Dynamic prescription of individualised postural equipment

Abstract

A computer-implemented method for dynamic prescription of individualised postural equipment, comprises receiving, via at least a first user interface component, input data from a user, the input data specifying elements of a body shape of a human subject, generating a 3D subject model of the body of the human subject based on the input data, causing an electronic display to display the 3D subject model positioned relative to a 3D postural equipment model of a postural equipment prescription for the human subject intended to support the subject when implemented in postural equipment, to thereby enable the user to visualise a relationship between the 3D subject model and the 3D postural equipment model, receiving, via at least a second user interface component, modification data in respect of at least one of the 3D subject model and the 3D postural equipment model, updating at least one of the 3D subject model and the 3D postural equipment model based on the modification data, causing the electronic display to display the updated at least one of the 3D subject model and the 3D postural equipment model, and outputting postural equipment prescription data in response to a user command, the prescription data enabling production of postural equipment corresponding to the 3D postural equipment model.

Description

[0001] DYNAMIC PRESCRIPTION OF INDIVIDUALISED POSTURAL EQUIPMENT Field of the Technology The present invention relates to a method, a computer program, and system for prescription of individualised seating. Background to the Technology Generating individualised postural equipment such as seating for a chair, e.g. for a wheelchair, for individuals with complex postural needs is a challenging process. One common process involves a specialist medical professional taking measurements of the subject and prescribing the seating based on the measurements and other issues such as areas where the subject experiences pain and the medical professional’s assessment of the subject’s ability to adapt to new seating positions. A follow-up assessment may also be required where the user's shape is captured using a mould or a 3D body scan. In such cases, the initial prescription often needs to be revised as there may be conflicting information. As such, because the subjects often have complex postural issues, a common outcome of this process is that the prescribed seating does not fit the subject as intended. Where the ordered seating allows, adjustments may be made to improve the fit, however, in practice the process of making adjustments is often a highly iterative and time-consuming process, particularly where the medical professional needs to order alternative components. This process to prescribe a custom seating system typically results in 3 or more visits. Where one or more components of the ordered seating does not allow for adjustment, the end result may be that the subject is provided with sub-optimal equipment. Object of the Technology It is an object of the technology to provide at least one aid for prescribing individualised seating. Alternatively, it is an object of the technology to at least provide the public with a useful choice. Summary of the Technology According to one aspect of the technology there is provided a computer-implemented method for dynamic prescription of individualised postural equipment, comprising receiving, via at least a first user interface component, input data from a user, the input data specifying elements of a body shape of a human subject; generating a 3D subject model of the body of the human subject based on the input data; causing an electronic display to display the 3D subject model positioned relative to a 3D postural equipment model of a postural equipment prescription for the human subject intended to support the subject when implemented in postural equipment, to thereby enable the user to visualise a relationship between the 3D subject model and the 3D postural equipment model; receiving, via at least a second user interface component, modification data in respect of at least one of the 3D subject model and the 3D postural equipment model, updating at least one of the 3D subject model and the 3D postural equipment model based on the modification data, causing the electronic display to display the updated at least one of the 3D subject model and the 3D postural equipment model; and outputting postural equipment prescription data in response to a user command, the prescription data enabling production of postural equipment corresponding to the 3D postural equipment model. In an embodiment, the method further comprises repeatedly iterating through the steps of updating the at least one of the 3D subject model and the 3D postural equipment model based on the modification data, and causing the electronic display to display the updated at least one of the 3D subject model and the 3D postural equipment model, each time modification data is received. In an embodiment, the method comprises generating the 3D postural equipment from the prescription data. In an embodiment, receiving modification data in respect of the 3D postural equipment model comprises receiving a modification of the prescription data. In an embodiment, the method further comprises processing the input data to make at least one recommendation for at least one component of the postural equipment. In an embodiment, the input data further comprises postural equipment data corresponding to at least one of a current or proposed postural equipment for the subject. In an embodiment, generating the 3D subject model comprises modifying a 3D base skeleton model by scaling the skeleton model based on measurements of the subject included in the input data. In an embodiment, the 3D base skeleton model includes a plurality of nodes defining the positions of bones of the 3D base skeleton model, and generating the 3D subject model comprises adjusting a position of at least one of the plurality of nodes based on measurements of the subject included in the input data. In an embodiment, receiving modification data comprises receiving an input adjusting an angle of the at least one bone of the 3D subject model. In an embodiment, the method comprises, after generating the 3D subject model of the body of the human subject based on the input data, causing the electronic display to display the 3D subject model to enable the user to make adjustments to the 3D subject model and / or input additional data specifying further elements of the body shape of the human subject prior to the 3D model being displayed in conjunction with the 3D seating model. In an embodiment, the postural equipment is a seating apparatus. In a second aspect of the technology, there is provided a computer program comprising instructions which when executed cause one or more processors to carry out the above method. In a third aspect of the technology, there is provided a tangible computer-readable medium comprising the computer program. In a fourth aspect of the technology, there is provided system for dynamic prescription of individualised postural equipment comprising: at least a first user interface component for receiving input data from a user, specifying elements of a body shape of a human subject; a 3D modelling engine for: generating a 3D subject model of the body of the human subject based on the input data; and causing an electronic display to 3D subject model positioned relative to a 3D postural equipment model of a postural equipment prescription for the human subject intended to support the subject when implemented in in postural equipment, to thereby enable the user to visualise a relationship between the 3D subject model and the 3D postural equipment model; at least a second user interface component for receiving modification data in respect of at least one of the 3D subject model and the 3D postural equipment model, whereafter the 3D modelling engine updates at least one of the 3D subject model and the 3D postural equipment model based on the modification data, and causes the electronic display to display the updated at least one of the 3D subject model and the 3D s postural equipment model; and a prescription output component for outputting prescription data in response to a user command, the prescription data enabling production of postural equipment corresponding to the 3D postural equipment model. In a fifth aspect of the technology, there is provided computer-implemented method for dynamic prescription of individualised postural equipment, comprising receiving, via at least a first user interface component, input data from a user, the input data specifying elements of a body shape of a human subject; generating a 3D postural equipment model of a postural equipment prescription for the human subject intended to support the subject when implemented in postural equipment based on the input data; causing an electronic display to display the 3D postural equipment model to thereby enable the user to visualise the 3D postural equipment model; receiving, via at least a second user interface component, modification data in respect of the 3D postural equipment model, updating the 3D postural equipment model based on the modification data, causing the electronic display to display the updated a 3D postural equipment model; and outputting postural prescription data in response to a user command, the prescription data enabling production of postural equipment corresponding to the 3D postural equipment model. Further aspects of the technology, which should be considered in all its novel aspects, will become apparent to those skilled in the art upon reading of the following description which provides at least one example of a practical application of the technology. Brief Description of the Drawings One or more embodiments of the technology will be described below by way of example only, and without intending to be limiting, with reference to the following drawings, in which: Figure 1 shows a block diagram of the computing components of an example system. Figure 2 is an example user interface. Figure 3 and Figure 4 are example visual guides to gathering information. Figures 5 to 8 are further example user interfaces. Figures 9 and 10 illustrate data entry being reflected in an updated 3D model. Figures 11 to 14 illustrate a back support algorithm of an embodiment. Figure 15 shows an example of a cushion support generated by a cushion support algorithm. Figures 16A to 16C illustrate determining the dimension of thigh supports. Figures 17A to 17C illustrate determining a cushion cut-out. Figures 18A and 18D illustrate determining a cushion modification to accommodate a difference in thigh angle. Figures 19 to 22 are further example user interfaces. Brief Description of Exemplary Forms of the Technology 1.1. Overview Embodiments of the technology provide a system 100 that implements a computer-implemented method for generating a dynamic prescription for postural equipment. Postural equipment includes: seating apparatus such as postural support devices, wheelchair seating, mobility device seating and other seats; standing apparatus such as a standing frame, standing aid, and postural support; and lying apparatus such as night-time positioning equipment, and a sleep system. The technology is described below in relation to seating and particularly wheelchair seating. In an examples of the technology, computer processors of the system (e.g. of the servers described below) execute program code to carry out the method. The technology includes a user interface for capturing measurements of a subject to be provided with individualised seating, such as an individualised wheelchair. The technology incorporates a 3D modelling engine for generating a three-dimensional virtual model of the subject based on the measurements, which can be viewed while finalising measurements of the subject. The technology also includes a recommendation module for suggesting components of the seating from which a user (generally, a specialist medical professional) can generate a seating prescription that suits the subject’s specific postural support needs. The technology enables the user to view the 3D virtual model of the subject in a same visualisation as a 3D model of the prescribed seating. The technology enables the user to alter the prescription based on the visualisation and / or determine whether the subject’s posture can adapt to the prescribed seating. In this way, the subject’s seating prescription can be altered with reference to the virtual model until a more suitable prescription is generated. The technology therefore allows for faster, easier, and more cost-effective modifications of the prescription, and also allows for the ability to create a more suitable prescription for each individual subject. 1.2. System Architecture An example block diagram of a system 100 for implementing the technology is illustrated in FIG.1. In FIG.1, the client 130 is the end-user's device, such as a web browser running on a user’s computing device, a mobile application, or any other application interface. The frontend 120 is the user interface of the web application. It includes functional modules 122 for rendering user interface components as needed on the client, and handling user interactions. The frontend 120 fetches geographical information (e.g. from the Google Map API 185) for localization or to provide location-specific content, retrieves translations (e.g. from the Google Translate API 155) for the user interface to support multiple languages or localization, and handles user authentication and authorization processes (e.g. using the AWS Cognito API 150). The frontend 120 also incorporates an API service 124 that serves as an intermediary between the frontend and the backend 110 and hence also handles communication between the client 130 and the backend 110. API service 124 also implements an access token service in which it fetches data from the backend based on user access tokens. The backend 110 of the application is responsible for processing requests, managing the application's core functionality, and interacting with various services. The NGINX (frontend server) 111 acts as a web server and reverse proxy, routing user requests and serving frontend application files. The business logic layer (Node.js API with Nest.js) 116 is responsible for implementing the core business logic and functionality of the application. It includes various functional modules 117 for different tasks. The functional modules 117 include a 3D modelling engine for generating 3D models of subjects and seating as described in further detail below. Functional modules 117 also include a recommendation module, that implements logic for recommending seating components based on the subject’s MAT assessment as described further below. Other modules: handle user authentication, authorization, and user data import; manage the storage and retrieval of files; generate and send quotations to users; provide translations for the frontend; fetch product data; import user data; manage file downloads from an AWS bucket 190; detect country by IP address using a third-party IP geolocation service 170; quotation card generation, PDF and CSV generation, link saving management, email generation and sending using an external service 175 for sending emails or messages to users, files management, projects saving management, and authentication logic The system 100 also comprises a persistence layer 112 formed from AWS Aurora 113 (Amazon's managed relational database service) and a Postgres relational database 114 used to store and manage data. Databased store information describes the types of data stored in the database including product configurations, user data, and links to configurations. Other components include: Amazon Simple Storage Service (S3) 135 which is used for file storage, such as storing user-uploaded files or other data; AWS Cognito 150, a service for managing user identities and authentication; Dropbox API 180 used for file management and storage; Google Spreadsheets API 160 for working with Google Sheets or spreadsheets; Odoo API 165, an open- source business management software; AWS Lambda functions 140 which are serverless functions that can be triggered to perform specific tasks; and an AWS Gateway API 145 that provides an interface for external services or applications to interact with AWS Lambda functions. 1.3. User interface for capturing measurements Embodiments of the technology enable the user to complete a digital MAT (“Mechanical Assessment Tool”) Assessment for the subject. The following description, focusses on how the system 100 captures information related to the subject’s measurements, posture, biomechanical limitations, medical conditions, pain, etc. However, it will be appreciated that the system 100 also captures other information such as name, address, health fund, medical history, current seating product, etc. User interface comprises a number of user interface component parts for capturing data and displaying information to the user. Different parts of the user interface are displayed to the user depending on context such as what information is being gathered at a particular time. FIG.2 is an example user interface 200 showing some of the information that can be captured and shows that it includes user interface components 211-217 for capturing information as diverse as the subject’s home environment 211, transport needs 212, hand function 213, thermoregulation 214, level of seating needs 215, muscle tone 216, and whether or not they have a mobility device 217. Other information that can be captured includes information about weight, diagnosis, condition status, cognition, communication, challenging behaviour, medication, hearing, vision, respiration, sensation, history and / or risk of pressure injury, pressure relief, transfer method, nutrition intake, length of time on seating etc. FIG.3 is a visual guide 300 to measurements (A to N) to be captured by the user with the subject in a seated position. Similarly, FIG.4 is a visual guide to dimensions (R to T, and V to X) to be captured for a new mobility device. In some examples, the visual guides are displayed on the user interface while the user gathers measurements or can be accessed via a menu of the user interface. FIG.5 is an example of a user interface 500 comprising user interface components in the form of a plurality of fields for capturing elements of a body shape of a human subject, in this example measurements include: A – Top of the head (or maximum sitting height) 511; B – Shoulder height 512; D – Scapula height 513; C – Axilla height 514; L – Shoulder width 515; M – Chest width 516; J – Thigh depth 517; and N – Hip width 518. User interface 500 also includes a button 519 for causing the user interface to display additional fields for entering further measurements, here measurements E to K as shown in FIG.3 which may be needed to more accurately represent the body shape of some subjects. In this respect, E is Lumbar Height, F is Elbow Height, G is Lower Leg Length, H is Trunk Depth, I is Forearm Depth, J is Thigh Depth, and K is Foot Length. User interface 500 also comprises a plurality of fields for capturing mobility device measurements including: R – Frame width 521; S – Seat depth 522; T – Back post height 213; Drop down field 524 for selecting a mobility device; V – Seat Frame to Back Post Angle 525; W – Seat Frame to Front Frame Angle 526; X – Front Frame to Foot Support Angle 527; and Z – Wheelchair tilt 528. User interface 500 also includes radio buttons 539 for selected between wheelchair cane type. As explained in further detail below, the system 100 takes the entered data and generates a 3D model of the subject for display as part of the user interface in order to assist in visualisation in the next step of data capture which involves completing three MAT assessment forms. Advantageously, the 3D model of the subject is updated in response to the user entering data. Visual comparison of the 3D model to the actual subject can assist the user to correctly assess the subject. FIG.6 is an example user interface 600 of a first MAT assessment form for entering information related to other elements of a user’s body shape, in this example a subject’s posture in current seating. As shown in FIG.6, a 3D model of the subject 611 is displayed together with a series of expandable menus 621-627 enable a user to specify data about the subject’s pelvis 621, trunk 622, hip position 623, body segment angles 624, feet 625, head and neck 626, and upper limbs 627. FIG.7 is an example user interface 700 of a second MAT assessment form for entering details about a subject’s posture in a supine position. As shown in FIG.7, an adjusted 3D model of the subject 611A is displayed together with a subset of the series of expandable menus 621-627. FIG.8 is an example user interface 800 of a third MAT assessment form for entering a details about a subject’s posture in a sitting position on a plinth. As shown in FIG.8, an adjusted 3D model of the subject 611B is displayed together with the series of expandable menus 621-624 visible. User interface 800 also incorporates user interface element 820 that allows a user to select a balance option for the subject using a series of radio buttons corresponding to a hands- free sitter (i.e. a subject that can sit up unsupported), a hands-dependent sitter (i.e. a subject can sit up when using his or her hands as support), and a propped sitter (i.e. a subject that is unable to sit up without props for support). FIG.9 is another example of data being entered using user interface 800. In the example of FIG.9, the trunk menu 622 has been opened and the user operated a slider bar 931 to define a scoliosis level of 35 degrees severe convex left which is reflected in updated 3D model of the subject 611C. A graphic element 941 is overlaid on subject model 611C to assist the user in visualisation. Visual comparison of the subject to the model 611 with the graphic element 941 in place to the subject can assist the user to refine the values entered via the slider bar. FIG.10 is an example of further example of data being entered using user interface 800. In the example of FIG.10, the pelvis menu 621 has been opened and the user has operated a slider bar 1031 to define a pelvic obliquity angle of 13 degrees left which obliquity is reflected in updated 3D model of the subject 611D. Again, graphic element 942 is overlaid on subject model 611D to assist the user in visualisation. Once the user has finished the assessment process, they can output a MAT assessment report that is generated from the system via the user interface and / or proceed to the subsequent steps of generating a seating prescription as described in further detail below. 1.4. Subject Model A 3D modelling engine of the functional modules 117 of the system 100 implements a 3D body visualization algorithm to generate a virtual image of a subject's body in three dimensions (3D) based on the subject's body measurements. This process utilizes subject body measurements to replicate the body in 3D and incorporates a Body Mass Index (BMI) approach to calculate body mass distribution. The measurements obtained above encompass critical dimensions such as shoulder height, hip width, limb lengths, and other relevant anatomical measurements. These measurements serve as the foundation for creating a close to accurate representation of the subject's unique physique. When the subject's age, gender, and weight are entered into the user interface via the MAT Assessment system, the 3D body visualization algorithm uses this information to introduce age- specific, gender-specific, and weight-specific attributes to the 3D model. Using the collected body measurements, age, gender and weight the system 100 employs algorithms and mathematical modelling techniques to generate a digital 3D model that faithfully reflects the subject's body shape and proportions. Each measurement is utilized to create corresponding dimensions within the 3D model, ensuring that the replication is very precise. The system 100 goes beyond just replicating the external dimensions of the body. It recognizes the significance of body mass distribution for creating a holistic and realistic representation. To achieve this, the system 100 incorporates the Body Mass Index (BMI) approach as another element of specifying a body shape of the subject. BMI is a well-established metric used to assess body mass relative to height. The system 100 uses the subject's weight and height measurements to calculate the BMI. This BMI value is then utilized to estimate how body mass is distributed across the subject's 3D replicated model. By incorporating BMI-driven data, the system 100 adjusts the 3D body model's internal structure to distribute mass realistically, accounting for factors such as muscle distribution. This results in a more faithful representation of the subject's actual body composition, enhancing the accuracy of the 3D model. The realism introduced by accurate body measurements and BMI-driven body mass distribution allows the system 100 to provide more precise and personalized seating and mobility solution recommendations. As the system 100 suggests products (as described further below), it takes into consideration not onlysubject body dimensions and also calculated 3D body model dimension, resulting in seating solutions that are better tailored to the subject's needs. 1.4.1 Base model The process uses a base 3D body model which is a three-dimensional polygon mesh or shell, which consists of a set of vertices, edges and faces that define the shape of the displayed polygonal object. Information about its coordinates, normal vectors and coordinates of imposed textures - raster images used for color, relief illusion and model detailing are associated with a vertex. This mesh represented as a human body has some default measurements such as: height, length of arms and legs, feet, etc. In the 3D modelling engine, file processing and character customization based on input parameters, is implemented by “Three.js”. Three.js is a cross-browser JavaScript library used to create and display animated computer-generated 3D graphics when developing web applications. Three.js scripts can be used in conjunction with an HTML5 CANVAS, SVG or WebGL element. Once generated, 3D model is exported to the universal GLTF format. GLTF (GL Transmission Format) is a file format for storing 3D scenes and models that is extremely easy to understand (the structure is written in JSON standard), extensible and easily interoperable with modern web technologies. This format compresses 3D scenes effectively and minimizes runtime processing of applications using WebGL and other APIs. The 3D body model is resized using two methods: skeletal animation and morphing. 1.4.2 Skeletal animation method Skeletal animation methods are based on the use of a skeleton, which is defined as a hierarchical structure of bones. Each node of the structure has its own local coordinate system and three- dimensional transformation. Each bone occupies its place in the skeleton hierarchy and is influenced by other bones: each child bone inherits transformations of the parent bone. The arrangement of skeletal nodes that corresponds to the basic form of the model is called the binding pose. Usually changes in skeleton structure are solved in 3D models by replacing skeletons (i.e. by having a set of models, and choosing the one most appropriate for the subject( , but this solution is not suited to a complex use case where the skeletons of subjects are highly individual. For example, it is common for people with complex needs to have an asymmetric posture, which can be reflected in a diverse range of skeletal irregularities. To provide a functional way in which to generate a unique skeleton, embodiments of the technology are configured to change various parameters of the virtual 3D body by changing the structure of the virtual skeleton without changing the skeleton itself. In an example of the technology, this is used to change the body height, arm, leg, foot, and shoulder lengths. In an example, the dimensions A+J+G are used to approximate the height of the patient. In an example, the skeleton is scaled in proportion to the approximated height of the patient. In an example, a default height is used for the skeleton of 1760mm. Thus, if A+J+G was also 1760mm, the system 100 would calculate a skeleton scale of 1. Similarly, if A+J+G height is 1560mm skeleton scale is 0.89. All default body sizes are recalculated based on this value. 1.4.3 Morphing Other changes are made by automatically changing the location of skeleton nodes in 10 mm offsets in order to change the size of the corresponding body part based on the input measurement. For example, the default length of the forearm is 250 mm. By moving the hand bone in the direction of the normalcy of the forearm bone by 10 mm towards the hand, we lengthen the forearm by 10 mm and its length is 260 mm. It will be appreciated that other offset differences, e.g. in the range of 1mm to 50mm can be used in other implementations. Morphing is a technique in computer animation, a visual effect that creates an impression of smooth transformation of one object into another. For example, if a vertex has coordinates (x,y,z) when changing the morphing on some value, the vertex is moved to new coordinates (ax,by,cz). Thus, changing the shape of the mesh. Changing the morphing values by any value, enables the intermediate coordinates of the vertex to be obtained by linear interpolation. The technology uses morphing to change the gender and age of the body, on one single model, improving and reducing total amount of data transferred between the serve and the client device in order to minimise lag from the network connection. In the technology, this is used to change the width of the chest, hips, as well as to visualize the mass of the character's gender and age. In an example, the base body has a hip size (N) of 350mm. A morphing value of =1 changes the width of the hips by 10mm. Where, for example, the hip width value is measured at 400mm, a morphing value is determined by subtracting the base value from the measured value and dividing it by 10mm to obtain a morphing value, in this example =5. That is: (400 – 350) / 10 = 5. To display the body mass, body mass index is calculated depending on the entered height (A+J+G) and the patient's weight. Depending on the value of this index and other elements such as gender and age, the volume of the body shape is increased or decreased without adjusting the values entered by the user, such as the width of the hips or chest, since these values are rigidly entered by the user. Body mass is a rough visual representation, as it is not technically possible to display body mass in all its details. Using a combination of these two methods, it is possible to create a body as close as possible to the measurements needed to represent all the features of each subject. 1.5. Suggested Seating The functional modules 117 include a recommendation module that implements a number of algorithms to make recommendations to the user. Once all the data is aggregated, the recommendation module proceeds to score various products within the same category (e.g., Cushions, Back Supports, Head Supports) based on the user's provided information. After assessing all products, the recommendation module presents at least the top-scoring items in each category, emphasizing their distinctive features (e.g., pressure care, adaptability to changing needs, cost, etc.) to assist the user in making an informed choice that aligns with their specific requirements. The recommendation module also incorporates product rankings for certain items. These rankings indicate a product's suitability for subjects with more intricate needs or deformities. A higher product ranking signifies enhanced suitability for complex subjects. In some examples, the recommendation module combines both product scores and rankings to propose the most appropriate products. In instances where two products exhibit identical scores, the algorithm examines the product ranking, and the one with the higher ranking takes precedence. Furthermore, the algorithms implemented by the recommendation module take into account whether the deformities and posture issues are reducible, non-reducible, or reducible with effort, and tailors its recommendations based on these reducibility categories, which are able to adjust to reduce the deformity, or which have a shape to accommodate the deformity.. By leveraging various numerical parameters such as subject weight, mobility device specifications, and body measurements, the algorithm computes the most suitable product sizes, necessary customizations, and the extent of these customizations through calculations, as exemplified further below. The recommendation module takes into account the severity level (mild, moderate, severe) of deformities and assigns scores to each applicable product accordingly. In certain scenarios, a product may receive a zero / null score, indicating that it cannot be recommended to the subject, as it would cause issues for the subject according to the provided data. For example, the recommendation module will not recommend a cushion with tall lateral thigh contours for a subject who transfers in and out of the chair with an independent lateral transfer method. In an example, the system 100 also uses historical data of the subject stored in a profile. By recording the postural equipment used, configuration of those products, and the postural deformities at multiple times, the system 100 can identify trends in how the subject's posture may change over time. By comparing the trend information with the postural equipment being used at particular points in time, the system can suggest to a user that the changes in posture may be affected or unaffected by the postural equipment used. For example, if the system identifies particular features in postural equipment which have resulted in the stabilisation of a trend toward a severe posture or created a trend towards a neutral posture, the system 100 can apply higher scores to postural equipment containing similar features. In a further example, the system 100 could recommend a seating review interval based on the subject's history using postural equipment with similar features to the equipment prescribed. In an example, some recommendations can be encoded into one or more look-up tables that define a logic matrix for making recommendations for one or more components of the seating. The logic matrix groups relevant input data so it can be compared to a particular product, allowing the numerical parameters, severity, reducibility, and other elements related to a particular postural deformity to be compared to the features and adjustments of the seating component. In some scenarios, the recommendation module may recommend customisations to the standard features of a seating component, where the logic matrix shows the score is increased by the applying the customisation. In an example, the system 100 calculates size of back support depending upon information provided by the user. The system 100 uses the following tables to choose a style of back support and to calculate the size. The system 100 checks what wheelchair type is being used by the subject (or has been set to be used by the user) and then will check that what back support style has been suggested and then finally will calculates the height using mentioned formulas according to style of back support and wheelchair type. The system 100 uses the following table to calculate the back support width depending upon suggested back support style. If L > = 20” and / or B > = 23” then, the system 100 suggests Quad Mount Heavy Duty hardware for Back Support. Similarly, if 136kg < User weight < 180kg then, the system 100 suggests Quad Mount Heavy Duty hardware for Back Support. The system 100 uses following formulas to calculate the Arm Support size: Arm Support Length = Forearm Depth I From Elbow Height F of each side, get the height of Arm Supports. The system 100 uses following formulas to calculate the Thigh Support size. The system 100 provides personalized recommendations for back support solutions tailored to meet the specific needs of the subject. The system 100 assesses factors such as the curvature of the spine, any spinal irregularities, and the subject's seated posture to suggest back supports with the appropriate contouring and features. A back support algorithm implemented by the system 100 calculates the gaps between the 3D body surface and the back support. In an example, the back support comprises “pockets” for receiving one or more inserts or “cubes” of support. The system 100 determines the necessary number of cubes of support material to fill these calculated gaps with the cubes positioned at various points to offer enhanced support to the subject's back. Additionally, the algorithm takes into account factors such as reducibility when proposing contouring for different products. Implementation of the back support algorithm by the system 100, is illustrated with respect to FIGs.11 to 14. The system 100 generates a 3D model of the subject in a seated position 611E as shown in FIG.11 and then generates an abstract plane 1230, sized to match the most suitable back support dimensions based on the provided body measurements. This plane 1230 is positioned to align with the rearmost part of the 3D model body 630. The plane is divided into a grid structure resembling the rows and columns of pockets found in the back supports. In the illustrated example, there are six rows and five columns in the grid structure, such that the grid has thirty elements. Once appropriately positioned, the algorithm proceeds to compute the gap or distance between the centre point of each element of the grid and the 3D body. (In FIG.12, the centre points are represented as small circles in abstract plane, e.g. circle 1231 corresponding to the grid element in the fifth column / second row). FIG.13 illustrates calculated distances for a left most column of the grid. In this example, the system 100 has calculated a distance of 100 mm for a first, top grid element 1331, a distance of 80 mm for a second grid element 1332, a distance of 81 mm for a third grid element 1333, a distance of 61 mm for a fourth grid element 1334, a distance of 37 mm for a fifth grid element 1332, and a distance of 21 mm for a sixth, bottom grid element 1336. This gap or distance is then divided by the depth of cubes, allowing the algorithm to determine the optimal number of cubes required to fill the gap in accordance with the contours of the 3D body. FIG.14 illustrates example cube numbers for a left most column of the grid corresponding the distances in FIG.13. In this example, the system 100 has calculated a prescription of seven cubes 1431 for first, top grid element, a prescription of five cubes 1432 for second grid element, a prescription of five cubes 1433 for third grid element, a prescription of four cubes 1432 for fourth grid element, a prescription of two cubes 1435 for fifth grid element, and a prescription of one cube 1436 for bottom, sixth grid element. The recommendation of cubes is also contingent on the type of deformity present. Deformities may fall into categories of reducible, non-reducible, or reducible with effort. In cases of reducible deformities, the algorithm suggests the number and placement of cubes to aid in reducing the deformity. Conversely, for non-reducible deformities, the algorithm proposes the number and arrangement of cubes to accommodate the deformity effectively. The system 100 implements a cushion support algorithm employs a similar methodology to the back support algorithm for cushions. In this case, the cushion support algorithm implemented by the system 100 establishes an abstract plane beneath the 3D body, sized to match the most suitable cushion dimensions based on the provided body measurements. This plane is positioned to align with the lowest point of the subject's hip on the 3D body. This plane is structured with a grid pattern corresponding to rows and columns of pads to be used to form the cushion. Once correctly positioned, the algorithm proceeds to calculate the gap or distance between each point on the grid and the 3D body. This calculated gap or distance is then divided by the depth of the pads, enabling the algorithm to determine the optimal number of pads required to fill the gap in harmony with the contours of the 3D body. The suggestion of pads also takes into account the nature of deformities, whether they are reducible, non-reducible, or reducible with effort. For reducible deformities, the algorithm recommends both the number and placement of pads to aid in reducing the deformity, while for non-reducible deformities, it suggests the number and arrangement of pads to effectively accommodate the deformity. FIG. 15 shows an example of a 3D model 611F of a subject in position relative to an example cushion 1520 recommended by the cushion support algorithm. The cushion support module of the system 100 also calculates customisations or alignments of different parts of the cushion to suit the needs of subject. For example, if Thigh Depth is different for the two sides then the system 100 adds leg length discrepancy customisation in cushion with amount equal to the difference of leg lengths. In some examples, the subject may need custom lateral and medial thigh support in the cushion. Depending upon the need of custom lateral 1611A,1611B and medial thigh support 1612 in the cushion, cushion module of the system 100 calculates lateral and medial thigh supports as illustrated with respect FIGs.16A, 16B and 16C. In FIGs.16A-C: A = Width Of Cushion B = Depth of Cushion C = Hip Width D = Thickness of Left Lateral Thigh Support F = Left Leg Abduction / Adduction Angle E = Thickness of Right Lateral Thigh Support G = Right Leg Abduction / Adduction Angle T = Minimum Constant Thickness X = Angular Thickness of Left Lateral Thigh Support Y Angular Thickness of Right Lateral Thigh Support P = Standard Length of Medial Thigh Support N = Standard Thickness of Medial Thigh Support I = Angular Thickness of Medial Thigh Support for left leg H Angular Thickness of Medial Thigh Support for Right leg In order to specify the lateral thigh supports, the system 100 determines parameters for the lateral thigh supports as follows: A = Frame Width R B = Seat Depth S C = N D = X +T = B x Tan(F) E = Y +T = B x Tan(G) T = 15mm X = (B x Tan(F)) - T Y = (B x Tan(G)) - T In order to specify the medial thigh support, the system 100 determines parameters for the medial thigh supports as follows: I = P x Tan(F) H = P x Tan(G) New Front Width = H+N+I New Back Width = N = Old Back Width As illustrated with respect to FIG.17A to 17C, the cushion module of system 100 calculates contracture Cut-back customisation in the cushion 1711 depending upon user’s input for thigh to lower leg angle of the subject input during the Sitting MAT Assessment. As shown in FIGs.17A and 17B, where the posture of the subject is such that their legs are at an acute angle, in order to avoid the cushion rubbing on the subject’s legs 1712, the cushion module determines a cut-back. In FIGs.17A to 17C, θ = Thigh to Lower Leg Angle, U = Contracture Cut Back Length, and V = Height of base of cushion. As Tanθ = V / U, where V is known and θ is measure, U can be determined as U =V Tan^-1(θ). FIG.18A, illustrates an example, where the model of the subject 611G has an abnormal thigh to trunk angle. The example shows two angles, a and b represents Thigh to Trunk angles. Angle “a” is the angle when user has normal Thigh to Trunk angle which is 90 degrees, we can also call it a reference Thigh to Trunk Angle, while angle “b” is represents an abnormal Thigh to Trunk angle, angle “b” cannot be equal to 90 degrees and if it is, then the system 100 does not recommend the incorporation of Thigh Angle in cushion. If “b” is not equal to 90 degrees (or a suitable margin around 90 degrees the system 100 calculated the Cushion Thigh Angle = a – b. For example, if b = 80 then Cushion Thigh Angle = 90 - 80 = 10 degrees (i.e.10 degrees “up”). Similarly if b = 9, then Cushion Thigh Angle = 90 - 97 = -7 degrees up means 7 degrees down. In FIG.18A, “B” corresponds to the length of cushion. In an example, a slope to accommodate thigh angle is applied to half the cushion length, therefore, the system 100 determines Thigh Angle slope in Cushion from the middle of the cushion towards the subject’s legs. In following calculation “x” is representing Cushion Thigh Angle (degrees) which is a-b and “y” represents the desired reduction in the cushion height at the periphery of the cushion, such that y = tan|x| * (B / 2). The system 100 can also make recommendations for other aspects, including head supports where the system 100 evaluates the subject head and neck alignment, considering any challenges arising from disabilities or deformities. Based on this analysis, the system 100 proposes head support solutions that offer proper positioning, comfort, and stability. The system 100 maps the position and alignment of head and tries to position head support pad and adjust the hardware using inverse kinematics to provide better support to subject's head and neck. The system 100 takes into account factors like reducibility while suggesting contouring and positioning for different products. Once the seating is recommended, 3D modelling engine of functional models 117 generates a 3D seating model so that the user can view the 3D subject model in conjunction with the 3D seating model and make modifications. In this respect, a number of components of the seating have predefined 3D models in the form of polygonal 3D models generated using Blender. In an example, there are scalable models for components such as seat bases, cushions, back supports, lateral pads, and arm and thigh support pads. There are also static (not scalable) 3D models for “hardware” components such as wheelchair bases as well as head support pads. The models are prepared GLB / GLTF2.0 format and integrated with Three.js / WebGL technology. In an example, each 3D model object incorporates its own kind armature deforming, allowing for extensive reshaping to fit various body types. In order to scale the models, a combination of deformation techniques are used including morph target-based deformation, armature deforming and object transforms. Shaders are used to apply textures and materials, enhancing the deformation process and providing realistic visual effects. Example 1 Subject 1 is a 35-year-old individual with a stable condition of Cerebral Palsy (GMFCS level IV, Spastic Quadriplegia). The subject experiences issues related to frequent sliding on the cushion, decreased seating tolerance, and lumbar / sacral region pain. The subject's weight is 45 kg, and she spends more than 4 hours in a wheelchair daily. Her preferred transfer method is a hoist. Subject 1 currently uses a wheelchair with the following seating equipment: • Seat Cushion • Back Support • Head Support • Harness • Lateral Trunk Support • Lateral Thigh Support • Hip belt • Limb Support • Medial Thigh Support • Arm Support These components aim to support Patient I's postural needs but have an impact on mobility and transferring. The following MAT assessment findings are entered into the system 100 via the user interface: 1. Pelvis: • Severe Right pelvic obliquity (reducible with effort) • Moderate right pelvic rotation (reducible with effort) • Mild kyphosis (reduces with effort) 2. Trunk: • Severe convex right scoliosis • Moderate left rotation of trunk (reducible with effort) 3. Hips: • Thigh-trunk angle: 90° on both sides • Left hip in internal rotation, right hip in neutral 4. Lower Limbs: • Thigh-lower leg angle: 90° on both sides. • Lower leg-foot angle: 90° on both sides • Neutral foot position on both sides 5. Cervical Spine: • Lateral flexion to the right (reducible) 6. Head and Neck: • Restricted head control • Normal shoulder position 7. Upper Limbs: • Elbow and forearm at 90° • Neutral wrists and hands Table 1 illustrates an example output of the recommendation engine of the system 100 following the MAT Assessment. The third column, explains the system’s recommendation. Table 1 After the system 100 provides recommendation for seating products, the system 100 displays a 3D model of the subject relative to a 3D model of the seating prescription as described above. If the user is dissatisfied with the suggested products or their configurations they have the option to tweak the subject’s posture for enhanced comfort, and the suggested products contouring and position will change accordingly. Alternatively, the user can manually make adjustments to the products according to the subject's specific requirements. Table 2 shows an example of an outcome of a user making postural adjustments via the user interface and how such adjustment swill mostly affect the cushion and back support. Table 2 The example in Table 3, shows how entering modifications to the products, specifically the contouring of back support and cushion can affect the body of the subject. Table 3 Subject 2 is a 27-year-old male diagnosed with Duchenne Muscular Dystrophy, currently in a stable condition. He relies on a powerchair with seating equipment that requires adjustments. Patient II spends more than 4 hours in his wheelchair and prefers hoist-assisted transfers. Current Seating Equipment: Patient 2 currently uses a power wheelchair with the following seating equipment: • Cushion • Back Support • Head Support • Harness • Lateral Trunk Support • Lateral Thigh Support • Hip belt • Limb Support • Arm Support • Elbow Support The following MAT assessment findings are entered into the system: 1. Pelvis: • Moderate anterior pelvic tilt (reducible with effort) • Mild left pelvic obliquity (reducible with effort) 2. Trunk: • Mild Lordosis (reducible with effort) • Moderate Convex left scoliosis (reducible) 3. Hips: • Left hip exhibits abduction and external rotation 4. Lower limbs: • Thigh-lower leg angle: 90° on both sides • Lower leg-foot angle: 90° on both sides • Left foot inversion Cervical Spine: 5. Cervical curve in extension (reducible with effort) • Rotation of the cervical spine (reducible with effort) 6. Head and Neck: • The patient has independent head control • Normal shoulder position 7. Upper Limbs: • Elbow and forearm can achieve 90° • Neutral wrists and hands The system’s 100 recommendations are set out in Table 4.

[0002] Table 4 1.6. Other Postural Equipment As indicated above, ins some examples, the system 100 may be used in connection with other postural equipment, such as sleep systems. FIGs.19 and 20are example user interfaces 1900, 2000 for capturing input data for postural information a sleep system to enable generation of a 3D model of a subject. This input data may be captured in addition to or instead of the data described above and used to generate and / or update a 3D model of a subject. FIG.19 illustrates the capture of data specific to sleeping positions, in this example, user interface components in the form or radio buttons and text fields, enable the capture of personal and environmental factors including transfer method (how the subject gets into a bed) 1911, nutrition intake 1912, subject’s condition 1913, cognition and perception 1914, sleep history 1915, sleep position 1916, history of pressure injury (PI) 1917, and risk of pressure injury 1918. FIG.20 is an example of a user interface 200 comprising indicative measurement positions 2010 and user interface components in the form of a plurality of fields for capturing elements of a body shape of a human subject relevant to sleep position. In this example measurements include: A – Chest Width 2021; B – Shoulder Height 2022; C – Knee to Knee Width 2023; D – Trunk Height 2024; E – Hip to Ankle 2025; F – Knee to Surface; FIG.21 is an example screen display 2100 which illustrates how a current position of a 3D model of a subject relative to current equipment can be displayed to a user. In this example, righthand pane 2110 allows the user to select postural equipment components. In this example, the user has selected first 2112 and second 2114 postural components, and corresponding first 2122 and second 21243D models of the selected components are shown in lefthand pane 2120 in conjunction with a 3D model 2140 of a subject. Subject model 2140 has handles (e.g. first to third handles 2142) for adjusting the position of the 3D model relative to the current equipment. The interface 2100 also enables the user to alter the position of the current equipment relative to the user. Interface 2100 includes buttons 2150 for toggling between a display of the current position and a desired position. FIG.22 illustrates an example screen display 2200 where a user has toggled to the desired position window such that it is now display in the left pane. In this example, the user has kept the same equipment but has interacted with the user interface to adjust the position of the first 3D model 2122A and second 3D model 2124A of these components, and the subject model such that, for example, first to third handles 2142A are in updated positions. Accordingly, the interface 2200 enables the 3D model of the subject and the equipment to be adjusted prior to confirming that the currently selected equipment can be output as a prescription for the subject. Reference to any prior art in this specification is not, and should not be taken as, an acknowledgement or any form of suggestion that that prior art forms part of the common general knowledge in the field of endeavour in any country in the world. Where in the foregoing description reference has been made to integers or components having known equivalents thereof, those integers are herein incorporated as if individually set forth. It should be noted that various changes and modifications to the presently preferred embodiments described herein will be apparent to those skilled in the art. Such changes and modifications may be made without departing from the spirit and scope of the technology and without diminishing its attendant advantages. It is therefore intended that such changes and modifications be included within the present technology.

Claims

CLAIMS 1. A computer-implemented method for dynamic prescription of individualised postural equipment, comprising receiving, via at least a first user interface component, input data from a user, the input data specifying elements of a body shape of a human subject; generating a 3D subject model of the body of the human subject based on the input data; causing an electronic display to display the 3D subject model positioned relative to a 3D postural equipment model of a postural equipment prescription for the human subject intended to support the subject when implemented in postural equipment, to thereby enable the user to visualise a relationship between the 3D subject model and the 3D postural equipment model; receiving, via at least a second user interface component, modification data in respect of at least one of the 3D subject model and the 3D postural equipment model; updating at least one of the 3D subject model and the 3D postural equipment model based on the modification data; causing the electronic display to display the updated at least one of the 3D subject model and the 3D postural equipment model; and outputting postural equipment prescription data in response to a user command, the prescription data enabling production of postural equipment corresponding to the 3D postural equipment model.

2. The method as claimed in claim 1, further comprising repeatedly iterating through the steps of updating the at least one of the 3D subject model and the 3D postural equipment model based on the modification data, and causing the electronic display to display the updated at least one of the 3D subject model and the 3D postural equipment model, each time modification data is received.

3. The method as claimed in claim 1 or claim 2, comprising generating the 3D postural equipment from the prescription data.

4. The method as claimed in claim 3, wherein receiving modification data in respect of the 3D postural equipment model comprises receiving a modification of the prescription data.

5. The method as claimed in any one of claims 1 to 4, further comprising processing the input data to make at least one recommendation for at least one component of the postural equipment.

6. The method as claimed in any one of claims 1 to 5, wherein the input data further comprises postural equipment data corresponding to at least one of a current or proposed postural equipment for the subject.

7. The method as claimed in any one of claims 1 to 6, wherein generating the 3D subject model comprises modifying a 3D base skeleton model by scaling the skeleton model based on measurements of the subject included in the input data.

8. The method as claimed in claim 7, wherein the 3D base skeleton model includes a plurality of nodes defining the positions of bones of the 3D base skeleton model, and generating the 3D subject model comprises adjusting a position of at least one of the plurality of nodes based on measurements of the subject included in the input data.

9. The method as claimed claim 7 or claim 8, wherein receiving modification data comprises receiving an input adjusting an angle of the at least one bone of the 3D subject model.

10. The method as claimed in claim 1, comprising, after generating the 3D subject model of the body of the human subject based on the input data, causing the electronic display to display the 3D subject model to enable the user to make adjustments to the 3D subject model and / or input additional data specifying further elements of the body shape of the human subject prior to the 3D model being displayed in conjunction with the 3D seating model.

11. The method as claimed in any one of claims 1 to 10, wherein the postural equipment is a seating apparatus.

12. A computer program comprising instructions which when executed cause one or more processors to carry out the method of any one of claims 1 to 10.

13. A tangible computer-readable medium comprising the computer program of claim 11.

14. A system for dynamic prescription of individualised postural equipment comprising: at least a first user interface component for receiving input data from a user, specifying elements of a body shape of a human subject; a 3D modelling engine for: generating a 3D subject model of the body of the human subject based on the input data; and causing an electronic display to display the 3D subject model positioned relative to a 3D postural equipment model of a postural equipment prescription for the human subject intended to support the subject when implemented in postural equipment, to thereby enable the user to visualise a relationship between the 3D subject model and the 3D postural equipment model; at least a second user interface component for receiving modification data in respect of at least one of the 3D subject model and the 3D postural equipment model, whereafter the 3D modelling engine updates at least one of the 3D subject model and the 3D postural equipmentmodel based on the modification data, and causes the electronic display to display the updated at least one of the 3D subject model and the 3D s postural equipment model; and a prescription output component for outputting prescription data in response to a user command, the prescription data enabling production of postural equipment corresponding to the 3D postural equipment model.

15. A computer-implemented method for dynamic prescription of individualised postural equipment, comprising receiving, via at least a first user interface component, input data from a user, the input data specifying elements of a body shape of a human subject; generating a 3D postural equipment model of a postural equipment prescription for the human subject intended to support the subject when implemented in postural equipment based on the input data; causing an electronic display to display the 3D postural equipment model to thereby enable the user to visualise the 3D postural equipment model; receiving, via at least a second user interface component, modification data in respect of the 3D postural equipment model; updating the 3D postural equipment model based on the modification data; causing the electronic display to display the updated a 3D postural equipment model; and outputting postural equipment prescription data in response to a user command, the prescription data enabling production of postural equipment corresponding to the 3D postural equipment model.

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