WO2020055421A1

WO2020055421A1 - Biometrics & adjusting fabrics

Info

Publication number: WO2020055421A1
Application number: PCT/US2018/051047
Authority: WO
Inventors: Hao Meng; Brian R. Jung; William Meyer
Original assignee: Hewlett-Packard Development Company, L.P.
Priority date: 2018-09-14
Filing date: 2018-09-14
Publication date: 2020-03-19

Abstract

Examples described herein relate to a system consistent with the disclosure. For instance, the system may comprise a sensor to collect biometrics from a body, a fabric positioned around the body and coupled to the sensor, and a controller to receive the biometrics from the body, analyze the biometrics from the body, and cause the fabric to adjust based on the analyzed biometrics from the body.

Description

BIOMETRICS & ADJUSTING FABRICS

BACKGROUND

[0001] Wearable devices such as fitness trackers, smartwatches, internet of things (ioT), etc. may connect with other devices. Wearable devices may provide a user with data related to the physical activity of the user.

BRIEF DESCRIPTION OF THE DRAWINGS.

[0002] Figure 1 illustrates an example of a system consistent with the disclosure

[0003] Figure 2 illustrates an example of an apparatus suitable with a system consistent with the disclosure.

[0004] Figure 3 illustrates an example of a method consistent with the disclosure.

[000SJ Figure 4 illustrates an example diagram of a non-transitory machine readable medium suitable with a system consistent with the disclosure.

[0006] Figure 5 illustrates an example of a system consistent with the disciosure.

Detailed Description

[0007] Fabrics may include sensors to measure the physical status of a user.

The fabric may allow the sensors to be positioned at different location of a body when worn by a user. The sensors may notify the user of the physical status of the user.

That is, the sensors may provide the user with an update of the user’s physical status (e.g., paces taken, calories burned, minutes active) among other user information. The system may include a fabric positioned around the body of a user and sensors coupled to the fabric to update the user of their physical status, etc.

[0008] However, the system may not allow for adjustment of the fabric based on the updates provided by the sensors. For instance, compression fabric may not adjust the compression of the fabric based on the updated information from a sensor.

Compression fabric not adjusting based on updated information may lead to injury during physical activity. In addition, fabrics that adjust the compression of the fabric during physical activity may provide a more efficient experience for the user during physical activity.

[0009] As such, biometrics & adjusting fabrics, as described herein, may include a fabric, a sensor to collect biometrics, and a controller to cause the fabric to be adjusted based on analyzed biometrics. Adjusting the fabric during physical activity based on the biometrics of a user may allow for a target fit of the fabric. Accordingly, this disclosure describes systems that receives biometrics, analyzes the biometrics, and causes a fabric to adjust based on the analyzed biometrics.

[0010] Figure 1 illustrates an example of a system 100 consistent with the disclosure. The system 100 may be used with a variety of wearable devices, such as fitness trackers, smartwatches, etc., for example. In some examples, the system 100 may include fabric 102. The fabric 102 may be positioned around the body of a user. For example, the fabric 102 may be an article of clothing worn by the user in addition, the fabric 102 may be an accessory (e.g., wrist band, sleeve) worn by the user. That is, the fabric 102 may be socks, shorts, shirts, arm sleeves, leg sleeves, bottoms/pants, wrist bands, leg bands, underwear, etc. positioned around different parts of the body of the user. As used herein,“fabric” refers to cloth or material produced by weaving together threads.

[0011] The fabric 102 may be a compression fabric used to produce a fight fit around the body. As used herein,“compression fabric” refers to a piece of clothing that fits tightly around the body when worn by a user. In some examples, compression fabrics may provide support for a user wearing the fabric 102 during physical activity in some examples, the degree of compression of the fabric 102 may vary at different times during the use of the fabric 102 depending on the state of the body. As such, the fabric 102 may adjust to create a target fit around the body of a user. That is, the fabric 102 may adjust depending on the state of the muscles, heart rate, oxygen saturation, perspiration, temperature, or a combination thereof of the user. For example, if the user is experiencing extreme muscle fatigue, as compared to a previous state, the compression of the fabric 102 may loosen to enhance the workout of the user. In contrast, if the muscles of the user become less fatigued, as compared to a previous state, the compression of the fabric 102 may tighten to enhance the physical activity of the user. That is, the degree of compression may vary depending on the state of the body. As used herein,“target fit” refers to the amount of compression in a fabric that provides the user with a fit that allows the user to safely conduct physical activity without injury based on the health signs of the user and/or user input. As used herein,“health signs” refers to measurements to indicate the state of a body’s significant functions.

[0012] in some examples, adjusting the compression of the fabric may create an optimum environment for physical activity for a user. That is, adjusting the compression of the fabric 102 may improve exercise efficiency and/or reduce the risk of injury during physical activity. As used herein,“adjust” refers to the process of compressing an object to create a tighter fit or relaxing an object to create a looser less constricted fit.

[0013] In some examples, the system 100 may include a sensor 104 coupled to the fabric 102. in some examples, the sensor 104 may be removable coupled to the fabric 102. In various examples, the sensor 104 may collect biometrics from the body of a user. For examples, the sensor 104 may be an electromyography sensor, a heart rate sensor, an inertia measurement sensor, a blood oxygen level sensor, a thermometer, etc to measure the muscle fatigue, heart rate, oxygen saturation, perspiration, temperature, etc. of the body. However, this disclosure is not so limited. The senor 104 may be a sensor that allows for the collection of biometrics to measure the health signs of a body. As used herein,“biometrics” refers to the collection and/or measurement of the health signs of a body. It should be understood that when an element is referred to as being "on,"“in contact,”“coupled to”, or "coupled with" another element, it may be directly on, in contact, or coupled with the other element or intervening elements may be present.

[0014] In some examples, the sensor 104 may be positioned at various locations on the fabric 102. For example, the sensor 104 may be an electromyography sensor positioned in the arm of a shirt to measure the muscle fatigue of a body. In addition, the electromyography sensor may be positioned in different locations of the fabric 102 to measure different muscle groups. That is, the sensor 104 may be positioned in different locations of the fabric 102 to measure different biometrics of the body.

[0015] in some examples, the state of the body may be determined by measuring the different biometrics of the body with the sensor 104. That is, the sensor 104 may measure muscle fatigue, heart rate, oxygen saturation, perspiration, temperature, or other health signs to measure the biometrics of the body and determine the body state. In some examples, the sensor 104 may continuously collect biometrics from the body. That is, the sensor 104 may collect biometrics from the body without interruptions until the system 100 is no longer active (e.g., turned off). However, this disclosure is not so limited. In some examples, the sensor 104 may collect biometrics at varying intervals. For instance, the sensor 104 may collect biometrics every two minutes, five minutes, ten minutes, fifteen minutes, twenty minutes, etc. until the system 100 is no longer active in some examples, the rate at which biometrics are collected is determined by a user. That is, a user may set and/or determine how often the sensor 104 collects biometrics.

[0016] In some examples, the sensor 104 may collect biometrics from the body and send the collected biometrics to a controller 106 coupled to the fabric 102. The sensor 104 may send the collected biometrics to the controller 106 as the biometrics are collected. For instance, the sensor 104 may continuously send the collected biometrics to the controller 106 until the system 100 is no longer active. In contrast, the sensor 104 may send the collected biometrics to the controller 106 at varying intervals. For example, the sensor 104 may send the collected biometrics to the controller 106 every two minutes, five minutes, ten minutes, fifteen minutes, twenty minutes, etc. until the system 100 is no longer active. The sensor 104 may send the collected biometrics to the controller 106 as the sensor 104 collects the biometrics and/or offload to other storage/analysis devices.

[0017] in some examples, the controller 106 may receive the collected biometrics from the sensor 104. After receiving the collected biometrics from the sensor 104 the controller 106 may store the collected biometrics on a memory resource (e.g., memory resource 222 of Figure 2). In some examples, the memory resource may be included in the controller 106. Storing the collected biometrics may allow the controller 106 to analyze the collected biometrics. [0018] The controller 106 may analyze the received biometrics to determine the target fit of the fabric 102. In some examples, the controller 106 may compare the received biometrics with previously received biometrics to analyze the biometrics and determine the target fit of the fabric 102. However, this disclosure is not so limited. In some examples, the controller 106 may compare the received biometrics with biometrics inputted by the user to analyze the biometrics and determine the target fit of the fabric 102. For example, the user may enter biometrics before the sensor 104 begin to measure the biometrics to establish a baseline for analysis. As used herein, “baseline” refers to a start and/or initial biometric.

[0019] In some examples, the controller 106 may compare each vital sign of the biometrics with a previously received vital sign of a previous biometric and then analyze the compared biometrics. As used herein,“analyze” refers to the act of comparing each current vital sign with the respective previous vital sign and assessing all the compared health signs together. For example, the controller 106 may compare the current heart rate of the user with the previous heart rate of the user and compare the current temperature of the user with the previous temperature of the user. Then the controller 106 may asses the compared heart rate and the compared temperature together to complete the analysis.

[0020] in some examples, the controller 106 may cause the fabric 102 to adjust based on the analyzed biometrics. That is, the controller 106 may analyze the muscle fatigue, heart rate, oxygen saturation, perspiration, temperature, or other health signs of the user and cause the fabric 102 to adjust to provide a target fit of the fabric 102. In some examples, adjusting the fabric 102 based on the biometrics of the user may enhance the exercise experience of the user by reducing the risk of overload and/or injury in some examples, the fabric 102 may adjust by tightening based on the analyzed biometrics and/or user input in some examples, the fabric 102 may adjust by loosening based on the analyzed biometrics and/or user input. However, this disclosure is not so limited in some examples, the fabric 102 may adjust by tightening in a first location based on the analyzed biometrics and/or user input and loosening in a second location based on the analyzed biometrics and/or user input. For example, if the fabric 102 was made into a shirt the fabric may tighten in the arm region based on the analyzed biometrics and/or user input and ioosen in the chest region based on the analyzed biometrics and/or user input.

[0021] In some examples, the controller 106 may cause the fabric 102 to adjust based on a set cycle. As used herein,“cycle” refers to a regularly repeated sequence of events. For example, the controller 106 may cause the fabric 102 to Ioosen or tighten every 10 minutes until the compression of the fabric 102 reaches a threshold. As used herein,“threshold” refers to the level before an action or object stops. In some examples, the controller 106 may cause the fabric 102 to adjust based on a set cycle and analyzed biometrics. For example, the fabric 102 may be set to tighten at set intervals as long as the collected biometrics are in a set range. In addition, the set cycles may be determined based on the collected biometrics in some examples, the set cycles may be based on user input.

[0022] in some examples, the controller 106 may notify the user that the fabric 102 will adjust before adjusting the fabric 102. For instance, the controller 106 may cause a notification device (e.g., notification device 515 of Figure 5) to notify the user that the fabric 102 is to adjust.

[0023] Figure 2 illustrates an example of an apparatus 220 suitable with a system consistent with the disclosure. As illustrated in Figure 2, the apparatus 220 includes a processing resource 221 and a memory resource 222 The processing resource 221 may be a hardware processing unit such as a microprocessor, application specific instruction set processor, coprocessor, network processor, or similar hardware circuitry that may cause machine-readable instructions to be executed in some examples, the processing resource 221 may be a plurality of hardware processing units that may cause machine-readable instructions to be executed. The processing resource 221 may inciude central processing units (CPUs) among other types of processing units. The processing resource 221 may also include dedicated circuits and/or state machines, such as in an Application Specific Integrated Circuit (ASIC), Field

Programmable Gate Array (FPGA) or similar design-specific hardware. The memory resource 222 may be any type of volatile or non-volatile memory or storage, such as random-access memory (RAM), flash memory, read-only memory (ROM), storage volumes, a hard disk, or a combination thereof. [0024] The memory resource 222 may store instructions thereon, such as instructions 223, 224, 225, 226, and 227. When executed by the processing resource 221 , the instructions may cause the apparatus 220 to perform specific tasks and/or functions. For example, the memory resource 222 may store instructions 223 which may be executed by the processing resource 221 to cause the apparatus 220 to receive a collection of biometrics from a sensor coupled to a fabric positioned around the body. In some examples, a sensor may collect biometrics from the body of a user. In various examples, a plurality of sensors may collect biometrics from the body of a user to obtain the health signs of the user. The sensor may send the collection of biometrics to the processing resource 221 for analysis. The sensor may be coupled to the fabric to collect biometrics from the body.

[0025] The memory resource 222 may store instructions 224 which may be executed by the processing resource 221 to cause the apparatus 220 to analyze the collection of biometrics. The processing resource 221 may analyze the collection of biometrics sent from the sensor. That is, the processing resource 221 may compare current biometrics of a user with initial biometrics to analyze the collection of biometrics in some examples, the initial biometrics may be obtained by a sensor at the start of the collection of biometrics to establish a baseline. However, this disclosure is not so limited. In some examples, the initial biometrics may be entered by a user before the collection of biometrics starts to establish a baseline in some examples, the initial biometric may be both obtained by a sensor and enter by a user to establish a baseline. As used herein,“initial biometrics" refers to the first collection and/or measurement of the health signs of a body. As used herein,“current biometrics” refers to the most recent collection and/or measurement of the health signs of a body.

[0026] The memory resource 222 may store instructions 225 which may be executed by the processing resource 221 to cause the apparatus 220 to determine a target fit of the fabric based on the analyzed collection of biometrics. After the collection of biometrics is analyzed a target fit of the fabric may be determined. That is, the processing resource may determine how the fabric will adjust to obtain a target fit. in some examples, the target fit may be based on the collected biometrics of a user. In various examples, the target fit may be based on a user input and the collection of biometrics. As such, the target fit may change as the health signs changes.

[0027] The memory resource 222 may store instructions 226 which may be executed by the processing resource 221 to cause the fabric to adjust based on the determined target fit, wherein the fabric is adjusted by either tightening or loosening the fabric in some examples, after the collection of biometrics has been analyzed the fabric to provide the user with a target fit. For instance, if it is determined that the current compression of the fabric is too tight, based on the analyzed biometrics, the fabric may loosen, as compared to the previous state. In contrast, if it is determined that the current compression of the fabric is too loose, based on the analyzed biometrics, the fabric may tighten, as compared to the previous state.

[0028] The memory resource 222 may store instructions 227 which may be executed by the processing resource 221 to notify a user before the fabric adjusts. In some examples, the user may receive a notification that the fabric positioned around the body of the user will adjust before the fabric adjust. That is, a notification may be sent to an external computing device (e.g., tablet, smart watch, laptop, internet of things (loT), etc.) to notify the user that the fabric will adjust. In some examples, after the fabric adjust the user may be prompted to indicate whether the adjusted fabric is suitable to the user if the user indicates that the adjusted fabric is too tight the fabric may be adjusted and/or loosened based on the user input and the collection of biometrics. In contrast, if the user indicates that the adjusted fabric is too loose the fabric may be adjusted and/or tightened based on the user input and the coliection of biometrics. However, if the user indicates that the adjusted fabric is suitable the fabric may not adjust until the collection of biometrics is anaiyzed.

[0029] Figure 3 illustrates an example of a method 330 consistent with the disclosure. Method 330 may be performed, for example, by a controller (e.g., controller 106, described in Figure 1 ) of a system (e.g., system 100, described in Figure 1 ). In some examples, the method 330 may be performed with more or less elements.

[0030] At 332, the method 330 may include measuring, with a senor, current biometrics from a body. In some examples, the controller may cause a sensor to take continuous measurements and/or collection of the biometrics of a user. That is, the sensor may measure and/or collect information related to a user’s muscle fatigue, heart rate, oxygen saturation, perspiration, temperature, or other health signs of a user to obtain the current biometrics.

[0031] At 333, the method 330 may include analyzing the current biometrics to determine a target fit of a fabric. In some examples, the fabric may be positioned around the body. The user may wear the fabric before the sensor is activated to position the fabric around the body of a user. As such, the controller may adjust the compression of the fabric to achieve a target fit based on the measurements of the current biometrics of the body. In some examples, the target fit may be based on the analyzed biometrics and a user input of an actual fit. As used herein,“actual fit” refers to the fit of a fabric determined by the user. For example, if the user determines that the fabric is too tight for the physical activity the actual fit of the fabric may be too tight.

[0032] At 334, the method 330 may include adjusting the fabric after a

determination of the target fit of a fabric. In some examples, when the system is activated the fabric may adjust based on the analyzed current biometrics in some examples, the controller may adjust the fabric by either tightening or loosening the fabric.

[0033] At 335, the method 330 may include sending a notification to notify a user that the fabric is to adjust before the fabric adjust. In some examples, a notification may be sent by providing haptic feedback to notify the user that the fabric is to adjust in various examples, a notification may be sent by sending a signal to an external computing device (e.g., external computing device 514 of Figure 5) to notify the user that the fabric is to adjust.

[0034] At 336, the method 330 may include measuring initial biometrics of the body. In some examples, the controller may determine the differences between the current biometrics and previous biometrics when analyzing the current biometrics. For example, the controller may compare differences between the current biometrics and the initial biometrics to determine a target fit of the fabric. As used herein,“previous biometrics” refers to a previous collection and/or measurement of the health signs of a body. [0035] Figure 4 illustrates an example diagram of a non-transitory machine readable medium 440 suitable with a system consistent with the disclosure. The non- transitory machine-readable medium 440 may be any type of volatile or non-volatile memory or storage, such as random-access memory (RAM), flash memory, read-only memory (ROM), storage volumes, a hard disk, or a combination thereof.

[0036] The medium 440 stores instructions 441 executable by a processing resource to receive a collection of biometrics from a sensor coupled to a fabric positioned around the body. In some examples, a plurality of sensor may collect biometrics from the body of a user and send the collection of biometrics to the processing resource to be analyzed. The received collection of biometrics may assist in determining the target fit for the fabric.

[0037] The medium 440 stores instructions 442 executable by a processing resource to analyze the collection of biometrics. The collection of biometrics may be analyzed as the information (e.g., collection of biometrics) is sent to the processing resource. This may allow the processing resource to determine the target fit of the fabric on a continuous basis to provide the user with improved exercise efficiency and/or reducing the risk of physical injury during use of the system (e.g., system 100 of Figure 1 ).

[0038] The medium 440 stores instructions 443 executable by a processing resource to determine a target fit of the fabric based on the analyzed collection of biometrics. In some examples, determining the target fit may reduce the risk of injury to the user during the use of the system. That is, determining the target fit of the fabric may position the fabric around the body of a user in a manner that prevents injury during physical activity.

[0039] The medium 440 stores instructions 444 executable by a processing resource to cause the fabric to adjust based on the determined target fit. In some examples, the processing resource may adjust the fabric by either tightening or loosening the fabric. In some examples, when the system is activated the fabric may adjust based on the health signs of the user. For example, if the heart rate of the user has increased, as compared to a previous hear rate, the fabric may become less compressed (e.g., loosen) compared to a previous adjustment of the fabric. In addition, if the heart rate of the user has decreases, as compared to a previous hear rate, the fabric may become more compressed (e.g., tighten) compared to a previous adjustment of the fabric in some exampies, the target fit may be based on the analyzed biometrics and a user input of an actual fit.

[0040] The medium 440 stores instructions 445 executable by a processing resource to notify a user before the fabric adjusts. In some examples, the user may receive a notification that the fabric positioned around the body of the user will adjust before the fabric adjust. For example, the system may provide haptic feedback to the user to indicate to the user the fabric is to adjust. That is, a notification device may vibrate so the user may be notified when the fabric is to adjust in some examples, the system may provide varying degree of haptic feedback to indicate different reactions. For example, the system may provide haptic feedback in short burst to indicate the fabric is to tighten. In contrast, the system may provide haptic feedback in long burst to indicate the fabric is to loosen.

[0041] The medium 440 stores instructions 446 executable by a processing resource to store the collection of biometrics on a non-volatile memory in various exampies, the collection of biometrics may be stored on the non-volatile memory of an external computing device. In some exampies, the collection of biometrics may be stored on the non-volatile memory included with the processing resource. The stored collection of biometrics may be used to analyze the collection of biometrics. That is, the stored collection of biometrics may contain a previous collection of biometrics and the previous collection of biometrics may be compared to a current collection of biometrics to assist in the determination of the target fit for the fabric.

[0042] The medium 440 stores instructions 447 executable by a processing resource to loosen the fabric before the fabric is positioned around the body in some exampies, the fabric may be in a relaxed state when the fabric is not positioned around the body of a user. That is, when the sensor is not activated the fabric may be loose to allow a user to wear (e.g., position the fabric around a body) the fabric with ease in addition, the fabric may be in a relaxed state (e.g., loosened state) when the sensor is deactivated to allow the user to remove the fabric with ease. [0043] The medium 440 stores instructions 448 executable by a processing resource to tighten the fabric after the fabric is positioned around the body in some examples, the fabric may be in a compressed state (e.g., tightened state) when the fabric is not positioned around the body of a user. That is, when the sensor is not activated the fabric may be tightened to provide a target fit for a fabric worn by the user.

[0044] Figure 5 illustrates an example of a system 500 consistent with the disclosure. System 500 is analogous or similar to system 100 of Figure 1. Fabric 502 is analogous or similar to fabric 102 of Figure 1. Sensors 504 are analogous or similar to sensor 104 of Figure 1.

[0045] in some examples, the system 500 may include fabric 502 positioned around the body of a user. Fabric 502 collectively refers to fabric 502-1 and 502-2. The fabric 502 may be a machine washable fabric with contract and relax material embedded in the fabric 502. In some examples, the fabric 502-1 or 502-2 may be one article of clothing worn by a user. In addition, the fabric 502 may be multiple articles clothing worn by a user in some example, if the fabric 502 comprises multiple articles clothing the components (e.g., sensor 504, notification device 515, power mechanism 508) of each fabric 502-1 and 502-2 may work together as an individual system 500.

[0048] in some example, the system may include a plurality of sensors 504 coupled the fabric 502. In some examples, a portion of the sensors 504 may be removable coupled to the fabric 502. In addition, another portion of the sensors 504 may be permanently coupled to the fabric 502. In some examples, the sensors 504 may be coupled to the fabric 502 to collect biometrics from a user. That is, the sensors 504 may measure the muscle fatigue, heart rate, oxygen saturation, perspiration, temperature or other health signs of a user to collect the biometrics from the user. The sensors 504 may be positioned in different locations of the fabric 502 to obtain the measurements. For example, a sensor of the plurality of sensors 504 may be positioned in the sleeve of a shirt, chest of a shirt, leg of pant, etc. to measure different the muscle fatigue, heart rate, oxygen saturation, perspiration, temperature or other health signs of the user.

[0047] in some examples, the system 500 may include a power mechanism 508 to activate and/or deactivate the sensors 504. in some examples, the power mechanism 508 may be a button. However, this disclosure is not so limited. For example, the power mechanism may be a device to receive a signal sent by an external computing device 514 to activate and/or deactivate the sensors 504.

[0048] The system 500 may include a controller (e.g., controller 106 of Figure 1 ). In some examples, the controller may be coupled to the fabric 502. However, this disclosure is not so limited. In some examples, the controller may be included in an external computing device 514. That is, the external computing device 514 may be communicatively coupled to the components (sensors 504, power mechanism 508, notification device 515, etc.) of the system 500. The external computing device 514 may communicate with the system 500 with a wired connection or a wireless

connection. As used herein,“communicatively coupled" refers to various wired and/or wireless connections between devices such that data and/or signals may be transferred in various directions between the devices.

[0049] in some examples, the external computing device 514 may receive the collected biometrics measured by the sensors 504. For instance, the collected biometrics may be sent to the external computing device 514 by the sensors 504 as the biometrics are measured. That is, the sensors 504 may send a communication

(represented by arrow 518) to the external computing device 514. The communication 518 may contain data of the collected biometrics. In various examples, the sensor 504 may continuously communicate the collected biometrics to the external computing device 514 through communication 518. In some examples, the sensor 504 may communicate the collected biometrics to the external computing device 514 at varying intervals (e.g., every 3 minutes, every 5 minutes, etc.). The external computing device 514 may store the received collected biometrics on the memory resource included in the external computing device 514. in some examples, storing the received collected biometrics may allow the external computing device 514 to compare and/or analyze previous biometrics with current biometrics.

[0050] in some examples, the external computing device 514 may notify the user that the fabric 502 will adjust before adjusting the fabric 502. For instance, the external computing device 514 may provide notification through a display screen 516 located on the external computing device 514. In some examples, the external computing device 514 may provide notification by providing haptic feedback. For example, the external computing device 514 may vibrate to notify the user that the fabric 502 is to adjust. In some examples, the external computing device 514 may provide notification by communicating with the notification device 515. That is, the external computing device

514 may send a communication (represented by arrow 519) to the notification device

515 coupled to the fabric 502 to alert the user that the fabric 502 is to adjust. As used herein,“notification device” refers to a device used to notify a user of impending change to the system 500. For instance, the notification may notify the user that the fabric 502 is to adjust, the system is about to turn off, etc. In some examples, the notification device 515 may be a light source to provide a visual display of light to notify the user the fabric 502 is to adjust in some examples, the notification device 515 may be a display screen to provide a visual display to notify the user the fabric 502 is to adjust in some examples, the notification device 515 may be a motor to provide haptic feedback to notify the user the fabric 502 is to adjust in some examples, the notification device 515 may be a speaker to provide audio feedback to notify the user that the fabric 502 is to adjust.

[0051] in some examples, the external computing device 514 may cause the fabric 502 to adjust based on the analyzed biometrics. The external computing device 514 may analyze the muscle fatigue, heart rate, oxygen saturation, perspiration, temperature, or other health signs of the user and cause the fabric 502 to adjust to provide a target fit of the fabric 502. The external computing device 514 may then send a communication 519 to cause the fabric 502 to adjust. In some examples, adjusting the fabric 502 based on the biometrics of the user may enhance the physical activity of the user by reducing the risk of overload and/or injury.

[0052] The figures herein follow a numbering convention in which the first digit corresponds to the drawing figure number and the remaining digits identify an element or component in the drawing. Elements shown in the various figures herein may be capable of being added, exchanged, and/or eliminated so as to provide a number of additional examples of the disclosure. In addition, the proportion and the relative scale of the elements provided in the figures are intended to illustrate the examples of the disclosure and should not be taken in a limiting sense. [0053] It should be understood that the descriptions of various examples may not be drawn to scale and thus, the descriptions may have a different size and/or configuration other than as shown therein.

Claims

What is claimed:

1. A system comprising:

a sensor to collect biometrics from a body;

a fabric positioned around the body and coupled to the sensor; and a controller to:

receive the biometrics from the body;

analyze the biometrics from the body; and

cause the fabric to adjust based on the analyzed biometrics from the body.

2. The system of claim 1 , wherein adjusting the fabric includes tightening the fabric, loosening the fabric, or a combination thereof.

3. The system of claim 1 , wherein the biometrics includes information on muscle fatigue, heart rate, oxygen saturation, perspiration, temperature, or a combination thereof.

4 The system of claim 1 , further comprising a plurality of sensors to collect the biometrics.

5 The system of claim 4, wherein the plurality of sensors includes an electromyography sensor, a heart rate sensor, an Inertia measurement sensor, a blood oxygen level sensor, a thermometer, inertia measurement unit sensor, or a combination thereof.

6 The system of claim 4, further comprising a power mechanism to activate the plurality of sensors.

7 The system of claim 1 , wherein the system is communicatively coupled to an external computing device to provide notification before the fabric adjusts.

8. A non-transitory machine-readable medium storing instructions executable by a processing resource to: receive a collection of biometrics from a sensor coupled to a fabric positioned around the body;

analyze the collection of biometrics;

determine a target fit of the fabric based on the analyzed collection of biometrics;

cause the fabric to adjust based on the determined target fit, wherein the fabric is adjusted by either tightening or loosening the fabric; and

notify a user before the fabric adjusts.

9. The non-transitory machine-readable medium of claim 8, further including instructions to:

loosen the fabric before the fabric is positioned around the body; and tighten the fabric after the fabric is positioned around the body.

10. The non-transitory machine-readable medium of claim 8, further including instructions to store the collection of biometrics on a non-volatile memory.

1 1. The non-transitory machine-readable medium of claim 8, wherein the collection of biometrics is analyzed as the biometrics are received.

12. A method comprising:

measuring, with a senor, current biometrics from a body;

analyzing the current biometrics to determine a target fit of a fabric, wherein a determination of the target fit is based on the analyzed current biometrics and user input of an actual fit; and

adjusting the fabric after a determination of the target fit of a fabric, wherein the fabric is positioned around the body.

13. The method of claim 12, further comprising sending a notification to notify a user that the fabric is to adjust before the fabric adjust.

14. The method of claim 13, further comprising providing haptic feedback to notify the user that the fabric is to adjust.

15. The method of claim 12, further comprising measuring initial biometrics of the body, wherein analyzing the current biometrics comprises determining the differences between the current biometrics and previous biometrics.