LOOP-BASED MEASURING DEVICE
20220054041 · 2022-02-24
Inventors
Cpc classification
G01B7/16
PHYSICS
A61B5/0816
HUMAN NECESSITIES
A61B5/053
HUMAN NECESSITIES
A61B5/02438
HUMAN NECESSITIES
A61B5/1121
HUMAN NECESSITIES
A61B5/1072
HUMAN NECESSITIES
A61B5/0245
HUMAN NECESSITIES
A61B2562/12
HUMAN NECESSITIES
A61B5/0295
HUMAN NECESSITIES
A61B5/11
HUMAN NECESSITIES
A41H1/02
HUMAN NECESSITIES
International classification
A61B5/11
HUMAN NECESSITIES
A41H1/02
HUMAN NECESSITIES
A61B5/00
HUMAN NECESSITIES
A61B5/107
HUMAN NECESSITIES
Abstract
The present invention will provide a measuring device embedded within an elastic garment that will provide detect bodily movement by deforming a conductive material and measuring the change in electrical quantities within the conductive material as it deforms. Furthermore, the present invention will provide a measuring device configured to incorporate machine learning algorithms to estimate physiological, kinematic, dynamic, psychological, physical, biological, or other health parameters based upon the variations in electrical quantities within the conductive material as it deforms. This is accomplished through an elastic textile, a conductive element embedded within the elastic textile, and an electronic device configured to measure electrical quantities of the conductive element. These elements work in conjunction to detect and monitor movement in the human body.
Claims
1. A loop-based sensor, comprising: at least one conductive element embedded within a textile, said at least one conductive element forming at least one loop; a textile area formed within said at least one loop, said textile area configured to be worn on the surface of the body, said textile area configured to deform said at least one conductive element with the body as it moves; and an electronic device in electrical communication with said at least one conductive element, said electronic device configured to monitor the electrical quantities of said conductive element, wherein said electrical quantities change when said at least one conductive element deforms; wherein said electronic device will detect and measure body parameters by comparing changes in electrical quantities in said at least one conductive element.
2. The sensor of claim 1, wherein said electrical quantities comprise inductance and wherein said electronic device is configured to measure said inductance within said at least one conductive element.
3. The sensor of claim 2, wherein said measuring of said inductance comprises measuring the oscillation frequency of said at least one conductive element.
4. The sensor of claim 1, wherein said electrical quantities comprise capacitance and wherein said electronic device is configured to measure said capacitance within said at least one conductive element.
5. The sensor of claim 1, wherein said electrical quantities comprise resistance and wherein said electronic device is configured to measure the opposition to the flow of electric current through said at least one conductive element.
6. The sensor of claim 1, wherein said at least one conductive element is formed in a planar configuration and wherein said at least one loop forms a generally spiral configuration.
7. The sensor of claim 1, wherein said at least one conductive element is formed in a three-dimensional configuration.
8. The sensor of claim 7, wherein said three-dimensional configuration forms a generally conical configuration.
9. The sensor of claim 1, wherein said at least one conductive element further comprises a plurality of conductive elements forming concentric loops.
10. The sensor of claim 1, wherein said at least one conductive element further comprises a plurality of discontinuous segments.
11. The sensor of claim 1, wherein said textile further comprise an elastic, form-fitting textile, wherein said at least one conductive element is stitched into said textile, and wherein said at least one conductive element does not overlap itself.
12. The sensor of claim 1, wherein said textile further comprises a stretchable, non-conductive filament, wherein said at least one conductive element is formed around said non-conductive filament, wherein said at least one conductive element has a generally coiled shape.
13. The sensor of claim 1, wherein said textile further comprises a patch, wherein said patch is affixed to a garment for monitoring body parameters.
14. The sensor of claim 13, wherein said patch further comprises a wireless communication device, wherein said wireless communication device is configured to communicate any detected movement and physical parameters to an external device.
15. The sensor of claim 1, wherein said body parameters further comprise limb movements, body flexion, body extension, body expansion, body contraction, joint rotations, joint angles, joint position, posture, gait, step length, stride length, cadence, speed, foot angle, hip angle, knee angle, gait phase, body height, body weight, body mass index, movements of the lungs, air in/out the lungs, vibrations of the vocal cords, respiration rate, volume of air inhaled or exhaled, coughing, talking, laughing, movements of the heart, heartbeat, opening and closing of the heart valves, blood volume and blood flow, deformation of blood vessels, heart rate, blood flow, and temperature.
16. The sensor of claim 1, wherein said body parameters are used to estimate health parameters, said health parameters comprising physiological, kinematic, dynamic, psychological, physical, biological, or other health parameters.
17. The sensor of claim 1, further comprising machine learning algorithms configured to monitor and compare said body parameters, said machine learning further comprising supervised methods, unsupervised method, reinforcement learning, transfer learning, encoders, decoders, semi-supervised methods, neural networks, deep neural networks, convolution neural networks, ensembled estimators, bagging methods, decision tries, logistic regression, random forest, linear discriminant analysis, support vector machine, naïve Bayes, and K-nearest neighbors algorithm.
18. A body sensor, comprising: an elastic, form-fitting garment configured to be worn on the body, said garment configured to deform with the body as it moves; a conductive element embedded within said garment, said conductive element configured to deform with said garment as the body moves; and an electronic device in electrical communication with said conductive element, said electronic device configured to measuring the oscillation frequency of said at least one conductive element, wherein said oscillation frequency changes when said conductive element deforms; wherein said body sensor will measure movements of the body by comparing changes in inductance in said conductive element.
19. A method of monitoring body movement, said method comprising: embedding a conductive element within an elastic, form-fitting textile, said conductive element forming a loop, wherein the area within the loop forms a textile area; positioning said textile area adjacent to the body, wherein said textile area and said conductive element are configured to deform with the body as it moves; measuring variations of electrical or electromagnetic quantities within said conductive element as it deforms with the body; and estimating physiological, kinematic, dynamic, psychological, physical, biological or health parameters based upon said variations of electrical or electromagnetic quantities.
20. The method of claim 19, wherein said conductive element is spun around a non-conductive fabric.
Description
DESCRIPTION OF THE DRAWINGS
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DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT
[0048] Illustrative embodiments of the invention are described below. The following explanation provides specific details for a thorough understanding of and enabling description for these embodiments. One skilled in the art will understand that the invention may be practiced without such details. In other instances, well-known structures and functions have not been shown or described in detail to avoid unnecessarily obscuring the description of the embodiments.
[0049] Unless the context clearly requires otherwise, throughout the description and the claims, the words “comprise,” “comprising,” and the like are to be construed in an inclusive sense as opposed to an exclusive or exhaustive sense; that is to say, in the sense of “including, but not limited to.” Words using the singular or plural number also include the plural or singular number respectively. Additionally, the words “herein,” “above,” “below” and words of similar import, when used in this application, shall refer to this application as a whole and not to any particular portions of this application. When the claims use the word “or” in reference to a list of two or more items, that word covers all of the following interpretations of the word: any of the items in the list, all of the items in the list and any combination of the items in the list.
[0050] The embodiments disclosed in the present invention provide apparatus and methods for measuring a joint angle, posture and/or gait parameters, as well as provide feedback about aforementioned parameters. The embodiments described below consist of an elastic fabric configured to be worn by the user with electronics attached to it. When the embodiment is worn by the user, it automatically measures the variables solicited, including posture, angle joint and/or gait parameters. The disclosed embodiments are particularly beneficial in medical fields, such as preventive medicine, sport medicine, rehabilitation and physical training.
[0051] In a first embodiment, the present invention is used to monitor the back posture to prevent the occurrence of low back pain and/or improve the user posture by notifying him/her when a harmful or incorrect posture is being held. Furthermore, the present invention can notify the user by sound or vibration. In an alternative embodiment, the notifications can be delivered by wireless communication with an external device, for example a cellphone. Here, the present invention is wirelessly connected to an external device using an external application. The external application, or app, displays the information received by the embodiments, as well as, plotting the information in the screen. It is also possible to generate a computer file and storage it on the phone and/or share it by email, messaging apps, cloud storage apps, among other alternatives available on the cellphone.
[0052] In an alternative embodiment, the elastic fabric is configured to be worn over a single joint, for example elbow or knee. Here, the present invention comprises at least one conductive element attached on the elastic fabric. The conductive element goes over the joint such that a strain on the elastic fabric results in a change in an electrical property such as, resistance, capacitance or inductance. The mentioned electrical change is captured by a controller and processed into a desired parameter, for example, joint angle. This is particularly beneficial in fields like sport medicine, rehabilitation, physical training and virtual reality, due to the possibility of measure a joint angle.
[0053] In a further alternative embodiment, the elastic fabric with at least one conductive element is implemented in a patch configuration. The patch can be attached in any area of a garment where a measurement of strain is required. As used herein, the term “attached” refers that the elastic fabric may be sewn, knitted, embedded, or paste on a garment meant to be worn by the user.
[0054] In a further alternative embodiment, in the present invention may contain a combination of conductive elements, where each conductive element in presence of strain and/or pressure result in a change of different electrical property like inductance, capacitance or resistance. Said electrical property changes can be received and processed by the controller integrated in each measurement apparatus. In a further alternative embodiment, mentioned electrical changes can be an input into a machine learning algorithm to enhance the performance of the model trained to measure a parameter, such as join angle, posture, speed, gait parameters, etc.
[0055] In a further alternative embodiment, IMU's can be used to improve the performance of the measurement apparatus discussed in the present invention. Furthermore, embodiments which conductive element's measurement is based on inductance can be used to harvest power due to the Electromagnetic Field (EMF) produced by creation of inductance in the sensor which is a coil.
[0056] In the preferred embodiment, the measurement apparatus comprises at least one conductive element, elastic fabric and a controller, which is commonly attached to the elastic fabric or garment. The controller is programmed to read the change of an electrical property when strain and/or pressure is applied to the conductive elements as well as process the data into the desired parameters (e.g. posture, joint angle, gait parameters, etc.). In alternative embodiments, the controller may wirelessly communication with external devices, such as, computer, cellphone, tablet, etc. Additionally, some embodiments are wirelessly connected to an external device using an app. Said app displays the information received by the embodiments, as well as, plotting the information in the screen. It is also possible to generate a computer file and store it on the phone and/or share it through email, messaging apps, cloud storage apps, among other alternatives available on the cellphone.
[0057] Referring now to
[0058] Smart garment 10 may be adapted to be worn by a user. Sensors 14, which may be positioned at the user's lower back level, and may sense physiological or performance characteristics of the user. Physiological characteristics may be indicative of conditions of the user's body (e.g., respiration). Performance characteristics may be indicative of behavior of the user's body to respect to a parameter of interest (e.g., movement, position, speed). Moreover, sensors 14 may transmit data of the aforementioned characteristics to an electronic device 12 positioned on the upper level of the textile portion 16.
[0059] Sensors 14 may consist in a conductive element such as, a thin copper wire or a conductive thread made by a combination of metallic wires, sewn into a textile portion 16 using hand or machine sewing stitches, for example, a zigzag stitch.
[0060] Electronic device 12 may contain a microcontroller to read the data sent by sensors 14, a wireless connection device and batteries. Electronic device 12 may receive the data sent by sensors 14 and process it in order to obtain a value of interest or an electrical characteristic of sensors 14 (e.g., angle, velocity, coordinate, distance, voltage, inductance, resistance, capacitance), as well as wireless transmission of the data via to an external device (e.g., computer, cellphone, tablet, etc.)
[0061] Referring now to
[0062] Referring now to
[0063] The smart garment 30 may be adapted to be worn by a user. The elastic textile portion 34 may be located in the thoracic section of the smart garment 30. At least one sensor 32 may be attached on an elastic textile portion 34 in a flat loop configuration using basic stitches (e.g., straight, zigzag, wave form, stretch stitch, knit stitch, blind hem) or others. As used herein, the term “attached” refers that sensors 32 may be sewn, knitted, embedded, or intermeshed with an elastic textile portion 34. Sensors 32 may also sense physiological or performance characteristics of the user and transmit the data to an electronic device 12. Physiological characteristics may be indicative of conditions of the user's body (e.g., respiration). Performance characteristics may be indicative of behavior of the user's body to respect to a parameter of interest (e.g., movement, position, speed).
[0064] The electronic device 12 may contain a microcontroller to read the data sent by sensors 32, wireless communication and batteries. The electronic device 12 may receive the data sent by sensors 32 and process it in order to obtain a value of interest (e.g., angle, velocity, coordinate, distance, respiration, heart rate), as well as transmit wirelessly the data to another external electronic device (e.g., computer, cellphone, tablet, etc.)
[0065] Referring now to
[0066] The electronic device 12 may contain a microcontroller to read the data sent by sensors 42, wireless communication and batteries. The electronic device 12 may receive the data sent by sensors 42 and process it in order to obtain a value of interest (e.g., angle, velocity, coordinate, distance, respiration, heart rate), as well as wirelessly transmit the data to an external device (e.g., computer, cellphone, tablet, etc.)
[0067] Referring now to
[0068] Referring now to
[0069] Referring now to
[0070] Referring now to
[0071] Referring now to
[0072] Referring now to
[0073] Referring now to
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[0075] Sensors 14, 32, and 42 may contain at least one thin conductive element, which in presence of a deformation, may presents a variation in an electrical characteristic (e.g., voltage, current, resistance, inductance, capacitance). Sensors 14, 32, and 42 may be attached to an elastic component 640 and/or a textile portion 62 in a flat coil configuration using basic stitches (e.g., straight, zigzag, wave form, stretch stitch, knit stitch, blind hem) or others. As used herein, the term “attached” refers that sensors 14, 32, and 42 may be sewn, knitted, embedded, or intermeshed with an elastic component 640 and/or a textile portion 62.
[0076] Electronic device 12 may contain a microcontroller to read the data transmitted by sensors 14, 32, and 42, wireless communication and batteries. Electronic device 12 may receive the data sent by sensors 14, 32, and 42 and process it in order to obtain a value of interest (e.g., angle, velocity, coordinate, distance, respiration, heart rate), as well as transmitting the data wirelessly to an external device (e.g., computer, cellphone, tablet, etc.).
[0077] Referring now to
[0078] Referring now to
[0079] Referring now to
[0080] Referring now to
[0081] Referring now to
[0082] It should be noted that textile in this context relates to a portion of a garment or cloth. Such a textile can have different shapes, be made of different materials, which could be either stretchable or not, and have ornaments or other functional elements including, but not limited to buttons, zips, brooches, stones, perforated fabric, sequins, light-emitting diodes (LEDs), digital displays, and decorative holes.
[0083] Regarding machine learning algorithms, various embodiments may be used to fully utilize the dynamic and powerful utility of machine learning and artificial intelligence. In a first embodiment, a machine learning model is developed for each single individual. In this configuration a personalized model is developed. In an alternative embodiment, a machine learning model is developed across any potential user. In this configuration one single model is developed to enable a more universal, plug-and-play use of the sensor.
[0084] In a further alternative embodiment, transfer learning is used. For example, a single model is first developed across any potential user. Such a model is then retrained with data of only one participant to make it individual-specific.
[0085] In a further alternative embodiment, a model is generated for each single configuration of the sensor. For instance, a model is trained for the spiral configuration, one model is trained for the configuration of
[0086] In a further alternative embodiment, a model is generated for each location the sensor is placed. For instance, a model is trained for the knee joint, one for the elbow, one for the wrist, and other models for other body parts.
[0087] In a further alternative embodiment, a model is generated for each single application. For instance, a model is trained for gait analysis, one model is trained for good-posture, one model for monitoring breathing, and other models for other physiological, kinematic, dynamic, psychological, physical, biological or health parameters.
[0088] In a further alternative embodiment, a model is generated for each single material used in the sensor. That would include different textiles and different conductive materials.
[0089] In a further alternative embodiment, a model is generated to combine one or more parameters presented in the previous embodiments. For instance, a model could include the combination of different textiles and materials, a model could include different positions including for instance shoulder and wrist, a model could include different shapes such as spiral and single loop, a model could include a single individuals with one or multiple sensors, a model could include a single textile, different conductive materials, different sensor configurations, and a single use, such as kinematics. This embodiment includes other combinations of the previous parameters.
[0090] In a further alternative embodiment, transfer learning, which focuses on storing knowledge gained while solving one problem and applying it to a different but related problem, is used across the embodiment previously presented.
[0091] In a further alternative embodiment, a method is proposed whereby the sensor is placed adjacent to the body of a person, an electronic device reads the electrical or electromagnetic quantities associated to the sensor, variation of the electrical or electromagnetic quantities associated to the sensor are measured, and such measurements are used to estimate physiological, kinematic, dynamic, psychological, physical, biological or health parameters.
[0092] In a further alternative embodiment, the estimates for physiological, kinematic, dynamic, psychological, physical, biological or health parameters is accomplished through machine learning. Machine learning algorithms comprise supervised methods, unsupervised method, reinforcing learning, semi-supervised methods, neural networks, deep neural networks, convolution neural networks, ensembled estimators, bagging methods, decision tries, logistic regression, random forest, linear discriminant analysis, support vector machine, naïve Bayes, or K-nearest neighbors' algorithm.
[0093] In a further alternative embodiment, the sensor is placed in a position to detect movements of the lungs, air in/out the lungs or vibrations of the vocal cords. Such detection is processed to detect parameters including respiration rate, volume of air inhaled or exhaled, coughing, talking, and laughing.
[0094] In a further alternative embodiment, the sensor is placed in a position to detect movements of the heart. Such detection is processed to detect heartbeat, hear rate, opening and closing of the heart valves, blood volume and blood flow. In yet a further alternative embodiment, the sensor is placed closed to a blood vessel in close proximity to the skin to detect heart rate and blood flow.
[0095] In a further alternative embodiment, the surface defined by the loop is not crossed by any element from human body, including but not limited to, torso and limbs.
[0096] In summary, the present invention discloses a loop-based sensor, comprising at least one conductive element embedded within a textile, said at least one conductive element forming at least one loop, a textile area formed within said at least one loop, said textile area configured to be worn on the surface of the body, said textile area configured to deform said at least one conductive element with the body as it moves; and an electronic device in electrical communication with said at least one conductive element, said electronic device configured to monitor the electrical quantities of said conductive element, wherein said electrical quantities change when said at least one conductive element deforms, wherein said electronic device will detect and measure body parameters by comparing changes in electrical quantities in said at least one conductive element.
[0097] Electrical quantities of the present invention further comprise inductance and wherein said electronic device is configured to measure said inductance within said at least one conductive element. Here, the measuring of said inductance comprises measuring the oscillation frequency of said at least one conductive element. Alternatively, the electrical quantities comprise capacitance where the electronic device is configured to measure said capacitance within said at least one conductive element. Alternatively, the electrical quantities comprise resistance where the electronic device is configured to measure the opposition to the flow of electric current through said at least one conductive element.
[0098] In an alternative embodiment, the at least one conductive element is formed in a planar configuration and wherein said at least one loop forms a generally spiral configuration. Alternatively, the at least one conductive element is formed in a three-dimensional configuration and wherein said at least one loop forms a generally conical configuration. Alternatively, the at least one conductive element further comprises a plurality of conductive elements forming concentric loops. In an alternative embodiment, the at least one conductive element further comprises a plurality of discontinuous segments in electrical communication.
[0099] In an alternative embodiment, the textile further comprises an elastic, form-fitting textile, wherein said at least one conductive element is woven, knitted, or stitched into said textile, and wherein said at least one conductive element does not overlap itself.
[0100] In an alternative embodiment, the present invention further comprises a stretchable, non-conductive filament, wherein said at least one conductive element is formed around said non-conductive filament, wherein said at least one conductive element is coiled around said filament.
[0101] In an alternative embodiment, the textile further comprises a patch, wherein said patch is affixed to a garment for monitoring body parameters. Here, the patch further comprises a wireless communication device, wherein said wireless communication device is configured to communicate any detected movement and physical parameters to an external device.
[0102] In an alternative embodiment, the body parameters comprise body movement and other bodily functions. Body parameters further comprise limb movements, body flexion, body extension, body expansion, body contraction, joint rotations, joint angles, joint position, posture, gait, step length, stride length, cadence, speed, foot angle, hip angle, knee angle, gait phase, body height, body weight, body mass index, movements of the lungs, air in/out the lungs, vibrations of the vocal cords, respiration rate, volume of air inhaled or exhaled, coughing, talking, laughing, movements of the heart, heartbeat, opening and closing of the heart valves, blood volume and blood flow, deformation of blood vessels, heart rate, blood flow, and temperature. The body parameters are used to estimate health parameters, said health parameters comprising physiological, kinematic, dynamic, psychological, physical, biological, or other health parameters.
[0103] In an alternative embodiment, the body parameters further comprise machine learning algorithms configured to monitor and compare said body parameters, said machine learning further comprising supervised methods, unsupervised method, reinforcement learning, transfer learning, encoders, decoders, semi-supervised methods, neural networks, deep neural networks, convolution neural networks, ensembled estimators, bagging methods, decision tries, logistic regression, random forest, linear discriminant analysis, support vector machine, naïve Bayes, and K-nearest neighbors algorithm.
[0104] A method of monitoring bodily physical parameters comprises embedding a conductive element within an elastic, form-fitting textile, positioning said textile adjacent to the body, wherein said textile and said conductive element are configured to deform with the body as it moves, measuring variations of electrical or electromagnetic quantities within said conductive element as it deforms with the body, and estimating physiological, kinematic, dynamic, psychological, physical, biological or health parameters based upon said variations of electrical or electromagnetic quantities.
[0105] In an alternative embodiment, the estimation of physiological, kinematic, dynamic, psychological, physical, biological or health parameters further comprises machine learning estimation comprising supervised methods, unsupervised method, reinforcement learning, transfer learning, encoders, decoders, semi-supervised methods, neural networks, deep neural networks, convolution neural networks, ensembled estimators, bagging methods, decision tries, logistic regression, random forest, linear discriminant analysis, support vector machine, naïve Bayes, and K-nearest neighbors algorithm.
[0106] While the above description contains specific details regarding certain elements, sizes, and other teachings, it is understood that embodiments of the invention or any combination of them may be practiced without these specific details. Specifically, although certain materials and shapes are designated in the above embodiments, any suitable materials or shapes may be used. These details should not be construed as limitations on the scope of any embodiment, but merely as exemplifications of the presently preferred embodiments. In other instances, well known structures, elements, and techniques have not been shown to clearly explain the details of the invention.
[0107] The above detailed description of the embodiments of the invention is not intended to be exhaustive or to limit the invention to the precise form disclosed above or to the particular field of usage mentioned in this disclosure. While specific embodiments of, and examples for, the invention are described above for illustrative purposes, various equivalent modifications are possible within the scope of the invention, as those skilled in the relevant art will recognize. Also, the teachings of the invention provided herein can be applied to other systems, not necessarily the system described above. The elements and acts of the various embodiments described above can be combined to provide further embodiments.
[0108] Changes can be made to the invention in light of the above “Detailed Description.” While the above description details certain embodiments of the invention and describes the best mode contemplated, no matter how detailed the above appears in text, the invention can be practiced in many ways. Therefore, implementation details may vary considerably while still being encompassed by the invention disclosed herein. As noted above, particular terminology used when describing certain features or aspects of the invention should not be taken to imply that the terminology is being redefined herein to be restricted to any specific characteristics, features, or aspects of the invention with which that terminology is associated.
[0109] While certain aspects of the invention are presented below in certain claim forms, the inventor contemplates the various aspects of the invention in any number of claim forms. Accordingly, the inventor reserves the right to add additional claims after filing the application to pursue such additional claim forms for other aspects of the invention.