 may be electrically connected via one or more electrical wires. In some examples, the limb sensor 110, load sensor 112, and position sensor 114 are powered separately from the power device 118 and / or controller 108 by a dedicated power device (e.g., a battery). In some examples, the limb sensor 110, load sensor 112, and / or position sensor 114 are indirectly powered by a power device 118 through a connection(s) with the controller 108. For example, the power device 118 (e.g., a battery) may be electrically connected to the limb sensor 110, load sensor 112, position sensor 114, controller 108, and / or warning device 116 (to provide power). In some examples, the limb sensor 110, load sensor 112, and position sensor 114 have their own batteries and do not require power from the power device 118.

[0026]

[0048] In the illustrated example, the power device 118 is a battery. In some examples, the power device 118 may include smart cloth and / or other devices that generate electricity. As used in this book, the term “smartcloths” may include kinetic energy generating fabrics, fabrics containing integrated circuits that can generate electricity from sweat and / or friction, frictional forms of human bioenergy, and / or other fabrics or devices that generate energy to power the ergonomics enhancement system 100 (e.g., one or more of the limb sensors 110, load sensors 112, position sensors 114, warning devices 116, and / or controllers 108).

[0027]

[0049] Figure 2A is an enlarged perspective view of a limb sensor 110 (e.g., upper body sensor system 111a) of the exemplary ergonomics enhancement system 100 of Figure 1. The limb sensor 110 in the illustrated example is a wearable membrane connected to (e.g., attached to) an arm 102a (or limb) of a body 106. In the illustrated example, the limb sensor 110 includes a plurality of membrane sensors 200 that generate a first output to track the movement of a limb 102 or arm 102a.

[0028]

[0050] The membrane sensor 200 in the example shown in Figure 2A includes a first membrane sensor 214 (e.g., a first membrane assembly), a second membrane sensor 216 (e.g., a second membrane assembly), and a third membrane sensor 218 (e.g., a third membrane assembly). In the example shown in Figure 2A, the first membrane sensor 214 (e.g., a shoulder membrane sensor system) is connected near or proximal to the shoulder 208, the second membrane sensor 216 (e.g., an cubital membrane sensor) is connected near or proximal to the elbow 206, and the third membrane sensor 218 (e.g., a hand membrane sensor) is connected near or proximal to the wrist 202.

[0029]

[0051] Each of the membrane sensors 200 detects the movement of user 106a and acquires (e.g., measures or calculates) movement data. For example, the limb sensor 110 in Figure 2 includes a first membrane sensor 214 positioned proximal to the shoulder 208 to generate a first output of a plurality of first outputs (e.g., limb sensor outputs 120) that can be used to detect the position of the shoulder 208 relative to the body 106 in response to the movement of the shoulder 208. For example, the limb sensor 110 in Figure 2 includes a second membrane sensor 216 positioned proximal to the elbow 206 to generate a first output of a plurality of second outputs (e.g., limb sensor outputs 120) that can be used to detect the position of the elbow 206 relative to the body 106 in response to the movement of the elbow 206. For example, the limb sensor 110 in Figure 2A includes a third membrane sensor 218 positioned proximal to the hand to generate a first output among a plurality of third outputs (e.g., limb sensor outputs 120) that can be used to detect the position of the hand / wrist 204 relative to the body 106 in response to the movement of the hand / wrist 204.

[0030]

[0052] Although the limb sensor 110 in Figure 2A includes multiple membrane sensors 200, in some examples the limb sensor 110 may include only one sensor assembly (e.g., a first membrane sensor 214), include two membrane sensors, include more than three membrane sensors, and / or any other number of membrane sensors 200.

[0031]

[0053] In some examples, the membrane sensor 200 may be mounted on a cloth, fabric, or other material or garment that the user 106a may wear. In addition, each of the membrane sensors 200 in the illustrated examples may be formed as a pad or patch that is attached to the limbs 102 and / or clothing of the user 106a. For example, the membrane sensor 200 may be attached to a sleeve or wearable device that the user 106a may wear detachably. In some examples, each of the membrane sensors 200 in the illustrated examples may include a release fastener (e.g., hook-and-loop fastener, Velcro® brand fastener, strap, and / or any other release fastener) that can secure the membrane sensor 200 to the limbs 102 of the body 106. In some examples, the membrane sensor 200 may be formed as a single membrane or wearable device that the user 106a may wear. For example, the membrane sensor 200 may be formed as a sleeve or shirt (for example, a shirt entirely composed of membrane sensors), or as other clothing that user 106a can wear. In other words, the exemplary limb sensor 110 may include a shirt formed of a single integrated membrane sensor instead of the first membrane sensor 214, the second membrane sensor 216, and the third membrane sensor 218. In other words, the entire shirt may be a single sensor and / or may include the functionality of a sensor. In some examples, the membrane sensor may be formed as a wearable device, which may include, but is not limited to, a sleeve, shirt, attachable fabric, sleeve, rubber or flexible sleeve, and / or any other wearable device or clothing. The membrane sensor 200 may be permanently attached to the fabric or clothing and / or detachable. In other examples, the membrane sensor 200 may be directly attached to user 106a's arm 102a by removable adhesive or tape.

[0032]

[0054] The ergonomics enhancement system 100 in Figures 1 and 2 includes one or more wires 203 (e.g., electrical wires) to connect the membrane sensor 200, controller 108, warning device 116, and / or power device 118 (e.g., communicatively and / or electrically). For example, the membrane sensor 200, controller, warning device 116, and / or power device are electrically connected in series. For example, a third membrane sensor 218 is electrically connected to a second membrane sensor 216 via a first wire 203a, the second membrane sensor 216 is electrically connected to a first membrane sensor 214 via a second wire 203b, and the first membrane sensor 214 is electrically connected to a warning device 116 via a third wire 203c. Alternatively, in some examples, the membrane sensor 200, controller 108, warning device 116, and / or power device 118 may be communicatively connected via wireless connection, Bluetooth connection, and / or any other communication protocol. In some examples, a power device 118 provides power to the membrane sensors 200. In some examples, each of the membrane sensors 200 is powered by an independent power source (e.g., a battery or smart cloth) and includes one or more antennas for transmitting data (e.g., limb sensor output 120) to the controller 108. In some examples, wire 203 may be omitted.

[0033]

[0055] Figure 2B is an illustrative figure 201 showing exemplary sensor outputs 205-209 of the exemplary membrane sensor 200 (e.g., first membrane sensor 214, second membrane sensor 216, third membrane sensor 218) of Figure 2A. During operation, the first membrane sensor 214 provides a first output among a plurality of first sensor outputs (e.g., limb sensor outputs 120). Specifically, during movement of the shoulder 208, the first membrane sensor 214 generates a first sensor output 205. Based on the position of the elbow 206 (e.g., flexed or straight), the second membrane sensor 216 generates a second sensor output 207. Based on the position of the hand (e.g., flexed or straight at the wrist), and / or the position of the forearm (e.g., a torsional or rotational position relative to the longitudinal axis along the forearm), the third membrane sensor 218 of the illustrated example generates a third sensor output 209.

[0034]

[0056] Each example of sensor output 205-209 represents the movement of arm 102a relative to its initial position (for example, with the palm touching body 106 and arm 102a positioned in contact with the side of body 106). Exemplary sensor outputs 205-209 represent, and / or can be used to detect, the amount of strain applied to arm 102a during movement, such as when shoulder 208 rotates relative to body 106, elbow 206 flexes at the elbow joint, hand flexes at wrist 202, arm 102a rotates relative to shoulder 208, forearm twists relative to elbow and / or shoulder, and / or arm 102a is in any other position relative to body 106. The other positions may include a variety of positions (e.g., arm 102a is externally rotated, arm 102a is raised above the user's head, arm 102a is rotated in a circle, etc.). Outputs 205-209 may be voltage signals, current signals, and / or any other type of signal.

[0035]

[0057] Figures 3A to 3E show exemplary membrane sensors 300 on which the membrane sensors 200 of the exemplary ergonomics enhancement system 100 of Figures 1 and 2 may be mounted. The illustrated example membrane sensor 300 includes a membrane 302 (e.g., a membrane layer) and a sensor 304 (e.g., a sensor layer). Figure 3A is a side view of the exemplary membrane sensor 300. Figure 3B is a top view of an exemplary membrane 302, and Figure 3C is a magnified view of the exemplary membrane 302 in Figure 3B. Figure 3D is a top view of an exemplary sensor 304, and Figure 3E is a magnified view of the exemplary sensor 304 in Figure 3D. For example, the illustrated example membrane sensor 300 may be equipped with the first membrane sensor 214, the second membrane sensor 216, and / or the third membrane sensor 218 of Figure 2A. The membrane sensors 300 of Figures 3A to 3E may be formed or molded in the same way as the first membrane sensor 214, the second membrane sensor 216, and the third membrane sensor 218, and / or may have any other arbitrary shape (e.g., a bracelet or belt) so as to be attached to (and / around) a part of the body 106. In addition, the membrane sensor 300 in the illustrated example is flexible and can adapt to (e.g., bend along and wrap around) parts of the body 106 (for example, the shoulder 208, elbow 206, and wrist 202 in Figure 2A).

[0036]

[0058] Referring to Figures 3A to 3E, the illustrated example membrane 302 is connected to the sensor 304 by an adhesive 306 (e.g., an adhesive layer 306). In the illustrated example, the adhesive 306 is positioned between the membrane 302 and the sensor 304. The adhesive 306 may include, but is not limited to, plastics, tapes, adhesives, pastes, and / or any other type of adhesive. The illustrated membrane 302 is a hexagonal metamembrane. For example, the membrane 302 in Figure 3B includes a first frame 308. To improve or increase the flexibility of the membrane sensor 300, the first frame 308 includes a plurality of first openings or notches 310. As a result, the frame 308 includes a plurality of flexible legs 312 (e.g., strips or frame portions) formed by the first notches 310. The first frame 308 defines a first pattern 314 (e.g., an authentic hexagonal pattern) (e.g., by first leg portions 312 and / or first notches 310). In detail, the first pattern 314 is an authentic or hexagonal pattern. The membrane 302 may be any material(s) that can bend according to or conform to a part of the body 106, such as rubber, plastic, aluminum, copper, and / or other materials.

[0037]

[0059] Referring to Figure 3D, sensor 304 is an electrical sensor (e.g., a strain sensor) that generates an electrical output based on the deflection position of sensor 304. For example, sensor 304 in Figures 3A to 3E may be a strain sensor, piezoelectric sensor, flex circuit, and / or any other flexible sensor that provides and / or generates an output signal (e.g., limb sensor output 120) when it deflects, bends, and / or moves otherwise relative to its initial position. For example, an electrical signal output by the sensor 304 can be communicated to the controller 108 via the wire 203 (Figure 2A).

[0038]

[0060] The sensor 304 in the illustrated example includes a second frame 318. To improve or increase the flexibility and / or stretchability of the membrane sensor 300, the second frame 318 includes a plurality of second openings or notches 320. As a result, the second frame 318 includes a plurality of flexible second legs 322 (e.g., strips or frame portions) formed by the second notches 320. The second frame 318 defines a second pattern 324 (e.g., an authentic hexagonal pattern) (e.g., by the second legs 322 and / or the second notches 320). In detail, the second pattern 324 is authentic. In the illustrated example, the first pattern 314 of the membrane 302 complements the second pattern 324 (e.g., is identical to the second pattern 324). For example, Figures 3C and 3E are enlarged views of the membrane 302 in Figure 3B and the sensor 304 in Figure 3D, respectively. Referring to Figures 3C and 3E, each of the first pattern 314 and the second pattern 324 contains substantially similar (e.g., identical) dimensional characteristics. As used in this text, "substantially similar (identical) dimensional characteristics" means that the dimensions of the film 302 and the dimensions of the sensor 304 are identical or within a specific manufacturing tolerance range (e.g., approximately 0.5 percent to 10 percent). The first pattern 314 and the second pattern 324 are a plurality of interconnected triangular portions or sections 326, each having a length dimension L as illustrated in Figures 3C and 3E. a Height dimension H a angle α, thickness W a , and radius r. For example, height dimension H a is the length of the base 328a of the triangular section 326a. The symbol α represents the angle of the side legs 328b and 328c of the triangular section 326a relative to the horizontal. Dimension L ais the distance between the tip 328d of triangular section 326a and the base 328a of triangular section 326a. The tip 328d is defined on the opposite side of the base 328a by the respective ends of the legs 328b and 328c. The respective ends of the legs 328b and 328c proximal to the tip 328d are not connected (e.g., disconnected), and a gap 329 is formed between them. Radius r is the radius of the corner of triangular section 326. Dimension W a is the width of the legs 312, 322 of the first pattern and the second pattern 314, 324, respectively. The dotted lines in Figures 3C and 3E are part of the dimension lines and do not form parts of the first pattern 314 and the second pattern 324. In addition, the first notch 310 extends through (e.g., penetrating) the metafilm thickness 330 of the film 302 (Figure 3A), and the second notch 320 extends through (e.g., penetrating) the sensor device thickness 332 of the sensor 304 (e.g., Figure 3A). However, in some examples, the first notch 310 and / or the second notch 320 may be formed as recessed cavities that do not extend through (e.g., penetrating) the metafilm thickness 330 and the sensor device thickness 332 of the film 302 and / or the sensor 304, respectively (or only partially extend through a portion of them). Table 1 below provides exemplary dimensional values ​​that may be used to implement the first pattern 314 and / or the second pattern 316. Such exemplary dimensions are provided as examples, and the membrane sensor 300 is not limited to the parameters, values, and units shown. In other examples, the membrane sensor 300 may be formed with other arbitrary dimensional values. TIFF0007867901000001.tif99170

[0039]

[0061] Figures 4A to 4E show another exemplary membrane sensor 400 disclosed herein that may implement the exemplary ergonomics enhancement system 100 of Figures 1 and 2. The illustrated example membrane sensor 400 includes a membrane 402 (e.g., a membrane layer) and a sensor 404 (e.g., a sensor layer). Figure 4A is a side view of the exemplary membrane sensor 400. Figure 4B is a top view of the exemplary membrane 402, and Figure 4C is a magnified portion of the exemplary membrane 402 in Figure 4B. Figure 4D is a top view of the exemplary sensor 404, and Figure 4E is a magnified portion of the exemplary sensor 404 in Figure 4D. For example, the illustrated example membrane sensor 400 may implement the first membrane sensor 214, the second membrane sensor 216, and / or the third membrane sensor 218 of Figure 2A. The membrane sensors 400 in Figures 4A to 4E may be formed or molded in the same manner as the first membrane sensor 214, the second membrane sensor 216, and the third membrane sensor 218, and / or may have any other arbitrary shape (e.g., a bracelet or belt) so as to be attached to (and / around) a part of the body 106. In addition, the membrane sensors 400 in the illustrated example are flexible and can adapt to (e.g., bend along and wrap around) a part of the body 106 (e.g., the shoulder 208, elbow 206, and wrist 202 in Figure 2A).

[0040]

[0062] Referring to Figures 4A to 4E, the membrane 402 in the illustrated example is connected to the sensor 404 via an adhesive 406 (e.g., an adhesive layer). The adhesive 406 may include plastic, tape, glue, latex strips, and / or any other type of adhesive. In the illustrated example, the adhesive 406 is positioned between the membrane 402 and the sensor 404. The membrane 402 in the illustrated example includes a first frame 408. The first frame 408 in Figures 4B and 4C includes a plurality of first openings or notches 410 that define a first pattern 412 in order to improve or increase the flexibility and / or stretchability of the membrane sensor 400. Specifically, the first pattern 412 in the illustrated example is a paper cutout pattern (e.g., a biaxial paper cutout pattern). The membrane 402 may be rubber, plastic, aluminum, copper, and / or any other material that can bend along or conform to a portion of the body 106.

[0041]

[0063] Referring to Figure 4D, sensor 404 is an electrical sensor (e.g., a strain sensor) that generates an electrical output based on the deflection position of sensor 404. For example, sensor 404 in Figures 4A to 4E may be a strain sensor, piezoelectric sensor, flex circuit, and / or any other flexible sensor that provides and / or generates an output signal (e.g., limb sensor output 120) when it deflects, bends, and / or moves otherwise relative to its initial position. For example, the electrical signal output by sensor 404 may be communicated to controller 108 via wire 203 (Figure 2A).

[0042]

[0064] Sensor 404 includes a second frame 418 having a plurality of second apertures or notches 420 defining a second pattern 422. In detail, the second pattern 422 in the illustrated example is a paper cutout pattern. In other words, the first pattern 412 complements the second pattern 422 (for example, is identical to the second pattern 422). For example, Figures 4C and 4E are enlarged views of the film 402 in Figure 4B and the sensor 404 in Figure 4D, respectively.

[0043]

[0065] Referring to FIGS. 4C and 4E, each of the first pattern 412 and the second pattern 422 includes substantially similar (e.g., identical) dimensional characteristics. As used herein, "substantially similar (identical) dimensional characteristics" means that the dimensions of the film 402 and the sensor 404 are the same or within a certain (e.g., approximately 0.5 percent to 10 percent) manufacturing tolerance range. For example, the first notch 410 of the first pattern 412 has a first set 410a of the first notch 410 positioned in a first orientation and a second set 410b of the first notch 410 positioned in a second orientation different from the first orientation. For example, the first set 410a of the first notch 410 is substantially perpendicular to the second set 410b of the first notch 410. Similarly, for example, the second notch 420 of the second pattern 422 has a first set 420a of the second notch 420 positioned in a first orientation and a second set 420b of the second notch 420 positioned in a second orientation different from the first orientation. For example, the first set 420a of the second notch 420 is substantially perpendicular to the second set 420b of the second notch 420 (e.g., exactly at a right angle or nearly exactly at a right angle (e.g., within 10 degrees from perpendicular)). The first notch 410 and the second notch 420 each have a length H b and a width W b . In addition, each of the first set 410a of the first notch 410 and each of the second set 410b of the first notch 410 are separated by a distance Wc. Similarly, each of the first set 420a of the second notch 420 and each of the second set 420b of the second notch 420 are separated by a distance Wc. The length L a is the distance between each of the first set 410a of the first notch 410 and between each of the first set 420a of the second notch 420. The length L b is the distance between each of the second set 410b of the first notch 410 and between each of the second set 420b of the second notch 420. In the illustrated example, the width W b is equal to the distance Wc. Similarly, the length L a and the length L bThis is equal to W. However, in some cases, the width W b distance Wc and / or length L a and length L b These values ​​may be different. In addition, the first set 410a of the first notch 410 may be inclined at an angle with respect to the second set 410b of the first notch 410, and / or the first set 420a of the second notch 420 may be inclined at an angle with respect to the second set 420b of the second notch 420. In some examples, the first notch 410 and / or the second notch 420 may have other arbitrary preferred patterns. In addition, the first notch 410 extends through (e.g., penetrating) the metathickness 430 of the film 402 (Figure 4A), and the second notch 420 extends through (e.g., penetrating) the sensor device thickness 432 of the sensor 404 (Figure 4A). However, in some examples, the first notch 410 and / or the second notch 420 may be formed as recessed cavities (e.g., grooves, slits, channels, etc.) that do not extend through (e.g., penetrate) the metafilm thickness 430 and sensor device thickness 432 of the film 402 and / or sensor 404, respectively (or partially extend through a portion of them). Table 2 below provides exemplary dimensional values ​​that may be used to implement the first pattern 412 and / or the second pattern 422. Such exemplary dimensions are provided as examples, and the film sensor 400 is not limited to the parameters, values, and units shown. In other examples, the film sensor 400 may be formed with other arbitrary dimensional values. TIFF0007867901000002.tif98170

[0044]

[0066] Figure 5 is a schematic diagram of the exemplary displacement and load distribution of the membrane sensor 500, the exemplary membrane sensors in Figures 3A to 3E, and the exemplary membrane sensors in Figures 4A to 4E. The membrane sensor 500 includes a membrane 502 formed without notches or openings. Figure 5 shows side views of the membrane sensor 500, membrane sensor 400, and membrane sensor 300 (labeled (a), (c), and (e), respectively). Figure 5 also shows top views of the membrane sensors 500, 400, and 300 (labeled (b), (d), and (f), respectively). The membrane sensors 500, 400, and 300 are each shown in a deflected or extended position when the same or identical force is applied to each of them (or when the arm 102a is in a bent position). Figure 5 shows the difference in flexibility between membrane sensors 500, 400, and 300. Membrane sensor 400 can bend 506 units more than membrane sensor 500 (e.g., its flexibility is approximately 10% to 20% greater). Membrane sensor 300 can bend 508 units more than membrane sensor 400 (e.g., its flexibility is approximately 10% to 40% greater than membrane sensor 400 and / or approximately 30% to 75% greater than membrane sensor 500). Load-strain mappings for membrane sensors 500, 400, and 300 are illustrated when they are bent to the positions shown in Figure 5. The strain key 510 indicates the level of strain. Although membrane sensor 500 has the minimum amount of elongation or bending, it can withstand larger loads and / or strains than membrane sensors 400 and 300.

[0045]

[0067] Figures 6 to 6D show other exemplary membrane sensors 600a to 6d disclosed herein that may be used to implement the ergonomic improvement systems of Figures 1 and 2. The membrane sensors 600a to 6d (e.g., strain sensors and flex circuits) may be assembled into various configurations, such as including, for example, a first membrane sensor 600a, a second membrane sensor 600b, a third membrane sensor 600c, and a fourth membrane sensor 600d. For example, the membrane sensors 600a to 600d may implement the exemplary membrane sensor 200 in Figure 2A, the exemplary membrane sensors 300 in Figures 3A to 3E, and / or the membrane sensors 400 in Figures 4A to 4E.

[0046]

[0068] The first membrane sensor 600a includes a membrane 604 (e.g., a wearable membrane), a sensor 608 (e.g., a strain-sensing element), and a first adhesive 606 (e.g., an adhesive layer), and can be connected to or attached to the skin 602 of user 106a (e.g., directly). In the illustrated example, the membrane 604 is attached to the skin 602 of user 106a. The first adhesive 606 is positioned between the membrane 604 and the sensor 608, connecting or adhering the membrane 604 and the sensor 608. When the membrane 604 is connected to body 106, it comes between the first side of the first adhesive 606 and the skin 602 of user 106a (e.g., on top of the skin 602). The sensor 608 is positioned near or proximal to the second side opposite the first side of the first adhesive 606 (e.g., in direct contact with the second side).

[0047]

[0069] The second membrane sensor 600b includes a sensor 608, a first adhesive 606, a membrane 604, and a second adhesive 612. The second adhesive 612 may be used to connect the membrane 604 to the skin 602 of user 106a (e.g., directly). The membrane 604 is positioned between the first adhesive 606 and the second adhesive 612, and the second adhesive 612, when connected to body 106, is positioned between the membrane 604 and the skin 602. The first adhesive is positioned between the membrane 604 and the sensor 608, connecting the membrane 604 and the sensor 608.

[0048]

[0070] The third membrane sensor 600c includes a membrane 604 positioned between the sensor 608 and the first adhesive 606. For example, the sensor 608 is attached to the membrane 604 and / or integrally formed with the membrane 604. The first adhesive 606 connects or attaches the membrane 604 and the sensor 608 to the clothing 610 worn by the user 106a. When the user 106a puts on the clothing 610, the membrane sensor 600c is held or maintained on the user 106a. When the user 106a puts on the clothing 610 having the membrane sensor 600c, the sensor 608 is positioned proximal to the user 106a's skin 602 (for example, in direct contact with the skin 602). In other words, when the user 106a is wearing the clothing 610, the sensor 608 is inside the clothing 610 or positioned on the inner surface of the clothing 610.

[0049]

[0071] The fourth membrane sensor 600d includes a sensor 608, a first adhesive 606, a membrane 604, a second adhesive 612, and clothing 610. The first adhesive 606 connects or adheres the membrane 604 to the sensor 608. In other words, the first adhesive is positioned between the sensor 608 and the membrane 604. The second adhesive 612 adheres the membrane 604 to the clothing 610. In other words, the second adhesive is positioned between the membrane 604 and the clothing 610. When user 106a puts on clothing 610, clothing 610 is positioned proximal to user 106a's skin 602. In other words, when user 106a is wearing clothing 610, the sensor 608 is exposed or positioned on the outer surface of clothing 610.

[0050]

[0072] Sensor 608 (and sensors 304 in Figures 3A to 3E, and / or sensors 404 in Figures 4A to 4E, etc.) can be various types of sensors (e.g., strain sensors). For example, the sensors 608 in Figures 6A to 6D (and sensors 304 in Figures 3A to 3E, and / or sensors 404 in Figures 4A to 4E, etc.) may include, but are not limited to, load cell sensors, piezoelectric devices or piezoelectric sensors, flexible circuit boards, conductive materials (including carbon nanomaterials (e.g., carbon black [CBs], carbon nanotubes [CNTs], graphene and its derivatives), metallic nanowires (NWs), nanofibers (NFs), and nanoparticles (NPs)), MXene (e.g., Ti3C2Tx), ionic liquids, hybrid microstructures / nanostructures, conductive polymers, and / or other materials or sensors (multiple) that sense strain and / or load, which may generate output signals (e.g., electrical signals or limb sensor outputs 120) when they bend, flex, and / or are otherwise deformed.

[0051]

[0073] The film 604 (and films 302 in Figures 3A to 3E and / or films 402 in Figures 4A to 4E, etc.) may be formed from a variety of materials, including, but not limited to, silicone elastomers (e.g., ecfoex and polydimethylsilowane [PDMS]), rubber, thermoplastic polymers, medical adhesive films, thermoplastic polyurethanes (TPU), polystyrene-based elastomers, PDMS, natural fiber-based materials such as cotton, wool, flax, and / or other flexible materials.

[0052]

[0074] The membrane sensors 200, 300, 400, and 600a-600d may have varying thicknesses in the z-direction (e.g., stacking direction / cross-section). In some examples, the thickness of membranes 302, 402, and / or 604 may be the same as or different from the thickness of sensors 304, 404, and / or 606. The membrane sensors 200, 300, 400, and / or 600a-d, membranes 302, 402, 604, and / or sensors 304, 404, 608 may be formed by molding (e.g., injection molding), additive manufacturing (e.g., 3D printing), lithography, a combination thereof, and / or any other manufacturing process.

[0053]

[0075] Figure 7A shows an exemplary lower body sensor system 700 disclosed herein, which may be used to implement the exemplary ergonomics enhancement system 100 of Figure 1. The illustrated example lower body sensor system 700 implements the load sensor 112 and position sensor 114 of Figure 1. The load sensor 112 includes a load cell 706, and the position sensor 114 includes a light-detection ranging (LiDAR) sensor 704 (e.g., a pressure pad or step-scan sensor). The load cell 706 and LiDAR sensor 704 are incorporated into a shoe 702 worn by the user 106a (e.g., fitted, attached, or embedded). The LiDAR sensor 704 emits pulse waves into the surrounding environment to detect the position of the user's feet. When the user is standing with their feet together, the pulses bounce off the shoe of the opposite foot and return to the sensor. The sensor calculates the distance traveled using the time difference between each pulse returning to the sensor. If one foot is in front of and / or behind the other foot, the pulse wave is projected onto the surrounding environment rather than onto the shoe of the opposite foot, indicating that the user's feet are not together. Therefore, the pulses emitted by the LiDAR sensor 704 can be used to determine whether the user 106a is standing in a stable or supportive position (e.g., with one foot separated from and in front of the other) or in an unstable or unsupportive position (e.g., with both feet separated, but the left foot substantially aligned with the right foot) while performing a physical task.

[0054]

[0076] Figure 7B shows another exemplary lower body sensor system 700 of the exemplary ergonomics enhancement system 100 of Figure 1. The illustrated example lower body sensor system 700 implements the load sensor 112 and position sensor 114 of Figure 1. The load sensor 112 includes a load cell 706, and the position sensor 114 includes a pressure sensor 708 (e.g., a pressure pad or a step scan sensor). The load cell 706 and pressure sensor 708 are placed inside a shoe 702 that a user 106a (Figure 1) may wear (e.g., embedded in the heel of the shoe). The load cell 706 measures the load or weight of user 106a to determine the total weight that user 106a is holding or lifting. The illustrated example pressure sensor 708 may detect and / or determine the foot position (e.g., foot positioning) of user 106a performing a physical task. For example, the pressure sensor 708 can detect and / or otherwise determine whether the user is standing in a stable or supportive position (e.g., with weight evenly distributed between both feet) or in an unstable or unsupportive position (e.g., with all weight concentrated forward on the toes or backward on the heels) while performing a physical task. In some examples, the pressure sensor 708 can be used to determine the user's weight distribution (e.g., whether the weight distribution is concentrated). For example, a shift in user 106a's weight from the center towards user 106a's heels may indicate that user 106a is out of balance and / or at risk of falling or injury. In some cases, the ergonomics enhancement system 100 can determine whether the user's foot position is stable (or, for example, optimal) for supporting the detected load (e.g., object 119 in Figure 1) by determining the position of the arm 102a using the upper body sensor system 111a, determining the position of each of the user's feet using the position sensor 114, and determining the load that the user 106a is supporting using the load sensor 112.

[0055]

[0077] Figures 8A and 8B are schematic diagrams of exemplary third outputs 800 of the exemplary lower body sensor system 700 shown in Figure 7A. Figure 8A shows the first output 801 of a plurality of third outputs 800, and Figure 8B shows the second output 803 of a plurality of third outputs 800. For example, the first output 801 of a plurality of third outputs 800 indicates that user 106a's feet are separated, but the left foot 805 is substantially aligned with the right foot 807. The second output 803 of the third outputs 800 in Figure 8B indicates that user 106a's right foot 807 is separated from and in front of the left foot 805. The pressure sensor 708 generates a Stepscan output or pressure output, as shown in Figures 8A and 8B. The third output 800 of the pressure sensor 708 can detect the pressure distribution on user 106a's feet. For example, the white areas 802 in Figures 8A and 8B indicate low pressure areas, the gray areas 804 in Figures 8A and 8B indicate medium pressure, and the black areas 806 in Figures 8A and 8B indicate high pressure. In Figure 8A, the user's right foot 807 experiences greater pressure than the left foot 805, which has more white areas 802, as indicated by the larger gray areas 804 and black areas 806. Figure 8B shows that the weight of user 106a is concentrated on the heel of the right foot 807 and the ball of the foot or the central area of ​​the left foot 805.

[0056]

[0078] Figure 9 is a block diagram of an exemplary controller 108 of the exemplary ergonomics improvement system 100 of Figure 1. The controller 108 includes a sensor manager 902, a data monitor 904, a warning device manager 906, and a calibrator 908. The sensor manager 902, data monitor 904, warning device manager 906, and calibrator 908 are communicated together via a bus 910.

[0057]

[0079] The sensor manager 902 receives inputs from the limb sensor 110, the load sensor 112, and / or the position sensor 114. For example, the sensor manager 902 receives the limb sensor output 120, the load sensor output 122, and / or the position sensor output 124. For example, the sensor manager 902 receives outputs 205-209, the output from the load cell 706, and the output from the pressure sensor 708 and / or the LiDAR sensor 704. The sensor manager 902 receives the outputs as current, voltage, etc. In some examples, the sensor manager 902 may adjust the signals to be suitable for processing by the data monitor 904. In some examples, the sensor manager 902 converts the inputs to binary values ​​(e.g., on / off), digital values, and / or analog values. For example, the sensor manager 902 may convert the signal from the position sensor 114 to a binary value.

[0058]

[0080] For example, the sensor manager 902 may provide a binary value of "1" to each of outputs 205-209 depending on whether the output signal exceeds a threshold (e.g., a certain current value) associated with each of the membrane sensors 214, 216, and 218, and may provide a binary value of "0" to each of outputs 205-209 of the membrane sensors 214, 216, and 218 depending on whether the output signal exceeds a threshold (e.g., a certain current value) associated with each of the membrane sensors 214, 216, and 218. For example, the sensor manager 902 may provide a binary value of "1" if the position sensor 114 provides a signal indicating that user 106a is standing in a stable foot position, and may provide a binary value of "0" if the position sensor 114 provides a signal indicating that user 106a is standing in an unstable foot position. In some cases, the sensor manager 902 may provide a binary value of "1" when the load sensor 112 provides a signal indicating a weight above a threshold (e.g., 50 pounds), and may provide a binary value of "0" when the load sensor 112 provides a signal indicating a weight below this threshold.

[0059]

[0081] The data monitor 904 stores and processes signals(s) from the sensor manager 902. The data monitor 904 may compare signals(s) from the sensor manager 902 to thresholds. In some cases, thresholds may be retrieved, read, or otherwise accessed by the data monitor 904 from memory. For example, to determine whether user 106a is performing a non-ergonomic or inappropriate activity based on data provided by limb sensor output 120, load sensor output 122, and / or position sensor output 124, the data monitor 904 may compare signals from the sensor manager 902 to a table via a comparator. For example, the data monitor 904 may compare signals from the sensor manager 902 to thresholds stored in lookup tables associated with each threshold for each of the limb sensor output 120, load sensor output 122, and / or position sensor output 124. For example, the data monitor 904 may compare the determined position of the limb 102 with a position threshold associated with the measured load supported by user 106a, provided by the load sensor 112, and the determined position of the right foot 807 relative to the left foot 805. The data monitor 904 may communicate a warning activation signal to the warning device manager 906 if it determines that the determined position of the limb 102 exceeds a position threshold (e.g., from a lookup table) associated with, or corresponding to, the measured load from the load sensor 112 and / or the detected position of the right foot 807 relative to the left foot 805. For example, outputs 205-209 in Figure 13 may indicate non-ergonomic or inappropriate movement or position of the limb 102 if the load supported by user 106a exceeds a threshold load and / or if user 106a's foot position is an unstable foot position (e.g., the foot position shown in Figure 8A). In some cases, outputs 205-209 in Figure 13 may indicate ergonomic or appropriate movement or position of limb 102 when the load supported by user 106a does not exceed a threshold load, and / or when user 106a's foot position is a stable foot position (e.g., the foot position shown in Figure 8B).

[0060]

[0082] For example, the lookup table may have multiple first thresholds corresponding to the outputs from membrane sensors 214, 216, and 218. Based on the comparison of the outputs from membrane sensors 214, 216, and 218 with the corresponding thresholds stored in the lookup table for each of the membrane sensors 214, 216, and 218, the weight provided by the load sensor 112, and the foot position provided by the position sensor 114, the data monitor 904 determines whether the activity performed by user 106a (e.g., based on limb movement or position) is ergonomically appropriate or ergonomically inappropriate. If one or more signals or combinations of signals from the sensor manager 902 exceed one or more thresholds or combinations of thresholds when compared with the limb sensor output 120, the load sensor output 122, and the position sensor output 124, the warning device manager 906 triggers a warning signal 126 to trigger an alarm (e.g., indicating non-ergonomic activity or movement).

[0061]

[0083] If the signal from the sensor manager 902 exceeds a threshold, the warning device manager 906 may receive a signal from the data monitor 904. The warning device manager 906 may transmit a warning signal 126 and / or an alarm. The exemplary alarms disclosed herein include, but are not limited to, visual alarms (e.g., light), auditory alarms (e.g., speakers), haptic feedback, combinations thereof, and / or any other alarm(s).

[0062]

[0084] The calibrator 908 commands the user to perform actions to complete the calibration, as shown in Figure 12. The calibrator 908 can further store motion data from various positions obtained during calibration and process such motion data to be used as thresholds for the data monitor 904. The calibrator 908 sets zero or reference values ​​for the limb sensor 110, load sensor 112, and position sensor 114.

[0063]

[0085] Alternatively, the controller 108 in the illustrated example may be configured to communicate sensor outputs from the upper body sensor system 111a and / or the lower body sensor system 111b (e.g., sensor outputs 120, 122, 124, 205-209, 800, etc.) to a remote electronic device (e.g., a server, computer, control room, portable device, mobile phone, and / or other computing device that is communicably connected to the controller 108 of the ergonomics enhancement system 100). For example, the controller 108 and / or the sensor manager 902 may transmit or communicate one or more outputs provided by sensors (e.g., limb sensor 110, load sensor 112, position sensor 114, membrane sensors 214, 216, 218, load cell 706, pressure sensor 708, LiDAR sensor 704, and / or any other sensors). A remote electronic device may be configured to model the motion of user 106a (for example, user 106a's arm 102a) based on data provided by controller 108. The remote electronic device may be configured to detect whether the model represents motion that may be ergonomic or acceptable, or motion that may be non-ergonomic or unacceptable. If the remote electronic device determines that user 106a's motion is acceptable, it does not communicate with controller 108. If the remote electronic device determines that user 106a's motion is unacceptable, it communicates a command to controller 108 to the warning device manager 906 to activate an alarm signal 126 in order to activate the warning device 116.

[0064]

[0086] Figure 9 shows an exemplary implementation of the controller 108 of Figure 1, but one or more of the elements, processes, and / or devices shown in Figure 9 may be combined, separated, reconfigured, omitted, eliminated, and / or implemented in any other way. Furthermore, the sensor manager 902, data monitor 904, warning device manager 906, and calibrator 908, and / or, more broadly, the exemplary controller of Figure 1, may be implemented by hardware, software, firmware, and / or any combination of hardware, software, and / or firmware. Therefore, for example, the sensor manager 902, the data monitor 904, the warning device manager 906, and the calibrator 908, and / or, more broadly, the exemplary controller 108 in Figure 1, can be implemented by one or more analog or digital circuits, logic circuits, programmable processors, programmable controllers, graphics processing units (GPUs)(or more), digital signal processors (DSPs)(or more), application-specific integrated circuits (ASICs)(or more), programmable logic devices (PLDs)(or more), and / or field-programmable logic devices (FPLDs)(or more). If any of the claims of the apparatus or system of this patent application are interpreted as covering purely software and / or firmware implementations, then at least one of the sensor manager 902, data monitor 904, warning device manager 906, and calibrator 908, and / or, more broadly, the exemplary controller 108 in Figure 1, is expressly defined herein as including a non-transient, computer-readable storage device or storage disk (e.g., memory, digital versatile disc (DVD), compact disc (CD), Blu-ray disc, etc.) containing software and / or firmware.Furthermore, the exemplary controller 108 in Figure 1 may include, in addition to or instead of, those shown in Figure 9, one or more elements, processes, and / or devices, and / or two or more of any or all of the elements, processes, and devices shown. As used herein, the expression “in communication,” including its variations, encompasses direct communication and / or indirect communication through one or more intermediate components, and does not require direct and physical (e.g., wired) communication and / or constant communication, but rather includes selective communication at periodic intervals, scheduled intervals, aperiodic intervals, and / or one-time events.

[0065]

[0087] Figures 10 and 11 show flowcharts representing exemplary hardware logic, machine-readable instructions, a hardware-implemented state machine, and / or any combination thereof for implementing the ergonomics enhancement system 100 of Figure 1. The machine-readable instructions may be one or more executable programs, or parts(s) of executable programs, executed by a computer processor (e.g., the processor 1312 shown in the exemplary processor platform 1300 described below in association with Figure 1). The programs may be implemented as software stored on a non-transient computer-readable storage medium associated with the processor 1312 (e.g., a CD-ROM, floppy disk, hard drive, DVD, Blu-ray disk, or memory), but alternatively, all and / or parts of the program may be executed by a device other than the processor 1312, and / or implemented in firmware or dedicated hardware. Furthermore, while the exemplary programs are described with reference to the flowcharts shown in Figures 10 and 11, numerous other methods for implementing the exemplary ergonomics enhancement system 100 may be used alternatively. For example, the order in which blocks are executed may be changed, and / or parts of the described blocks may be modified, erased, or combined. Additionally or alternatively, some or all of the blocks may be implemented by one or more hardware circuits (e.g., discrete and / or integrated analog and / or digital networks, FPGAs, ASICs, comparators, operational amplifiers (op-amps), logic circuits, etc.) that are constructed to perform the corresponding operations without executing software or firmware.

[0066]

[0088] The machine-readable instructions described in this book may be stored in one or more of the following formats: compressed, encoded, fragmented, compiled, executable, and packaged. The machine-readable instructions described in this book may be stored as data (e.g., instruction parts, code, coded representations, etc.) that can be used to create, construct, and / or generate machine-executable instructions. For example, machine-readable instructions may be fragmented and stored in one or more storage devices and / or computing devices (e.g., servers). Machine-readable instructions may require one or more of the following processes to become directly readable, interpretable, and / or executable by computing devices and / or other machines: installation, modification, adaptation, updating, synthesis, completion, configuration, decoding, unpacking, decompression, distribution, reallocation, and compiling. For example, machine-readable instructions may be stored as multiple parts, each individually compressed, encoded, and stored in separate computing devices. These multiple parts, when decoded, decompressed, and combined, form a set of executable instructions that implement a program (such as the one described in this book).

[0067]

[0089] In another example, machine-readable instructions may be stored in a state readable by a computer, but require additional libraries (e.g., dynamic link libraries (DLLs)), software development kits (SDKs), application programming interfaces (APIs), etc., to be executed on a particular computing device or other device. In yet another example, machine-readable instructions may need to be configured (e.g., storing configurations, entering data, recording network addresses, etc.) before the machine-readable instructions and / or corresponding programs(s) can be executed in whole or in part. Thus, the disclosed machine-readable instructions and / or corresponding programs(s) are intended to encompass such machine-readable instructions and / or programs(s), regardless of the specific form or state of the machine-readable instructions and / or programs(s) when stored, or at rest or transmission.

[0068]

[0090] The machine-readable instructions described in this book can be expressed in any past, present, or future instructional language, scripting language, programming language, etc. For example, machine-readable instructions can be expressed in C, C++, Java. (Registered trademark) C#, Perl, Python, JavaScript (Registered trademark) ), Hypertext Markup Language (HTML), Structured Query Language (SQL), Swift (Registered trademark) It can be expressed using any language, such as the above.

[0069]

[0091] As described above, the exemplary processes in Figures 10 and 11 may be implemented using executable instructions (e.g., computer-readable instructions and / or machine-readable instructions) stored on non-transitory computer-readable medium and / or machine-readable medium (e.g., hard disk drives, flash memory, read-only memory, compact disks, digital multipurpose disks, caches, random access memory, and / or other storage devices or storage disks that store information over any period of time (e.g., long-term, permanently, short-term, for temporary buffering, and / or for information caching)). As used herein, the term “non-transitory computer-readable medium” is explicitly defined to include any type of computer-readable storage device and / or storage disk, but not including propagating signals and transmission media.

[0070]

[0092] In this text, “Including” and “comprising” (and all their conjugations and tenses) are used as open-ended terms. Therefore, in the claims, whenever any form of “including” or “comprising” (e.g., comprises, includes, comprising, including, having, etc.) is used as a preamble or in any type of claim description, it should be understood that additional elements or terms may exist without falling outside the scope of the corresponding claims or description. When used in this text, the word “at least” is used, for example, as a transitional term in the preamble of the claims, but it is open-ended, just as the words “including” and “comprising” are open-ended. The word "and / or" refers to any combination or subset of A, B, and C (for example, (1) A only, (2) B only, (3) C only, (4) A and B, (5) A and C, (6) B and C, and (7) A, B, and C) when used in the form of A, B, and C. The expression "at least one of A and B" is intended to refer to an implement that includes any of (1) at least one A, (2) at least one B, and (3) at least one A and at least one B when used in this text in the context of describing a structure, component, item, object, and / or thing. Similarly, when the expression "at least one of A or B" is used in this text in a context describing a structure, component, item, object, and / or thing, it is intended to refer to an implement that includes (1) at least one A, (2) at least one B, and (3) at least one A and at least one B.When used in this text in a context describing the implementation or execution of a process, instruction, activity, and / or step, the expression "at least one of A and B" means (1) at least one A, (2) at least one B, and (3) at least one A. It is intended to refer to an execution that includes either (1) at least one A, (2) at least one B, or (3) at least one A and at least one B.

[0071]

[0093] In this text, singular references (e.g., "a / an," "first," "second," etc.) do not exclude the possibility of plural entities. In this text, the term "a single entity" refers to one or more such entities. The terms "a single," "one or more," and "at least one" are interchangeable in this text. Furthermore, multiple means, elements, or method acts, even if listed individually, can be implemented, for example, by a single unit or processor. In addition, individual features may be included in various examples or claims, but such features can also be combined, and inclusion in various examples or claims does not imply that the combination of features is unfeasible and / or unprofitable.

[0072]

[0094] Method 1000 in Figure 10 is an exemplary method for implementing the ergonomics improvement system 100 in Figure 1. Method 1000 begins in block 1002 with the sensor manager 902 receiving data collected from the sensor(s). Such sensors(s) may include limb sensors 110, load sensors 112, position sensors 114, membrane sensors 214, 216, 218, load cell 706, pressure sensor 708, LiDAR sensor 704, and / or any other sensors(s).

[0073]

[0095] In block 1004, the data monitor 904 compares data (e.g., one or more signals) from the sensor manager 902 with a threshold. The threshold can be obtained from a lookup table that can be stored in the database or memory of the controller 108.

[0074]

[0096] In block 1006, the data monitor 904 determines whether the threshold has been exceeded in block 1004. If the data monitor 904 determines that the threshold has been exceeded in block 1006, the process proceeds to block 1008. In block 1008, the warning device manager 906 activates a warning signal (e.g., warning signal 126) to activate the alarm and / or warning device 116. If the data monitor 904 determines that the threshold has not been exceeded in block 1006, the process returns to block 1002.

[0075]

[0097] Referring to Figure 11, Method 1100 is an exemplary method for calibrating the upper body sensor system 111a and the lower body sensor system 111b of the exemplary ergonomics enhancement system 100 of Figure 1. For example, calibration is implemented using a calibrator 908. For example, calibration of the exemplary ergonomics enhancement system 100 of Figure 1 may be performed when the system is first turned on and / or at any other time during the use of the system. In some examples, calibration may be automatically configured to be performed at predetermined intervals or in the event of a specific event (for example, when the controller 108 detects an abnormal value output by one or more sensors of the ergonomics enhancement system of Figure 1).

[0076]

[0098] In block 1104, the exemplary ergonomics enhancement system 100 shown in Figure 1 may detect the upper body sensor system 111a (e.g., membrane sensors 214, 216, 218) and the lower body sensor system 111b (e.g., load cell 706, pressure sensor 708, LiDAR sensor 704, etc.) via the sensor manager 902. In block 1106, the exemplary calibrator 908 commands the user 106a to start sensor calibration. Exemplary sensor calibration positions are disclosed herein and illustrated in Figure 12.

[0077]

[0099] In block 1108, the exemplary calibrator 908 records the sensor output(s) associated with various sensor calibrations. For example, the calibrated values ​​of each sensor (e.g., limb sensor 110, load sensor 112, and / or position sensor 114) become zero or reference values.

[0078]

[0100] Figure 12 is an illustrative diagram showing exemplary calibration positions 1200 disclosed herein, which may be used to implement the exemplary method 1100 of Figure 11. Sensor calibration positions may be commanded to user 106a using a user interface which may include, for example, a display, a speaker, a combination thereof, and / or other communication devices mounted on controller 108. Exemplary calibration positions 1200 may be used to calibrate one or more of the membrane sensors 214, 216, and 218 after they have been attached to or connected to user 106a. For example, each of the membrane sensors 214, 216, and 218 may be calibrated using the exemplary calibration position 1200 of Figure 12. For example, calibration position 1200 includes three sets of calibration positions (i.e., position 1, position 2, and position 3) for each of the shoulder 208, elbow 206, and hand / wrist 202. However, the calibration position is not limited to the position shown in Figure 12, and may include one or more other positions not shown in Figure 12.

[0079]

[0101] At shoulder calibration position 1 (1202), user 106a is commanded to move their arm (i.e., arm 102a) to a forward position (for example, the position where it is fully extended in front of user 106a) and then to a backward position (for example, the position where it is fully extended behind user 106a). Controller 108 records the output of sensors (e.g., membrane sensors 214, 216, 218) as arm 102a moves to the forward and backward positions.

[0080]

[0102] At shoulder calibration position 2 (1204), user 106a is commanded to move their arm to an upward position (for example, the highest position above the user's head) and then to a downward position (for example, the highest position along the side of the user's body). Controller 108 records the output of sensors (e.g., membrane sensors 214, 216, 218) as arm 102a moves to the upward and downward positions.

[0081]

[0103] At shoulder calibration position 3 of 1206, user 106a is commanded to extend their arm outward and sideways (for example, in a shape like outstretched wings), and further to rotate / twist the arm in a circular motion between a first rotation position (for example, a twist or rotation in the first rotational direction) and a second rotation position (for example, a twist or rotation in the second rotational direction opposite to the first rotational direction). Controller 108 records the output of sensors (e.g., membrane sensors 214, 216, 218) as the arm 102a moves to the first and second rotational positions.

[0082]

[0104] At elbow calibration position 1 (1208), user 106a is commanded to move their arm laterally and further to a flexed position (e.g., the most flexed position where the hand is proximal to the shoulder 208) and an extended position (e.g., the most extended position). Controller 108 records the outputs of sensors associated with the elbow 206 (e.g., membrane sensors 214, 216, 218) as the arm 102a moves to the flexed and extended positions.

[0083]

[0105] At elbow calibration position 2 (1210), user 106a is instructed to bend their elbow and move the bent elbow to the upper bend position and the lower bend position. Controller 108 records the output of sensors (e.g., membrane sensors 214, 216, 218) as arm 102a moves to the upper bend position and the lower bend position.

[0084]

[0106] At elbow calibration position 3 (1212), user 106a is commanded to rotate the arm between a first rotation position and a second rotation position opposite the first rotation position, with the elbow bent. Controller 108 records the output of sensors (e.g., membrane sensors 214, 216, 218) as the arm 102a moves to the first and second rotation positions with the elbow 206 bent.

[0085]

[0107] At wrist / hand calibration position 1 (1214), user 106a is commanded to move or bend their hand at the wrist to an upward position (e.g., the uppermost position) and then to a downward position (e.g., the lowermost position). Controller 108 records the output of sensors (e.g., membrane sensors 214, 216, 218) as the hand moves to the upward and downward positions.

[0086]

[0108] At wrist / hand calibration position 2 (1216), user 106a is commanded to move their hand laterally at the wrist to a first lateral position (e.g., the rightmost position) and then to a second lateral position (e.g., the leftmost position). Controller 108 records the output of sensors (e.g., membrane sensors 214, 216, 218) as the hand moves to the first and second lateral positions.

[0087]

[0109] At the wrist / hand calibration position 3 (1218), user 106a is commanded to twist his hand laterally at the wrist to a first rotation position (e.g., the position where it has rotated the most in the first rotation direction) and then to a second rotation position (e.g., the position where it has rotated the most in the second rotation direction). Controller 108 records the output of sensors (e.g., membrane sensors 214, 216, 218) as the hand moves to the first and second rotation positions.

[0088]

[0110] Figure 13 is a block diagram of an exemplary processing platform constructed to implement an exemplary controller for the exemplary ergonomic improvement system disclosed herein by executing the instructions in Figures 10 and 11.

[0089]

[0111] Figure 13 is a block diagram of an exemplary processor platform 1300 constructed to execute the instructions in Figures 10 and 11 in order to implement the ergonomics enhancement system 100 of Figure 1. The processor platform 1300 may be, for example, a server, a personal computer, a workstation, a self-learning machine (such as a neural network), a mobile device (such as a mobile phone, smartphone, or tablet such as an iPad®), a headset or other wearable device, or any other type of computing device.

[0090]

[0112] The illustrated example processor platform 1300 includes a processor 1312. The illustrated example processor 1312 is hardware. For example, the processor 1312 may be implemented by one or more integrated circuits, logic circuits, microprocessors, GPUs, DSPs, or controllers from any desired affiliate or manufacturer. The hardware processor may be a semiconductor-based (e.g., silicon-based) device. In this example, the processor implements a sensor manager 902, a data monitor 904, a warning device manager 906, and a calibrator 908.

[0091]

[0113] The illustrated example processor 1312 includes local memory 1313 (such as a cache). The illustrated example processor 1312 communicates with main memory, which includes volatile memory 1314 and non-volatile memory 1316, via bus 1318. The volatile memory 1314 may be implemented by synchronous dynamic random access memory (SDRAM), dynamic random access memory (DRAM), RAMBUS® dynamic random access memory (RDRAM®), and / or any other type of random access memory device. The non-volatile memory 1316 may be implemented by flash memory and / or any other preferred type of memory device. Access to the volatile memory 1314 and non-volatile memory 1316 is controlled by a memory controller.

[0092]

[0114] The illustrated example processor platform 1300 also includes an interface circuit 1320. The interface circuit 1320 can be implemented by any type of interface standard (e.g., Ethernet interface, Universal Serial Bus (USB), Bluetooth® interface, Near Field Communication (NFC) interface, and / or PCI Express interface).

[0093]

[0115] In the illustrated example, one or more input devices 1322 are connected to the interface circuit 1320. The input devices 1322(or more) allow the user to input data and / or commands to the processor 1312. The input devices(or more) may be implemented by, for example, a voice sensor, a microphone, a camera (still or video), a keyboard, buttons, a mouse, a touchscreen, and / or a voice recognition system.

[0094]

[0116] One or more output devices 1324 are also connected to the interface circuit 1320 in the illustrated example. The output devices 1324 may be implemented by, for example, display devices (e.g., light-emitting diodes (LEDs), organic light-emitting diodes (OLEDs), liquid crystal displays (LCDs), cathode-ray tube displays (CRTs), positional switching (IPS) displays, touchscreens, etc.), and / or speakers. Thus, the interface circuit 1320 in the illustrated example typically includes a graphics driver card, a graphics driver chip, and / or a graphics driver processor.

[0095]

[0117] The illustrated example interface circuit 1320 also includes communication devices (transmitters, receivers, transceivers, modems, resident gateways, wireless access points, and / or network interfaces, etc.) to facilitate data exchange with external machines (e.g., any type of computing device) via the network 1326. Communication may be via, for example, an Ethernet connection, a digital subscriber line (DSL) connection, a telephone line connection, a coaxial cable system, a satellite system, a line-of-site wireless system, a mobile phone system, etc.

[0096]

[0118] The illustrated example processor platform 1300 also includes one or more mass storage devices 1328 for storing software and / or data. Examples of such mass storage devices 1328 include floppy disk drives, hard drive disks, compact disk drives, Blu-ray disk drives, independent disk redundant array (RAID) systems, and digital versatile disk (DVD) drives.

[0097]

[0119] The machine-executable instructions 1332 in Figures 10 and 11 may be stored in a mass storage device 1328, volatile memory 1014, non-volatile memory 1316, and / or a removable, non-transient, computer-readable storage medium (such as a CD or DVD).

[0098]

[0120] The aforementioned examples of ergonomic enhancement systems may be wearable devices. Each of the exemplary ergonomic enhancement systems disclosed above has certain features, but it should be understood that it is not necessary for any particular feature of one example to be used only for that example. Instead, any of the features described above and / or shown in the drawings may be combined with any of the other features of the example, in addition to or as a substitute for them. Features of one example are not mutually exclusive with features of another example. Instead, the scope of this disclosure encompasses any combination of any features. For example, the first membrane sensor 214 may be implemented by membrane sensor 300, the second membrane sensor 216 may be implemented by membrane sensor 400, and the third membrane sensor may be implemented by any of membrane sensors 600a to d, and / or any combination thereof.

[0099]

[0121] Furthermore, this disclosure includes examples relating to the following clauses.

[0100] Article 1. A wearable ergonomics enhancement system comprising: a membrane including a first frame, the first frame having a plurality of first notches defining a first pattern; and a sensor connected to the membrane, the second frame having a plurality of second notches defining a second pattern, wherein the first pattern complements the second pattern.

[0101] Article 2. The system described in Clause 1, wherein the first and second patterns are paper cutting patterns.

[0102] Article 3. The system described in Clause 1 or 2, wherein the first and second patterns are authentic patterns.

[0103] Article 4. A system described in any one of clauses 1 to 3, wherein the sensor is a strain sensor.

[0104] Article 5. A system as described in any one of clauses 1 to 4, wherein the strain sensor is a flexible circuit.

[0105] Article 6. A system as described in any one of clauses 1 to 5, wherein the sensor is a piezoelectric sensor.

[0106] Article 7. The system according to any one of Clauses 1 to 6, wherein the membrane is composed of at least one of a paper cutting pattern or an authentic pattern.

[0107] Article 8. The system according to any one of clauses 1 to 7, further comprising an adhesive for connecting a membrane and a sensor.

[0108] Article 9. A first membrane sensor connected to the shoulder of the body, which generates a first output in response to shoulder movement to detect at least one of the position or rotation of the shoulder; a second membrane sensor connected to the elbow of the body, which generates a second output in response to elbow movement to detect at least one of the position or rotation of the elbow; and a third membrane sensor connected to the wrist of the body, which generates a third output in response to hand movement to detect at least one of the position or rotation of the hand. A wearable ergonomics enhancement system equipped with [features / equipment].

[0109] Article 10. The system according to any one of the clauses 1 to 9, wherein each of the first membrane sensor, the second membrane sensor, and the third membrane sensor includes a plurality of apertures that define a pattern.

[0110] Article 11. The system according to any one of the clauses 1 to 10, wherein the pattern is at least one of a paper cutting pattern or an authentic pattern.

[0111] Article 12. The system described in any one of clauses 1 to 11, further including a load sensor for measuring the load on the body.

[0112] Article 13. The system according to any one of clauses 1 to 12, further comprising a position sensor for detecting the position of the body's right foot relative to the body's left foot.

[0113] Article 14. A system according to any one of Clauses 1 to 13, wherein a load sensor and a position sensor are positioned within footwear worn by the user.

[0114] Article 15. Based on the first output of the first membrane sensor, the second output of the second membrane sensor, and the third output of the third membrane sensor, the position of the limb relative to the body is determined; based on the fourth output from the load sensor, the measured load is determined; based on the fifth output of the position, the position of the body's right foot relative to the body's left foot is determined; the determined limb position is compared with a position threshold associated with the measured load and the detected position of the right foot relative to the left foot; and a warning signal is generated when it is determined that the detected position exceeds the position threshold associated with the measured load and the detected position of the right foot relative to the left foot. A system as described in any one of clauses 1 to 14, further comprising a processor that performs the following.

[0115] Article 16. A system as described in any one of clauses 1 to 15, wherein the load sensor includes a load cell.

[0116] Article 17. The system according to any one of the clauses 1 to 16, wherein the position sensor includes at least one of a pressure sensor or a LiDAR sensor.

[0117] Article 18. A method for tracking the movement of a limb of a body, comprising: determining the position of the limb relative to the body based on a first output of a first membrane sensor, a second output of a second membrane sensor, and a third output of a third membrane sensor; determining the position of the limb relative to the body based on a received first, second, or third output; receiving a second output from a load sensor attached to the body; determining the load of the body based on the received second output; receiving a third output from a step scanner attached to the body; determining the position of the foot by detecting the position of the body's left foot relative to the position of the body's right foot based on a third output from a pressure sensor; comparing the determined limb position with position thresholds associated with the determined load and the determined foot position; determining whether the determined position exceeds the position threshold; and generating a warning signal if the determined position exceeds the position threshold.

[0118] Article 19. A system according to any one of Clauses 1 to 18, wherein generating an alarm signal includes generating at least one of an audio signal, a tactile signal, or an optical signal.

[0119] Article 20. A system as described in any one of clauses 1 to 19, further including reading a position threshold from a lookup table. Furthermore, this application includes the following embodiments. ( (Appendix 6) A first wearable sensor (218, 302, 402, 502) connected to the shoulder (208) of the body (106, 106a), comprising a first membrane (218, 302, 402, 502) for generating a first output (120) in response to the movement of the shoulder (208) to detect at least one of the position or rotation of the shoulder (208), A second wearable sensor (216, 302, 402, 502) connected to the elbow (206) of the body (106, 106a), which generates a second output (120) in response to the movement of the elbow (206) to detect at least one of the position or rotation of the elbow (206), A third wearable sensor (212, 302, 402, 502) connected to the wrist (202) of the body (106, 106a), which generates a third output (120) in response to the movement of the hand (202) to detect at least one of the position or rotation of the hand (202), A wearable ergonomics enhancement system (100) equipped with [the following features]. (Aspect 7) The system (100) according to embodiment 6, wherein each of the first wearable sensor (218, 302, 402, 502), the second wearable sensor (216, 302, 402, 502), and the third wearable sensor (212, 302, 402, 502) includes a plurality of apertures defining a pattern (412, 422, 314, 324). (Pattern 8) The system (100) according to embodiment 6, further comprising a load sensor (112) for measuring the load on the body (106, 106a). (Aspect 9) The system (100) according to embodiment 8, further comprising a position sensor (114) for detecting the position of the right foot (807) of the body (106, 106a) relative to the left foot (805) of the body. (Aspect 10) The system (100) according to embodiment 8, wherein a load sensor (112) and a position sensor (114) are positioned within footwear worn by a user (106, 106a). (Aspect 11) It is a processor, Based on the first output (120) of the first wearable sensor (218, 302, 402, 502), the second output (120) of the second wearable sensor (216, 302, 402, 502), and the third output (120) of the third wearable sensor (212, 302, 402, 502), the position of the limb (102) relative to the body (106, 106a) is determined. Based on the fourth output (122) from the load sensor (112), the measured load is determined, Based on the fifth output (124) of the position sensor (114), the position of the body's right foot (807) relative to the body's left foot (805) is determined, The determined position of the limb (102) is compared with the measured load and the position threshold associated with the detected position of the right foot (807) relative to the left foot (805), In response to determining that the detected position exceeds the measured load and the position threshold associated with the detected position of the right foot (807) relative to the left foot (805), a warning signal (126) is generated. The system (100) according to embodiment 10, further comprising a processor that performs the following. (Aspect 12) The system (100) according to embodiment 11, wherein the load sensor (112) includes a load cell (706). (Aspect 13) The system (100) according to embodiment 11, wherein the position sensor (114) includes at least one of a pressure sensor (708) or a LiDAR sensor (704). (Aspect 14) A method for tracking the movement of limbs (102) of the body (106, 106a), Based on the first output (120) of the first wearable sensor (218, 302, 402, 502), the second output (120) of the second wearable sensor (216, 302, 402, 502), and the third output (120) of the third wearable sensor (218, 302, 402, 502), the position of the limb (102) relative to the body (106, 106a) is determined. Based on the received first output (120), second output (120), or third output (120), the position of the limb (102) relative to the body (106, 106a) is determined, The system receives a second output (122) from a load sensor (112) attached to the body (106, 106a), Based on the received second output (122), the load on the body is determined, Receiving a third output (124) from a step scanner (114, 708) attached to the body (106, 106a), The position of the foot is determined by detecting the position of the left foot (805) of the body (106, 106a) relative to the position of the right foot (807) of the body based on the third output from the pressure sensor (708), The determined position of the limb (102) is compared with the determined load and the position threshold associated with the determined foot position, To determine whether the determined position exceeds the position threshold, A method comprising generating a warning signal (126) if the determined position exceeds the position threshold. (Aspect 15) The method according to embodiment 14, further comprising reading the position threshold from a lookup table.

Claims

1. A film (214, 216, 218, 302, 402, 502) including a first frame (308, 408) having a plurality of first notches (310, 410) defining a first pattern (314, 412), Sensors (110, 214, 216, 218, 300, 400, 500, 600a to d) connected to the film, including a second frame (308, 318, 408, 418) having a plurality of second notches (320, 420) defining a second pattern (324, 422), and a sensor (110, 214, 216, 218, 300, 304, 400, 404, 500), A wearable ergonomics improvement system (100) comprising the first pattern (314, 412) having the same dimensions as the second pattern (314, 422) within the manufacturing tolerance range.

2. The system (100) according to claim 1, wherein the first pattern (412) and the second pattern (422) are paper cutting patterns (412, 422), or the first pattern (314) and the second pattern (324) are authentic patterns (314, 324).

3. The system (100) according to claim 1, wherein the sensors (110, 300, 304, 400, 404, 500, 600a to d) are at least one of a strain sensor (608) and / or a piezoelectric sensor (608).

4. The system (100) according to claim 1, wherein the film (214, 216, 218, 302, 402, 502) is composed of at least one of a paper cutout pattern (412, 422) or an authentic pattern (314, 324).

5. The system (100) according to claim 1, further comprising adhesives (306, 406, 606, 612) for connecting the films (214, 216, 218, 302, 402, 502) and the sensors (110, 300, 400, 500, 600a to d).

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