Patent Description:
Human range of motion is an important measure used for orthopedic and neurological studies. Clothes are considered as second skin of human body, and like skin the clothes realize all movements made by humans. All body movements cause stretching and contraction of skin in some form. Hence, human body movements can be analyzed in a better way by activating a sensor into a piece of clothing or fabric.

Conventional systems for studying range of motion include gait lab-based assessment which requires a patient to wear a body suit with multiple markers and then use 3D motion capture technology to get accurate point measurements. However, this requires intensive setup and hence huge cost. Conventional systems also utilize gyroscope and accelerometers for recording range of motion. However, the gyroscopes are not very perfect for sensing complex rotation across joints due to non-commutative nature of rotation. One conventional system disclose design of a triboelectric sensor based fabric which can provide sweat monitoring along with movement analysis. However, triboelectric fibers have low durability and are not robust to mechanical and environmental damage.

Document <CIT> discloses an article of clothing or clothing accessory for measuring body motion, posture, and/or configuration comprising sets of multiple flexible electromagnetic, light, and/or sound energy pathways, wherein each set longitudinally spans the same body joint in a selected configuration to increase measurement accuracy. Multiple flexible energy pathways longitudinally spanning the same body joint can transmit the same type or different types of energy (e.g. electromagnetic, light, or sound) and can transmit energy flows with the same flow parameters or different flow parameters.

The invention relates to a system according to claim <NUM>, alternative embodiments are defined in dependent claims <NUM>-<NUM>.

It is intended that the following detailed description be considered as exemplary only, with the true scope being indicated by the following claims.

The embodiments herein provide a sensor based wearable fabric design for identifying distortion in movements and quantifying range of motion. The typical interpretation of results obtained from conventional wearable fabric-based systems and methods has been modified to solve a problem of quantifying multi-axis complex range of motion. The range of motion is an essential part of clinical examination and is routinely used as a measure of function. For example, in case of joints, the range of motion, pain associated with the range of motion as well as the associated symptoms of distortion (e.g., crepitus and stiffness) are essential parts of the clinical examination of joints. A joint is a region of articulation between two bones. Human joints may have a complex range of motion and that can be dependent on a plurality of variables such as bone geometry, ligamentous and muscle anatomy and location.

However, most of the human joints have fundamental range of motion. For example, knee and elbow and the joints of the fingers (interphalangeal) with exception of thumb move in one axis only. In the knee joint, a round on flat articulation of tibia on femur is constrained by ligamentous attachments, to produce a predominantly uniaxial motion in flexion and extension. This seemingly uni-axial motion is also accompanied by rotations at end of the extension guided by the bony anatomy and ligamentous attachments. Therefore, the flexion-extension movement of the knee is a considered as a complex movement. However, there are joints which have more than a single axis of motion. For example shoulder, hip, and spine which are a series of joints linked together. It is difficult to measure the range of motion of the hip in a posture such as sitting cross legged which needs movements like abduction, external rotation and the flexion using conventional systems. Further, the range of motion of the shoulder, hip, and spine is non-planar, exists in all three fundamental body axes and, does not have a single or fixed axis of rotation. Further, pain and deformities might distort the axis to larger extent. In other words, the shoulder is a joint which is less constrained and has a multi axial range of motion in the planes of the flexion-extension, abduction-adduction, internal and external rotation as well as combined movements like circumduction.

Conventional systems and methods fail to provide accurate multi-axis complex range of motion measurements for clinical use. The proposed method and system provide a sensor based wearable fabric design for identifying distortion in movements and quantifying range of motion by using fiber optic grating technology. The wearable fabric is designed as a plurality of honey-comb structures comprising a plurality of adjacently placed hexagon structures with an optical sensor unit placed on each side of the hexagon structures. The optical sensor unit comprises a coherent light source, a Fiber Bragg Grating (FBG), a photo detector, and a transmitter <NUM>. The present disclosure exploits property of the FBG to cause frequency shift in a received light signal and a transmitted light signal which is further used to identify distortion in movement patterns of a subject. The identified distortion is further used to quantify range of motion of the movement patterns of the subject.

<FIG> illustrates a functional block diagram of a system <NUM> having a wearable fabric <NUM> for identifying distortion in movements and quantifying range of motion according to some embodiments of the present disclosure. The system <NUM> includes or is otherwise in communication with one or more hardware processors such as a centralized unit <NUM>, a wearable fabric <NUM>, a display unit <NUM>, one or more data storage devices <NUM> operatively coupled to the centralized unit <NUM>, and a data repository <NUM>. The centralized unit <NUM>, one or more components of the wearable fabric <NUM>, the display unit <NUM>, and the one or more data storage devices <NUM>, may be coupled by a system bus (not shown in <FIG>).

<FIG> is a functional block diagram of the wearable fabric <NUM> of <FIG> for identifying distortion in movements and quantifying range of motion according to some embodiments of the present disclosure. The wearable fabric <NUM> comprises a plurality of honey-comb structures, wherein each of the honey-comb structure comprising a plurality of adjacently placed hexagon structures. Each hexagon structure of each honey-comb structure comprises a plurality of optical sensor units <NUM> with each optical sensor unit placed on each side of the hexagon structure, at least a computation unit <NUM>, and at least a memory <NUM>. <FIG> is a schematic planar view of the sensor based wearable fabric design for identifying distortion in movements and quantifying range of motion in accordance with some embodiments of the present disclosure. The wearable fabric <NUM> comprises a plurality of honey-comb structures and each honey-comb structure comprises a plurality of adjacently placed hexagon structures as shown in <FIG>. As can be seen in <FIG>, each side of each hexagon structure is represented by a, b, c, d, e, and f respectively. Each optical sensor unit from the plurality of optical sensor units <NUM> is placed on each side of hexagon structures comprised in the plurality of plurality of honey-comb structures. The diagonals of each of the hexagon structure shown in <FIG> are used to provide support to each hexagon structure of the wearable fabric <NUM> and may be made up of textile fibre strands such as cotton, lycra, and the like. In an embodiment, design of the wearable fabric <NUM> is analogous to hexagonal closed packing (HCP) structures of solid state lattices, which proves to have highest 3D space efficiency so this wearable fabric <NUM> can be extended to 3D structures. In an embodiment, planar lattice structure of the wearable fabric <NUM> is also similar to that of graphite molecule which makes it a porous, breathable, better form fitting and comfortable garment.

The computation unit <NUM> of the wearable fabric <NUM> is configured to detect a deformation of a plurality of sides, wherein the plurality of sides corresponds to (i) one hexagon structure or (ii) at least two hexagon structures. In an embodiment, the computation unit <NUM> can be implemented as a stand-alone unit within the wearable fabric <NUM> but separated from the optical sensor units <NUM>. In the arrangement where the computation unit <NUM> is separated from the optical sensor units <NUM>, there is a possibility that each hexagon structure may have only one computation unit or each honey-comb structure may have only one computation unit. In another embodiment, the computation unit <NUM> may be a part of optical sensor units <NUM> placed on each side of the hexagon structures. In such cases, each side of each hexagon structure may have a computation unit.

In an embodiment, components of optical sensor unit <NUM> can be incorporated into woven fabrics. <FIG> illustrates a single knit element of the sensor based wearable fabric design for identifying distortion in movements and quantifying range of motion in accordance with some embodiments of the present disclosure. As can be seen from <FIG>, the optical sensor units are placed on each side of the hexagon structures. The optical sensor unit <NUM> may include but not limited to a coherent light source, a Fiber Bragg Grating (FBG), a photo detector, and a transmitter (not shown in <FIG>). In an embodiment, the coherent light source provides an input light signal of narrow wavelength (say <NUM>-<NUM> nanometer). The coherent light source may include but not limited to sun, candle, lamp, laser, bulb, super luminescent diode (SLD), and the like. The Fiber Bragg Grating (FBG) is a splitter which reflect a part of light input signal provided by the coherent light source and a difference of the input light signal incident on the FBG and reflected light signal by the FBG is determined and the difference is further transmitted to a photo detector. The photo detector is used to detect intensity of the light signal transmitted by the FBG. In an embodiment, intensity of detected light signal is a function of rotation of each of the optical sensor unit <NUM>. In another embodiment, rotation experienced by each of the optical sensor unit <NUM> as a result of movement of one or more body parts of a subject is measured based on the percentage of detected light signal. The photo detector may include but not limited to photo diodes, photo transmitters, and the like. The transmitter <NUM> comprised in each of the optical sensor unit <NUM> transmits information related to the detected deformation of the plurality of sides of each of the hexagon structure to the centralized unit <NUM>. In an embodiment, each optical sensor unit <NUM> is assigned a unique id represented as <NUM> hexadecimal (base-<NUM>) digits, such as '123e4567-e89b-12d3-a456-<NUM>'.

The memory <NUM> of the wearable fabric <NUM> stores the detected deformation of the plurality of sides of each of the hexagon structure. In an embodiment, the memory <NUM> can be implemented as a stand-alone unit within the wearable fabric <NUM> separated from the optical sensor units <NUM>. In the arrangement where the memory <NUM> is separated from the optical sensor units <NUM>, there is a possibility that each hexagon structure may have only one memory or each honey-comb structure may have only one memory. In another embodiment, the memory <NUM> may be a part of optical sensor units <NUM> placed on each side of the hexagon structures. In such cases, each side of each hexagon structure may have a memory.

The computation unit <NUM> of the wearable fabric <NUM> and the centralized unit <NUM> of the system <NUM> may be one or more software processing modules and/or hardware processors. In an embodiment, the hardware processors can be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and/or any devices that manipulate signals based on operational instructions. Among other capabilities, the centralized unit <NUM> is configured to fetch and execute computer-readable instructions stored in the one or more data storage devices <NUM>. The centralized unit <NUM> may include routines, programs, objects, components, data structures, and so on, which perform particular tasks or implement particular abstract data types.

In an embodiment, the centralized unit <NUM> may be implemented as stand-alone unit separated from the wearable fabric <NUM>. In another embodiment, the centralized unit <NUM> may be an integral part of the wearable fabric <NUM>. In arrangements where the centralized unit <NUM> is separated from the wearable fabric <NUM>, the centralized unit <NUM> may communicate with wearable fabric <NUM> through a wired or wireless communications medium. Wired communication mediums may include but not limited to Ethernet, serial, analog wires, universal serial bus (USB), and inter-IC bus (I2C). Wireless communications mediums may be implemented using wireless local area network protocols, protocols for other short-range wireless communication links. In an embodiment, the centralized unit <NUM> can be implemented in a variety of computing systems, such as laptop computers, notebooks, hand-held devices, edge devices, on-board devices, workstations, mainframe computers, servers, a network cloud and the like.

The memory <NUM> comprised in the wearable fabric <NUM> and the one or more data storage devices <NUM> of the system <NUM> may include any computer-readable medium known in the art including, for example, volatile memory, such as static random access memory (SRAM) and dynamic random access memory (DRAM), and/or non-volatile memory, such as read-only memory (ROM), erasable programmable ROM, flash memories, hard disks, optical disks, and magnetic tapes.

The data repository <NUM>, amongst other things, includes a system database and other data. The other data may include data generated as a result of the execution of the centralized unit <NUM> and the computation unit <NUM> involved in techniques that are described herein. The system database stores data processed, received, and generated by centralized unit <NUM> and the computation unit <NUM> which includes data received from the optical sensor units <NUM>, information transmitted to the centralized unit <NUM>, deformation detected by the computation unit <NUM>, signature of movement patterns and corresponding output which are generated as a result of the execution of the centralized unit <NUM> and the computation unit <NUM>.

The display unit <NUM> of the wearable fabric <NUM> may include an electronic device such as a television, computer, laptop, portable devices like a wrist watch device, a pendant device, a cellphone, a media player, a gaming device, a navigation device, and health care equipment or other electronic equipment. In an embodiment, the display unit <NUM> may be used to analyze or monitor condition of a patient and provide an alert to the patient by displaying one or more parameters related to movement of one or more body parts of a subject. For example, in case of a person undergoing orthopedic surgery, intensity of pain can be determined by the wearable fabric <NUM> based on identified distortion in movement of one or more body parts of the subject. This detail can be sent to the display unit <NUM> to alert the patient. In a non-limiting example embodiment, the display unit <NUM> can be used in a gym for determining fitness condition of the subject under consideration and providing an alert to the subject regarding one or more fitness parameters. For example, the display unit <NUM> may provide alert regarding type of exercises which should not be performed by the subject due to distortion or likelihood of distortion in movements of one or more body parts of the subject.

In an embodiment, the centralized unit <NUM> of the system <NUM> can be configured to identify distortion in movements and quantifying range of motion using sensor based wearable fabric design. Identification of distortion in movements and quantification of range of motion using sensor based wearable fabric design can be carried out by using methodology, described in conjunction with <FIG> and use case examples.

<FIG> is a flow diagram illustrating a method <NUM>, implemented by the system <NUM> of <FIG> for identifying distortion in movement patterns of a subject, in accordance with some embodiments of the present disclosure.

In an embodiment, the system <NUM> comprises one or more data storage devices <NUM> or the memory <NUM> operatively coupled to the centralized unit <NUM> or the computation unit <NUM> and is configured to store instructions for execution of steps of the method <NUM> by the centralized unit <NUM> or the computation unit <NUM>. The steps of the method <NUM> of the present disclosure will now be explained with reference to the components of the system <NUM> and the wearable fabric <NUM> as depicted in <FIG> and <FIG> and the steps of flow diagram as depicted in <FIG>. Although process steps, method steps, techniques or the like may be described in a sequential order, such processes, methods and techniques may be configured to work in alternate orders. In other words, any sequence or order of steps that may be described does not necessarily indicate a requirement that the steps be performed in that order. The steps of processes described herein may be performed in any order practical. Further, some steps may be performed simultaneously.

Referring to <FIG>, at step <NUM>, the computation unit <NUM> is configured to detect deformation of a plurality of sides in the wearable fabric <NUM> worn by the subject. As depicted in <FIG>, the wearable fabric <NUM> comprises a plurality of honey-comb structure with each honey-comb comprising a plurality of adjacently placed hexagon structures. Here, each hexagon structure comprising a plurality of optical sensor units with each optical sensor unit placed on each side of the hexagon structure. In other words, each side of each hexagon structure is representative of optical sensor unit <NUM>. Thus, deformation of a side represents rotation of an optical sensor unit by an angle. In an embodiment, the rotation of optical sensor unit is caused due to abnormalities in the movement patterns of one or more body parts of a subject. In an embodiment, said abnormalities may be generated as a result of a surgery, pain, excessive exercise, and the like. As shown in <FIG>, the optical sensor unit comprises a coherent light source, a FBG grating and a photo detector. In an embodiment, the optical sensor unit can be implemented as interferometry fiber optic (FO) gyroscopes. The interferometry fiber optic (FO) gyroscopes are inertial sensors that yield highly accurate absolute position and rotation information by virtue of the principle of Sagnac interferometry wherein two counter-propagating waves experience a differential phase delay. This differential phase delay can be very small, so interferometric methods are used to detect (and quantify) it. This differential phase delay is directly proportional to change in rotation angle of the interferometry fiber optic (FO) gyroscopes. Thus, by considering the optical sensor units <NUM> to be functioning as interferometry fiber optic (FO) gyroscopes, change in angle of rotation of optical sensor units <NUM> can be determined. This change in the angle of rotation is hereby referred as angle of deformation of the side of the hexagon structure. In an embodiment, principle of Sagnac interferometry is explained with the help of <FIG>.

<FIG> is a diagram illustrating working of Fibre Bragg Grating (FBG) for identifying distortion in movements and quantifying range of motion in accordance with some embodiments of the present disclosure. As can be seen in <FIG>, the FBG comprised in the optical sensor unit <NUM> receives a light signal from the coherent light source. The FBG is a device that is essentially built into a strand of optical fiber. The Fiber Bragg Gratings (FBGs) are made by laterally exposing core of a single-mode optical fiber to a periodic pattern of light signal received from an intense coherence light source (say laser light). The exposure produces a permanent increase in refractive index of the optical fiber's core, creating a fixed index modulation according to exposure pattern. This fixed index modulation is called a grating. In other words, the FBG has to contain alternating periods of high and low refractive index regions, like a grating. Essentially, if light of a finite bandwidth is sent into the FBG, a part of input spectrum, which corresponds to a Bragg reflection condition is reflected back and transmitted spectrum (which represents light detected at the output) contains all wavelengths minus those that were reflected back. At each periodic refraction change a small amount of light signal falling on the FBG is reflected. All the reflected light signals combine coherently to one large reflection at a particular wavelength when grating period is approximately half the received light signal's wavelength. This is referred to as the Bragg reflection condition, and the wavelength at which this reflection occurs is called Bragg wavelength. Light signals at wavelengths other than the Bragg wavelength, which are not phase matched, are essentially transparent. Therefore, received light signal propagates through the FBG with negligible attenuation or signal variation. Only those wavelengths that satisfy the Bragg reflection condition are affected and strongly back-reflected. The ability to accurately preset and maintain the grating wavelength is a fundamental feature and advantage of fiber Bragg gratings (FBGs). In an embodiment, central wavelength of reflected light signal component satisfies a Bragg relation: λBragg = nv , wherein n depicts the index of refraction and v depicts period of index of refraction variation of the FBG. Further, parameters n and v are dependent on temperature and strain, so the wavelength of the reflected light component also changes as function of temperature and/or strain. This dependency allows determining the temperature or strain from the wavelength of the reflected light component. Thus, in the present disclosure, some part of the light signal received by the FBG from the coherent light source is reflected and remaining part of the received light signal is transmitted to the photo detector. Further, the photo detector determines intensity of the detected light which is used as a measure of rotation of the optical sensor unit <NUM>. In an embodiment, deformation of the plurality of sides is determined based on a difference in frequency of received light signal and reflected light signal by the FBG. In another embodiment, the FBG is based on shift in frequency of incident light that falls on a fringe grating due to the change in the angle of rotation of the optical sensor units <NUM>. If the original frequency due to interference between incident light source and the fringe pattern is f, which is pre-known by design, and the change in the angle of rotation of the optical sensor unit <NUM> by ϕ causes a shift to frequency f' as δf = f - f', then ϕ is provided as shown in equation (<NUM>) below: <MAT> Here, a and b are coefficients learnt through a least square estimation method, performing experiments where ϕ is known. So <MAT> gives optimum values of a and b.

In an embodiment, the plurality of sides detected with deformation may correspond to (i) one hexagon structure or (ii) at least two hexagon structures. This can be explained with the help of <FIG> illustrate different possible ways of deformation in the sides of hexagon structures comprised in the sensor based wearable fabric design in accordance with some embodiments of the present disclosure. The deformation of side may have a uniform form (e.g. straight line) or non-uniform form (e.g., curved lines, spiral lines, and the like). In case of non-uniform deformation, the angle of deformation is determined based on the stress or strain, where said stress /strain are determined from the wavelength of the reflected light component by FBG. As can be seen in <FIG> and <FIG> (Here, 7B is providing clear representation of deformed side shown in <FIG>), only one side (here side a) of one hexagon structure (hexagon <NUM>) is deformed, wherein the deformation of side is non-uniform. Dotted line shown in <FIG> and <FIG> represents deformed side. Similarly, in <FIG> and <FIG> (Here, 7D is providing clear representation of deformed side shown in <FIG>), only one side (here side a) of one hexagon structure (hexagon <NUM>) is deformed by an angle of deformation(θ), wherein the deformation of side is uniform. In an embodiment, the uniform deformation of sides may result in alteration in the length of adjacent side of the deformed side (e.g. length of side 'f' of hexagon <NUM> is reduced in <FIG> and <FIG>).

Further, there is possibility of deformation of one side of many hexagon structures or many sides of one hexagon structure. Also, the deformed side of one hexagon structure may be same as the deformed side of other hexagon structures or different. <FIG> and <FIG> (Here, 7F is providing clear representation of deformed side shown in <FIG>) show non-uniform deformation of one side of many hexagon structures. As can be seen in <FIG> and <FIG>, side 'a' of hexagon <NUM> is deformed. However, in hexagon <NUM>, hexagon <NUM>, and hexagon <NUM>, the deformed sides are side 'b', side 'f', and side 'e' respectively instead of side 'a'. Similarly, <FIG>and <FIG> (Here, <NUM> is providing clear representation of deformed side shown in <FIG>) show uniform deformation of one side of many hexagon structures. For example, as depicted in <FIG> and <FIG>, same side 'a' of hexagon <NUM>, hexagon <NUM>, and hexagon <NUM> is deformed with same angle of deformation (θ). However, <FIG> and <FIG> (Here, 7J is providing clear representation of deformed side shown in <FIG>) show uniform deformation of one side of many hexagon structures, wherein angle of deformation of deformed sides is different for different hexagons. As can be seen in <FIG> and <FIG>, the same side 'a' of hexagon <NUM>, hexagon <NUM>, and hexagon <NUM> is deformed, but with different angle of deformations (say θ<NUM>, θ<NUM>, and θ<NUM> respectively). Furthermore, <FIG> and <FIG> (Here, <NUM> is providing clear representation of deformed side shown in <FIG>) show deformation of many sides of one hexagon structure, wherein the deformation of sides is non-uniform. For example, as depicted in <NUM> and <FIG>, side 'a', side 'b' , and side 'c' of hexagon <NUM> only are deformed.

In an embodiment, each optical sensor unit <NUM> comprised in the wearable fabric <NUM> is assigned a sensor ID. Each optical sensor unit <NUM> provides value of the angle of rotation by which it has gotten rotated along with the corresponding sensor ID. This information is saved in the memory <NUM> comprised in the wearable fabric <NUM> and transmitted by the transmitter <NUM> comprised in the optical sensor unit <NUM> to the centralized unit <NUM> using wired or wireless transmission.

Referring back to <FIG>, at step <NUM>, the centralized unit <NUM> is configured to generate signatures for movement patterns of one or more parts of body of the subject in accordance with the detected deformation. The centralized unit <NUM> aggregates the transmitted information related to the detected deformation of the plurality of sides to generate a signature of a specific movement pattern (alternatively referred as unified ROM signature). In an embodiment, there could be different movement patterns of one part of body of the subject. <FIG> show illustrative examples of movement patterns of the subject in accordance with some embodiments of the present disclosure. As can be seen in <FIG>, different movement patterns of human shoulder are provided. The movement patterns of human shoulder may include forward movements which includes but not limited to flexion, extension, neutral, abduction, rotation in abduction, rotation in neutral, elevation, and the like. Here, the range of motion of above-mentioned forward movements is determined based on direction of the range of motion which may vary from <NUM> degrees for neutral to <NUM> degrees for elevation. Further, signatures of flexion, extension, neutral, abduction, rotation in abduction, rotation in neutral, and elevation could be different for same body part (in this case, human shoulder).

Further, as depicted in step <NUM> of <FIG>, the centralized unit <NUM> is configured to compare, the generated signatures with stored signatures of movement patterns of the one or more parts of body of the subject. In an embodiment, the generated signature of the specific movement pattern is used to construct a trajectory. As an example, it is assumed that for a specific movement pattern A, the stored signature is S. However, for a patient wearing the wearable fabric <NUM>, the generated signature of same movement pattern A becomes <NUM>'. Further, using the generated signature S', a trajectory A' is constructed and a trajectory matching algorithm between A and A' is performed. In an embodiment, a method for trajectory matching involves making both trajectories piece-wise linear using multi-layer perceptron (MLP) and then fit subsequent lines to calculate square of the errors on fitting. So, <MAT> Where, <MAT> and Li = ith line approximation from movement pattern, wherein line approximations are by the movement pattern A as provided in equation <NUM> below as: <MAT> Here, L represents linear approximation of the trajectory and E represents error between actual and expected trajectory. L and E are measure of abnormality. In an embodiment, the step of comparing the generated signature with stored signatures of movement patterns of the one or more parts of body of the subject may involve a one to one mapping or one to many mapping. The one to one mapping refers to comparing the generated signatures of movement patterns of one body part to the stored signatures of same body part. For example, if a signature is generated for knee movement, then the generated signature must be mapped with the stored signature of knee movements only in case of one to one mapping. To achieve one to one mapping, a classification or categorization of movement patterns belonging to different body parts may be required. For example, all the movement patterns related to shoulder should be categorized as class <NUM>, movement patterns related to knee as class <NUM>, and the like. However, the one to many mapping refers to comparing the generated signatures of movement patterns of one body part to the stored signature of all body parts. For example, in accordance with one to many mapping even if a signature is generated for a specific movement pattern of knee, the generated signature is mapped with the stored signatures of movement patterns of all the body parts such as shoulder, ankle, elbow, spine, and the like.

Further, as depicted in step <NUM> of <FIG>, the centralized unit <NUM> is configured to determine, an error indicative of distortion in the movement patterns of the one or more parts of body of the subject in accordance with a difference between the generated signatures and the stored signatures. In an embodiment, the error indicative of distortion is used to quantify the range of motion of the movement patterns of the one or more body parts of the subject. The error indicative of distortion captures change in direction of the range of motion of the one or more body parts. For example, it is assumed that the direction of the range of motion for different movement patterns of knee of a person in normal condition are <NUM> degrees for hyperextension which may vary to <NUM> degrees for flexion. However, in a patient affected with arthritis, the direction of range of motion decreases and could be recorded as <NUM> degrees for hyperextension and <NUM> degrees for flexion providing an effective arc of only <NUM> degrees. In an embodiment, the centralized unit <NUM> is further configured to provide an alert when the error indicative of distortion exceeds a pre-defined threshold, wherein the alert is displayed in at least one of an electronic device handled by the subject. The pre-defined threshold represents an objectively defined value which is assigned as a part of clinical examination of every joint. This can be extended to recording range of motion in the rehabilitation process as well as post-surgical recovery of practically any joint where restoration of range is essential for restoration of function and relief from disability and pain. In an embodiment, the alert could be a text message, an image, a video providing the details of the distortion. The details of distortion may include severity of distortion, status, corrective actions to be taken. In other words, the generated signatures of movement patterns are compared with stored signatures of normal movement patterns to understand abnormal movement patterns based on clinician decided thresholds and may provide output to a treating physician to understand how the patient is affected by a problem or disease.

In an embodiment, illustrative articles of clothing woven using the wearable fabric <NUM> are discussed. <FIG> show illustrative examples of articles which can be made using the sensor based wearable fabric design for identifying distortion in movements and quantifying range of motion accordance with some embodiments of the present disclosure. The wearable fabric <NUM> may be used but not limited to form a smart t-shirt or vest, smart arm band, smart shorts, smart socks, smart watch band, and smart gloves as shown in <FIG>, <FIG> respectively. In an embodiment, the wearable fabric <NUM> may be completely woven into the clothing article. In another embodiment, the wearable fabric <NUM> may be woven to be a part of the clothing article. The smart t-shirt or vest can be used to determine shoulder range of motion (ROM), back ROM, thoracic and lumbar range, deformity and posture. In an embodiment, inference of possible defects in posture can be derived by observing signatures of movement patterns while sitting and standing. The smart shorts can be used to study hip movements, trend recovery patterns for patients who have undergone replacement surgeries, and hip reconstruction surgeries. The smart arm band or a knee brace is useful for study of recovery after knee injuries, arthritis patient monitoring and also therapy of patients who have undergone knee replacement surgeries. Similarly, the smart socks or ankle braces can be used to monitor ankle joints and foot deformities. In an embodiment, smart watch band as shown in <FIG> or a smart glove shown in <FIG> are used to monitor wrist movements. The smart watch band can also be used as a smart watch to work as a display unit for showing the details of the alert sent by the centralized unit <NUM>. However, <FIG> are only illustrative and the wearable fabric <NUM> may be used in forming any suitable article of clothing on intended joint/joints which are to be monitored.

The scope of the subject matter embodiments is defined by the claims.

Claim 1:
A system comprising a wearable fabric (<NUM>) and a centralized unit (<NUM>), the wearable fabric (<NUM>) comprising:
a plurality of honey-comb structures, wherein each of the honey-comb structure comprising a plurality of adjacently placed hexagon structures,
wherein each hexagon structure comprising a plurality of optical sensor units with each optical sensor unit placed on each side of the hexagon structure,
wherein each of the optical sensor unit (<NUM>) includes:
a coherent light source, configured to provide input light signal of narrow wavelength,
a Fiber Bragg Grating (FBG) sensor, configured to reflect a part of original input light signal and transmitting a difference of original and reflected input light signal,
a photo detector, configured to receive and detect intensity of the transmitted input light signal, and
a transmitter;
at least a computation unit (<NUM>) configured to detect a deformation of a plurality of sides, wherein the plurality of sides corresponds to (i) one hexagon structure or (ii) at least two hexagon structures;
wherein the transmitter is configured to transmit information related to the detected deformation to the centralized unit,
wherein the centralized unit is configured to:
receive, the transmitted information related to the detected deformation;
generate signatures of movement patterns of one or more parts of body of a subject in accordance with the detected deformation;
compare, the generated signatures with stored signatures of movement patterns of the one or more parts of body of the subject; and
determine an error indicative of distortion in the movement patterns of the one or more parts of body of the subject in accordance with a difference between the generated signatures and the stored signatures; and
at least a memory (<NUM>) to store the detected deformation of the plurality of sides.