Head mounted data acquisition system and applications therefor

Abstract

In a broad form there is disclosed a head mounted data acquisition system and applications therefor. In a broad form there is disclosed a head mounted data acquisition and assessment system and applications therefor. There is disclosed also a system for use of a multi sensor headset. In some forms there is provided an observation system which observes characteristics or parameters in order to analyse for health conditions. In some forms there is provided an observation system which observes gait and other characteristics or parameters in order to produce orthotics. In some forms the invention presents an AI-driven system for enhancing elderly care. There is described the framework and operational components of an AI system designed to assist elderly care. By leveraging artificial intelligence, the system offers a solution to improve the quality and effectiveness of care for the elderly population.

Description

HEAD MOUNTED DATA ACQUISITION SYSTEM AND APPLICATIONS THEREFOR .FIELD OF THE INVENTION

[0001] In a broad form there is disclosed a head mounted data acquisition system and applications therefor .

[0002] In a broad form there is disclosed a head mounted data acquisition and assessment system and applications therefor .

[0003] There is disclosed also a system for use of a multi sensor headset .

[0004] Also disclosed is an integrated Al system. More specifically but not exclusively there is disclosed an integrated Al system for enhancing elderly care .

[0005] In a particular but not exclusive form the invention relates to the field of elderly care . More specifically but not exclusively it relates to an integrated artificial intelligence (Al ) system with inputs from user ' s wearing multi sensor eyewear . In particular forms it is designed to improve the caregiving process through multimodal data analysis , personalised interactions , and health monitoring .

[0006] Also disclosed is wearable health monitoring and assessing glasses or spectacles . In preferred forms the glasses include an integrated multisensor system and augmented reality capabilities .

[0007] In a particular but not exclusive form the present invention relates to wearable health monitoring devices . More specifically but not exclusively it relates to smart glasses equipped with integrated sensors .

[0008] In particular but not exclusive forms the invention relates to head mounted data acquisition devices which may include one or more of augmented reality (AR) displays , onboard processing capabilities , and advanced diagnostic features for real-time health assessment and monitoring .BACKGROUND

[0009] The production of customised orthoses such as orthopaedic footwear and orthotics using multiple sensor arrays to feed a custom orthopaedic fitting and production system is known in the art , however this process and the sensors involved are expensive and require specialist knowledge and s kills to operate .

[0010] With the advent of multi-sensor virtual reality and augmented reality headsets , many of the sensors needed for the digital enabled production of orthoses are available in a relatively low cost user friendlyform factor, yet the application of these technologies in this form factor have not yet been applied to orthoses or orthopaedic footwear and orthotic production .

[0011] The disclosed invention is designed to address this issue .

[0012] As the global population ages , the demand for efficient and personalised elderly care solutions has significantly increased . Traditional caregiving methods often fail to address the nuanced needs of the elderly comprehensively, creating a need for innovative solutions that leverage technology to provide scalable , effective , and personalised care .

[0013] Current wearable health monitoring devices , such as smartwatches and fitness trackers , are limited in their diagnostic capabilities , typically focusing on basic metrics like heart rate and step count , and often require tethered connections to external devices for advanced processing . Existing AR wearables lack comprehensive health monitoring and standalone functionality, relying on smartphones or computers for computation and storage . Additionally, advanced diagnostics like ultrasound or thermal imaging require separate , non-portable equipment . There is a need for a single , lightweight , and ergonomic device that integrates multiple sensors , onboard processing, and advanced diagnostic capabilities into a fully independent system for real-time health monitoring and assessment .

[0014] More generally there is a need for a head mounted data acquisition system which can assist in a cost-effective way to acquire data relevant to the user and which can then be fed to applications relevant to the needs of the user .

[0015] One or more embodiments of the disclosed invention are designed to address one or more of these issues .NOTES

[0016] The term "comprising" ( and grammatical variations thereof ) is used in this specification in the inclusive sense of "having" or "including" , and not in the exclusive sense of "consisting only of" .

[0017] The above discussion of the prior art in the Background of the invention, is not an admission that any information discussed therein is citable prior art or part of the common general knowledge of persons s killed in the art in any country .BRIEF DESCRIPTION OF INVENTIONDefinitions

[0018] Orthosis : in this specification an orthosis is an orthotic device which provides support for a part of the body such as a joint.

[0019] Orthotic or Orthotic Device: in this specification an orthotic device is a support, brace or splint used to support, align or correct the function of moveable parts of the body.

[0020] Orthopaedic footwear: in this specification orthopaedic footwear is footwear which incorporates an orthotic device (for example an insert) which renders the footwear to function as an orthotic device.Summary of Invention

[0021]

[0022] In its broadest form there is disclosed a head mounted data acquisition system which can assist in a cost-effective way to acquire data relevant to the user and which can then be fed to applications relevant to the needs of the user.

[0023] In another broad form of the invention, there is provided an orthopaedic analysis, fitting and production system comprising at least one multi purpose multi sensor device for the production of orthoses; the system further comprising an automated or computer assisted design and modelling system which then outputs to an orthoses production system; the sensor device including sensors:1. wherein the sensors on the sensor device include at least but are not limited to a high resolution camera and accelerometer; and2. wherein the outputs of the sensors are connected either in real time or store and forward to the system whereby sensor data is sent from the sensors to the system thereby to produce orthoses.

[0024] Preferably, the system is adapted to produce customised orthopaedic footwear and orthotics .

[0025] Preferably, the sensors include a camera capable of high resolution near infra-red wavelength sensing.

[0026] Preferably, the sensors available include a LIDAR scanner.

[0027] Preferably, the multi purpose, multi sensor device is a virtual reality headset.

[0028] Preferably, the multi purpose , multi sensor device is an augmented reality headset .

[0029] Preferably, the user of the sensor device does not need specialised training or s kills to operate the sensor device .

[0030] Preferably, the system includes preprocessing of the sensor data .

[0031] Preferably, the sensor data is sent in real time to the system.

[0032] Preferably, the sensor data is stored and forwarded to the system .

[0033] Preferably, the sensor data is stored and forwarded to the system at predetermined time intervals .

[0034] In another broad form of the invention, there is provided a data acquisition, gait analysis orthopaedic analysis , fitting and production system comprising at least one multi purpose multi sensor device for the production of orthoses ; the system further comprising an automated or computer assisted design and modelling system which then outputs to an orthosis production system; the sensor device including sensors :1 . wherein the sensors on the sensor device include at least but are not limited to a high resolution camera; and2 . wherein the outputs of the sensors are connected either in real time or store and forward to the system whereby sensor data is sent from the sensors to the system thereby to produce orthoses .

[0035] Preferably, the system is adapted to produce customised orthopaedic footwear and orthotics .

[0036] Preferably, the sensors include a camera capable of high resolution near infra-red wavelength sensing .

[0037] Preferably, the sensors available include a LIDAR scanner .

[0038] Preferably, the multi purpose , multi sensor device is a virtual reality headset .

[0039] Preferably, the multi purpose , multi sensor device is an augmented reality headset .

[0040] Preferably, the user of the sensor device does not need specialised training or s kills to operate the sensor device .

[0041] Preferably, the system includes preprocessing of the sensor data .

[0042] Preferably, the sensor data is sent in real time to the system.

[0043] Preferably, the sensor data is stored and forwarded to the system .

[0044] Preferably, the sensor data is stored and forwarded to the system at predetermined time intervals .

[0045] In a further broad form, the invention comprises an integrated system utilising artificial intelligence to enhance the quality of care for the elderly.

[0046] In preferred forms, the system analyses multimodal data, including audio, video, and accelerometer inputs, to assess the physical and emotional well-being of elderly individuals and their interactions with caregivers .

[0047] In preferred forms, through natural language processing, the system facilitates communication and feedback, while a personalization engine tailors care and interaction based on individual user profiles. A dedicated privacy and ethics framework ensures data integrity and user consent.

[0048] In preferred forms, the present invention addresses the limitations of existing wearable health monitoring devices by providing a pair of smart glasses with integrated sensors, AR displays, onboard CPU, GPU, RAM, and storage, and Al-driven diagnostic capabilities.

[0049] In preferred forms, the glasses are designed to monitor a wide range of health metrics, including cardiovascular, neurological, and musculoskeletal conditions, in real-time without requiring external devices. Features of preferred forms of the invention include:

[0050] Multi-Sensor Integration: Sensors such as PPG, EEG, ultrasound, thermal imaging, and bioimpedance for comprehensive health monitoring.

[0051] Augmented Reality Displays: A micro-OLED display provides realtime health data and AR visualizations, enhanced by an onboard GPU.

[0052] Standalone Processing: A CPU, GPU, 4GB RAM, and 64GB storage enable local data processing, storage, and app execution.

[0053] AI-Driven Diagnostics: A multimodal Al algorithm processes data from all sensors to provide holistic health insights and early detection of medical conditions.

[0054] Therapeutic Feedback: Features such as red light therapy (RLT) and vibration therapy for stress relief and pain management.

[0055] Environmental Monitoring: Sensors for air quality, UV exposure, and gas detection provide real-time environmental insights .

[0056] User Accessibility : Includes a Braille haptic panel, bone conduction speaker, and voice recognition for accessibility by users with disabilities .

[0057] In yet another broad form of the invention there is provided an orthopaedic analysis, fitting and production system comprising at leastone multi purpose multi sensor device for the production of orthoses ; the system further comprising an automated or computer assisted design and modelling system which then outputs to an orthoses production system; the sensor device including sensors :

[0058] wherein the sensors on the sensor device include at least but are not limited to a high resolution camera and accelerometer ; and

[0059] wherein the outputs of the sensors are connected either in real time or store and forward to the system whereby sensor data is sent from the sensors to the system thereby to produce orthoses .

[0060] Preferably the system is adapted to produce customised orthopaedic footwear and orthotics .

[0061] Preferably the sensors include a camera capable of high resolution near infra-red wavelength sensing .

[0062] Preferably the sensors available include a LIDAR scanner .

[0063] Preferably the multi purpose , multi sensor device is a virtual reality headset .

[0064] Preferably the multi purpose , multi sensor device is an augmented reality headset .

[0065] Preferably the user of the sensor device does not need specialised training or s kills to operate the sensor device .

[0066] Preferably the system includes preprocessing of the sensor data .

[0067] Preferably the sensor data is sent in real time to the system .

[0068] Preferably the sensor data is stored and forwarded to the system .

[0069] Preferably the sensor data is stored and forwarded to the system at predetermined time intervals .

[0070] In yet a further broad form of the invention there is provided a data acquisition, gait analysis orthopaedic analysis , fitting and production system comprising at least one multi purpose multi sensor device for the production of orthoses .

[0071] Preferably the system further comprises an automated or computer assisted design and modelling system which then outputs to an orthosis production system; the sensor device including sensors .

[0072] Preferably the sensors on the sensor device include at least but are not limited to a high resolution camera .

[0073] Preferably the outputs of the sensors are connected either in real time or store and forward to the system whereby sensor data is sent from the sensors to the system thereby to produce orthoses .

[0074] Preferably the system is adapted to produce customised orthopaedic footwear and orthotics .

[0075] Preferably the sensors include a camera capable of high resolution near infra-red wavelength sensing .

[0076] Preferably the sensors available include a LIDAR scanner .

[0077] Preferably the multi purpose , multi sensor device is a virtual reality headset .

[0078] Preferably the multi purpose , multi sensor device is an augmented reality headset .

[0079] Preferably the user of the sensor device does not need specialised training or s kills to operate the sensor device .

[0080] Preferably the system includes preprocessing of the sensor data .

[0081] Preferably the sensor data is sent in real time to the system .

[0082] Preferably the sensor data is stored and forwarded to the system .

[0083] Preferably the sensor data is stored and forwarded to said system at predetermined time intervals .

[0084] In yet a further broad form of the system there is provided an integrated Al system for elderly care , comprising :

[0085] a multimodal data analysis module for analysing audio , video , and motion sensor data .

[0086] In yet a further broad form of the system there is provided an NLP module for facilitating natural language interactions .

[0087] 3 In yet a further broad form of the system there is provided a personalization engine for tailoring care and interaction based on user profiles .

[0088] In yet a further broad form of the system there is provided a privacy and ethics framework ensuring data integrity and consent .

[0089] In yet a further broad form of the system there is provided a multi sensor headgear or goggles or glasses that allow the system to monitor interactions between the patient and carer using video , audio or an accelerometer .

[0090] Preferably the multimodal data analysis module employs machine learning algorithms for interpreting interaction quality and emotional states .

[0091] Preferably the personalization engine integrates with electronic health records for comprehensive care planning .

[0092] Preferably the headgear or glasses facilitate feedback in the form of audio or video and interactive media that is shown to the wearer to help the carer or patient with necessary activities .

[0093] In yet a further broad form of the invention there is provided a wearable health monitoring device comprising :

[0094] A frame configured to be worn as glasses , the frame including a bridge , two arms , and lenses .

[0095] Preferably a plurality of sensors are integrated into the frame .

[0096] Preferably the frame incorporates a drone landing mount for a drone .

[0097] Preferably the drone landing mount incorporates charging apparatus

[0098]

[0099] Preferably the drone is operable from and in association with the glasses .

[0100] In yet a further broad form of the invention there is provided A wearable health monitoring device comprising

[0101] Al vision goggles.

[0102] Preferably the goggles incorporate a drone landing mount.

[0103]

[0104] Preferably the drone landing mount incorporates charging apparatus .

[0105]

[0106] Preferably the drone is operable from and in association with the goggles .

[0107] In yet a further broad form of the invention there is provided a wearable health monitoring device comprising goggles , glasses or a drone.

[0108] Preferably the glasses, goggles or drone include one or more of the following:

[0109] A photoplethysmography (PPG) sensor configured to monitor heart rate and blood oxygen levels;

[0110] An electroencephalogram (EEG) sensor configured to detect brain wave patterns;

[0111] An ultrasound transducer configured to provide real-time imaging of soft tissues and organs;

[0112] A thermal imaging camera configured to detect temperature variations and inflammation;

[0113] A bioimpedance sensor configured to measure blood pressure and body composition;

[0114] A sweat sensor configured to analyze glucose and electrolyte levels ;

[0115] A graphene acoustic sensor configured to analyze voice and breath sounds ;

[0116] An air quality sensor configured to detect environmental pollutants ;

[0117] A UV sensor configured to monitor ultraviolet radiation exposure;

[0118] A gas sensor array configured to detect harmful gases;

[0119] A micro-OLED display integrated into the lenses, configured to provide augmented reality (AR) visualizations and real-time health data;

[0120] A CPU integrated into the frame, configured to enable standalone processing of sensor data and AR applications;

[0121] A GPU integrated into the frame, configured to render real-time AR visualizations on the micro-OLED display;

[0122] 4GB RAM integrated into the frame, configured to support multitasking and smooth operation;

[0123] 64GB storage integrated into the frame, configured to store health data, apps, and content locally;

[0124] A multimodal Al processor configured to integrate data from the plurality of sensors and provide diagnostic insights;

[0125] A battery and solar strip integrated into the frame, configured to provide power to the device;

[0126] A bone conduction speaker integrated into the bridge, configured to provide audio output for accessibility;

[0127] A Braille haptic panel integrated into the bridge, configured to provide tactile feedback for visually impaired users;

[0128] A MEMS microphone and voice recognition software configured to enable voice commands;

[0129] A 1080p camera configured to capture environmental and gait data;

[0130] Far-UVC LEDs integrated into the frame, configured to provide pathogen control;

[0131] Red light therapy (RLT) LEDs integrated into the bridge, configured to provide therapeutic benefits;

[0132] A vibration actuator configured to provide haptic feedback and stress relief.

[0133] In yet a further broad form of the invention there is provided a method for real-time health monitoring using wearable glasses or goggles, the method comprising:

[0134] Collecting data from a plurality of sensors integrated into the glasses or goggles.

[0135] 13 Preferably the method further includes

[0136] Including one or more of :

[0137] Heart rate and blood oxygen levels from a photoplethysmography (PPG) sensor;

[0138] Brain wave patterns from an electroencephalogram (EEG) sensor;

[0139] Soft tissue imaging from an ultrasound transducer;

[0140] Temperature variations and inflammation from a thermal imaging camera;

[0141] Blood pressure and body composition from a bioimpedance sensor;

[0142] Glucose and electrolyte levels from a sweat sensor;

[0143] Voice and breath sounds from a graphene acoustic sensor;

[0144] Environmental pollutants from an air quality sensor;

[0145] Ultraviolet radiation exposure from a UV sensor;

[0146] Harmful gases from a gas sensor array;

[0147] Processing the collected data locally using a CPU and multimodal Al algorithm to generate diagnostic insights;

[0148] Rendering and displaying the diagnostic insights via a GPU-powered micro-OLED display integrated into the lenses of the glasses;

[0149] Storing health data and applications in 64GB onboard storage with support from 4GB RAM;

[0150] Providing therapeutic feedback via red light therapy (RLT) LEDs and a vibration actuator;

[0151] Enabling user interaction via a bone conduction speaker, Braille haptic panel, and voice recognition software.

[0152] Preferably the wearable health monitoring device further comprises :

[0153] A retinal imaging camera integrated into the bridge, configured to monitor eye health and detect conditions such as diabetic retinopathy and glaucoma .

[0154] Preferably the device further comprises :

[0155] A gesture recognition sensor configured to enable hands-free control of the device.

[0156] Preferably the device further comprises further comprising:

[0157] An impact detection sensor configured to detect falls and trigger emergency alerts.

[0158] Preferably the device further comprises further comprising:

[0159] A tear analysis sensor configured to detect biomarkers in tears for monitoring conditions such as diabetes and dry eye syndrome .

[0160] Preferably the device further comprises further comprising :

[0161] A laser Doppler flowmetry sensor configured to monitor blood flow in microvascular systems .

[0162] Preferably the device further comprises further comprising :

[0163] Preferably the device further comprises further comprising :

[0164] Preferably the device further comprises a 5G connectivity module configured to enable high-speed data transfer for real-time monitoring and telemedicine .

[0165] Preferably the device further comprises further comprising :

[0166] A holographic display integrated into lenses of spectacles or goggles , configured to proj ect 3D AR visualizations for advanced applications .

[0167] Preferably the device further comprises a transcranial magnetic stimulation (TMS ) module configured to provide non-invasive brain stimulation for therapeutic purposes .

[0168] Preferably the device further comprises further comprising :

[0169] Preferably an acupressure node is integrated into the frame , configured to provide stress relief and pain management .BRIEF DESCRIPTION OF DRAWINGS

[0170] Embodiments of the present invention will now be described with reference to the accompanying drawings wherein :

[0171] Figure 1 is a block diagram of a headmounted data acquisition system in accordance with a generalised embodiment suited to feed data and signals into a variety of applications .

[0172] Figure 2 is a block diagram of the main components of an example embodiment in the form of a first preferred embodiment of the invention;

[0173] Figure 3 illustrates an in use scenario utilising the system of Figure 2 ;

[0174] Figure 4 illustrates diagrammatically foot pressure (plantar pressure ) imprints of the client of Figure 3 , 4 utilising infrared sensing to analyse bottom of foot pressure points ;

[0175] Figure 5 is a process flow diagram according to an embodiment of the present invention;

[0176] Figure 6 illustrates the main components of the system of Figure 2 , which work together in the in use scenario of Figures 3 , 4 whereby an orthopaedic analysis is conducted on the client following acquisition of data from the client , thereby to produce appropriate orthoses consequential upon the data acquisition and orthopaedic analysis .

[0177] Figure 7 - main components of the example embodiment in accordance with a second preferred embodiment

[0178] Figure 8 is main components of the example embodiment in accordance with a second preferred embodiment in block diagram form;

[0179] Figure 9 - the process of the example embodiment of Fig 7 , 8

[0180] Figure 10 - illustrates a patient or user wearing the virtual reality or augmented reality goggles in order to implement the embodiment of figure 8

[0181] Figure 11 - illustrates conceptually an avatar that may appear in the virtual reality or augmented reality goggles worn by the user in figure 2 . 3 in order to assist , advise , and motivate the user .

[0182] Figure 12 is a block diagram of a head mounted data acquisition system according to a fifth embodiment incorporating a drone mount in association with the glasses or goggles and a drone operable in association with the system .DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

[0183] In its broadest form there is disclosed a head mounted data acquisition system which can assist in a cost-effective way to acquire data relevant to the user and which can then be fed to applications relevant to the needs of the user .

[0184] With reference to figure 1 there is disclosed in one broad form a head mounted data acquisition system 30 . The system 30 is suited to feed data and signals into a variety of applications , some of which are described in more detail further in this specification .

[0185] The system 30 includes a headmounted data acquisition device 31 in this instance in the form of face mounted eyewear 31 . More specifically the face mounted eyewear 31 may take the form of spectacles to which sensor componentry is fixed or incorporated .

[0186] Alternatively and more specifically the face mounted eyewear 31 may take the form of eyewear or goggles where optical lenses are replaced with displays 32 . In this instance the screens of the displays 32 are directed towards the eyes 33 of a wearer or user 34 .

[0187] Additionally there may be included mechanisms 35 which permit the eyes of the user 34 to see both the displays 32 and the environment in front of the user 34 at the one time and to resolve images from both . In one form these mechanisms 35 will include refractive components . In another form these mechanisms will include reflective components .

[0188] In yet another form these mechanisms will include both refractive and reflective components .

[0189] In another form the face mounted eyewear 31 includes a camera or other image acquisition device 36 . Images from the image acquisition device may be fed to the displays 32 . In another form the images from the image acquisition device 36 may also be fed to data processing apparatus or processor 37 .

[0190]

[0191] Data from the image acquisition device 36 may further be fed via Internet 38 or other communications medium to a server 39 for processing .

[0192] In addition data from the data processing apparatus 37 may also be fed to server 39 via Internet 38 or other communications medium .

[0193]

[0194] In use data from the face mounted eyewear 31 is utilised by applications relevant to the needs of the user 34 .

[0195] Various non-limiting applications are described in further detail further in this specification .First Preferred Embodiment

[0196] Broadly with reference to figure 2 , there is disclosed an orthopaedic analysis , fitting and production system 10 comprising at least one head mounted data acquisition device 11 in this instance in the form of a multi purpose multi sensor device for the production of orthoses 12 ; the system 10 further comprising an automated or computer assisted design and modelling system 13 which then outputs to an orthoses production system14 in this instance in the form of a 3D printer; the sensor device 11 including sensors :1 . wherein the sensors on the sensor device may include at least but are not limited to a high resolution camera 16 and accelerometer 15 ; and2 . wherein the outputs of the sensors are connected either in real time or store and forward to the system 10 whereby sensor data is sent from the sensors to the system thereby to produce orthoses 12 .

[0197] A first preferred embodiment of the invention is disclosed by way of an example embodiment .Example Embodiment

[0198] With reference to Figure 2 , the example embodiment discloses a sensible advice 11 in this instance in the form of an Apple Vision Pro ( trademark of Apple Corporation ) in use with a network 18 , a sensor data analysis system 17 , an orthopaedic analysis and fitting system, and a foot wear and orthotic production system 14 .

[0199] Figure 21 . The system 10 components of the example embodiment are : i . An Apple Vision Pro or similar head mounted data acquisition device 11 ii . The Internet 18 iii . A sensor data analysis system 17 iv . An orthopaedic analysis and fitting system v . A footwear and orthotic production system 142 . in this instance the Apple Vision Pro has a number of sensors including but not limited to : i . Wide range frequency cameras that can detect near or at infrared wavelength light .1 . Normal wavelength light can be used in combination with a LIDAR sensor to accurately measure subj ect feet for fitting and comfort2 . The near infrared or infrared camera capability can be used to measure heat signatures of pressure points of irritation on the foot and also a . In capturing heat signatures from the ground after someone has walked on it to see pressure points and bottom of foot contours for orthopaedic footwear and orthotic design .ii . LIDAR can be used in combination with the camera to produce l-5mm accurate computer-aided models of a user ' s foot and its changes as a person uses it . iii . Accelerometers can be used to help position the headset in space relative to the foot and can be used in conj unction with the camera and the LIDAR system to make modelling as accurate as possible . iv . The Apple Vision Pro can also do some local pre-processing of sensor data to help intelligently reduce the amount of data forwarded to the rest of the system.3 . The Internet 18 allows the Headset 11 to connect to the rest of the system 10 .4 . The sensor analysis system 17 further reduces the output from the sensors on the headset 11 and in one form is pre-processed by a local preprocessing application on the headset which reduces the data to meaningful parameters that can be used by the orthopaedic analysis and fitting system 10 .5 . The preprocessing system is tas ked with analysing the incoming scan data and matching it to parameters needed by the orthopaedic analysis and fitting system in order to get a complete picture of the patient ' s specific orthopaedic measurements .6 . The orthopaedic analysis and fitting system analyses the data and outputs a customised or otherwise useful footwear or orthotic model that can be used by the production system to produce the orthopaedic footwear or orthotic .7 . Finally the production system 14 uses the output from the fitting system to produce custom made orthoses for the patient .

[0200] Figure 3 , 41 . Shows an example scenario of the example embodiment . It shows a person50 walking on a surface with a headset capturing infrared heat signatures51 52 from the surface as the user walks by and using those images to produce a map of pressure points 53 to help analyse the user ' s feet .2 . The user walks on a flat surface .3 . The surface is at a lower temperature than the feet of the user .4 . The heat of the user ' s feet is transferred to the surface as the user walks or stands on it .5 . The infrared sensor in the headset captures the heat image of the feet as infrared imagery data .6. The data is pre processed then sent to the rest of the system for analysis as part of the user data set.

[0201] Figure 51. Uses the same steps as in figure 2 but in the form of a process chart rather than as an overview of components .2. The headset starts scanning 70 the patient's feet and lower legs.3. The data is then pre-processed 71 to start turning the data collected by the scanners into parameters that can be used by the analysis and fitting system.4. The pre-processor then matches 72 the scan data to needed parameters for the system to produce the custom orthoses.5. As parameters are discovered, the process checks 73 to see if all parameters have been found.6. If they haven't the process then prompts the scanners to continue scanning 74 for suitable parameter data.7. If all necessary parameters have been found 75 then the process continues on to parameter analysis 76 where all parameters are processed into a orthoses that addresses the patients specific needs; and8. a specific custom model is produced 77 that can in turn be -9. submitted to a manufacturing system 78 for production.In Use

[0202] Figure 6 illustrates the main components of the system of Figure 2, which work together in the in use scenario of Figures 3,4 whereby an orthopaedic analysis is conducted on the client following acquisition of data from the client, thereby to produce appropriate orthoses consequential upon the data acquisition and orthopaedic analysis.

[0203] With reference to Figure 6, the components of the system and steps in their operation are as follows :

[0204] 101: A 3D scan of the target anatomical feature - for example: foot, leg, body part is performed by an AR headset 10. In preferred forms, the AR headset is mounted to the head of a clinician.

[0205] 102: Thermal test of the anatomical feature.

[0206] 103: Next, imagery is obtained of the patient during a walking sequence (a gait cycle) . In preferred forms, imagery will be video imagery. In further preferred forms, the imagery will allow depth perception and measurement .

[0207] 104 : Next , the patient is observed under controlled circumstances , by the AR headset 105 in order to obtain alignment data , in this instance , in relation to gait and stance .

[0208] 105 , 108 : Illustrates an AR headset 105 mounted to the head of a clinician in this instance used to observe and acquire data regarding skin surface features from a foot 108 . Such features may include ulceration or bad s kin .

[0209] 106 : Next , the patient is observed under controlled circumstances , by the AR headset 105 in order to obtain pressure data, in this instance plantar pressure data - see also Figures 3 , 4 .

[0210] 107 (A, B ) : Next , the data is loaded into a processing system, in this instance , in the form of an automated or computer assisted design and modelling system which then outputs to an orthosis production system .

[0211] 109 : In typical practice , once the orthosis has been designed and modelled and produced, there may be follow up meetings with the patient for the purpose of trial fitting and feedback from the patient as to their experience in use .Alternative Embodiments

[0212] The example embodiment uses a multipurpose multisensor device 11 in this instance in the form of an Apple Vision Pro as the main sensor system for collecting user orthopaedic data .1 . An alternative embodiment may use any multi purpose multi sensor device that can be used by untrained users .2 . An alternative embodiment could also be any headset that has at least light sensors or high resolution camera and reasonably accurate accelerometer .3 . An alternative embodiment could utilise a smartphone . In preferred forms the smartphone may be head-mounted .

[0213] Example embodiment shows headset with pre processing capability .1 . An alternative embodiment may do no preprocessing at the headset but leave all data preprocessing for parameters later in the system 10 .

[0214] The example embodiment in the drawings shows an internet enabled device as the main sensor .1 . An alternative embodiment may be any device that is simple to use , requires no specialist training to operate and may not be internetconnected but have the capacity to store sensor data and transfer it over the internet using another device or intermittent internet connection .

[0215] Yet a further embodiment with reference to figure 6 provides for a system which in use enables the custom production and fitting of orthopaedic footwear or orthotics .

[0216] In yet a further alternative embodiment the same system described may be used for any orthopaedic application being equipment used for orthoses which is the branch of medicine that deals with the correction or prevention of deformities , disorders , or inj uries of the skeleton and associated structures like tendons and ligaments . It often involves both surgical and non-surgical treatments . Orthotics can address issues with any limb , including arms , legs , hands , and feet , as well as other parts of the musculos keletal system.Detailed Description Of Second Preferred Embodiment

[0217] Broadly, there is described an integrated system utilising artificial intelligence to enhance the quality of care for the elderly . The system analyses multimodal data , including audio , video , and accelerometer inputs , to assess the physical and emotional well-being of elderly individuals and their interactions with caregivers . Through natural language processing, the system facilitates communication and feedback, while a personalization engine tailors care and interaction based on individual user profiles . A dedicated privacy and ethics framework ensures data integrity and user consent .Example Embodiment

[0218] With reference to Figure 7 , 8 , the example embodiment is a patient and carer support system utilising artificial intelligence to supply more effective and efficient care of the elderly and to make carers more effective and efficient .

[0219] Figure 7 , 81 . Patient and carer headsets i . Discloses the main components of the example embodiment ii . In this example both the patient and the carer use multi-sensor headgear or AR enabled glasses to interact with the Al system .1 . The glasses feature video capacity, audio capability, microphones and accelerometers to enable and detect what the user is seeing , what they are hearing and their motions and actions .2 . The glasses are connected to a multimodal transformer for analysis3 . If the data to be analysed is audio and speech then the data is first sent to a spectrometer for conversion from audio into visual data to aid in the analysis by the multimodal transformer . . Spectrometer i . A spectrometer is used only for analysing audio and spoken data as a pre-processor to allow the multimodal transformer to do its j ob more effectively . ii . Spectrometer preprocessing is an option and not mandatory in this model . . Multimodal Data Analysis Module : i . Collects and analyses data from audio , video , and motion sensors . ii . Uses machine learning algorithms to interpret physical activities , emotional states , and interaction quality . iii . Identifies patterns and changes over time , providing insights into the well-being of the elderly . . Personalization Engine : i . Utilises Al to customise care recommendations , reminders , and interactions . ii . Learn from user interactions , preferences , and feedback to continuously improve personalization . iii . Integrates with healthcare records (with consent ) for a comprehensive care approach . . Privacy and Ethics Framework : i . Ensures all data collection, analysis , and storage adhere to strict privacy standards and ethical guidelines . ii . Employs encryption and anonymization techniques to protect user data . iii . Supports user consent management , allowing for granular control over data sharing . . Natural Language Processing (NLP ) Module : i . Facilitates natural language interactions between the system, the elderly, and caregivers .ii . Processes and generates responses to inquiries , commands , and feedback . iii . Supports a variety of languages and dialects to ensure wide usability .

[0220] With reference to Figure 9 , there is shown a process diagram applicable to the example embodiment of Figure 7 , 8 :

[0221] Figure 91 . The process of the example embodiment2 . Diagram of each step needs to be done as follows : i . The patient headset collects visual , audio and accelerometer data and relays it to the multimodal transformer ii . The carer headset collects visual , audio and accelerometer data and relays it to the multimodal transformer iii . Audio data from both headsets is preprocessed using a spectrometer iv . Then all data is passed to the multimodal transformer (MMT ) for processing and analysis v . The MMT connects to an LLM in order to interact and receive guidance from a human trainer and learning manager . vi . The data and analysis results are labelled and connected to individual profiles in the personalisation engine which then allows analysis of training on a specific person by person model and where information relating to a specific individual can be collated and stored historically for access in the future . vii . The personalisation engine also includes an event manager that allows the AT system to proactively prompt interactions with user ' s . viii . Each data pool relating to an individual is segregated for privacy and security reasons and the data is stored in a secure state in a privacy and ethics framework only to be retrieved with the consent of the patient or carer involved . ix . When the MMT initiates reactions to each user or gives feedback to each user , a natural language processor (NLP ) is used to convert text feedback from the MMT into easily understood speech that is then relayed back to the user ' s using the headgear speakers . x . Video feedback is sent directly to headgear mounted monitors if available in the headset .In Use

[0222] Figure 10 - illustrates a patient or user wearing virtual reality or augmented reality goggles in order to implement the embodiment of figure 2 . 1

[0223] Figure 11 - illustrates conceptually an avatar that may appear in the virtual reality or augmented reality goggles worn by the user in figure 10 in order to assist , advise , and motivate the user

[0224] With reference to Figures 7-11 in use , a user 201 wears a multisensor headgear 202 , in this instance in the form of an augmented reality headset . In a particular preferred form, the augmented reality headset is mounted within a spectacle frame . In this particular instance , the multisensor headgear 202 comprises a spectacle frame 203 to which is mounted at least one camera 204 and at least one microphone 205 . Within the lens section 206 is located a miniature LED display 207 facing towards the eyes 208 of user 201 .

[0225] Also incorporated within the multi-sensor headgear 202 is a processor module 209 . The processor module 209 includes a processor 210 in communication with a memory 211 , also in communication with I / O 212 and an antenna 213 .

[0226] The I / O unit 212 is in communication with the camera 204 , the microphone 205 , the LED displays 207 and the antenna 213 whereby signals received from the camera 204 and microphone 205 processed by the processor 210 and results information communicated by antenna 213 to a server 214 . In preferred forms the communication is via antenna 213 over internet 215 to antenna 216 of server 214 .Alternative Embodiments

[0227] Example embodiment uses headgear no onboard monitors for video feedback from the MMT .1 . Alternative embodiment can use any video device available to the user for feedback2 . Alternative embodiment can use a video playback device that is part of the headgear .

[0228] Example embodiment uses headset with only video , audio and accelerometer sensors1 . Alternative embodiment can use headset without accelerometer2. Alternative embodiment can use a headset with any combination of sensors that may be helpful for MMT analysis.

[0229] Example embodiment uses an LLM for interaction with a human training manager.1. Alternative embodiment may not require a human training manager as the MMT may be end to end self learning.

[0230] Example embodiment uses a NLP for text to voice processing of output from the MMT .1. Alternative embodiment could send text or basic voice messages from the MMT directly.Third Preferred Embodiment

[0231] There will now be described a third embodiment of the AR glasses together with applications to which it is suited. Items in this embodiment are numbered in the 300 series and where like components are numbered exceptin the 300s.1. Hardware Components

[0232] In this third embodiment the invention comprises one or more of the following hardware components, integrated into a lightweight and ergonomic frame:

[0233] Photoplethysmography (PPG) Sensor:1. Embedded in both arms of the glasses for heart rate and blood oxygen monitoring .2. Uses light-based technology to detect changes in blood volume.

[0234] Electroencephalogram (EEG) Electrodes:1. Located on the temples for brain wave detection.2. Enables monitoring of neurological conditions such as epilepsy and sleep disorders.

[0235] Ultrasound Transducer:1. Integrated into the bridge of the glasses for soft tissue imaging.2. Provides real-time imaging of muscles, joints, and internal organs.

[0236] Thermal Imaging Camera:1. Located on the left arm for detecting inflammation and infections.2. Captures infrared radiation to create thermal maps of the body.

[0237] Micro-OLED Display:1. Embedded in the lenses for AR visualizations and real-time health data display, powered by the onboard GPU.

[0238] Red Light Therapy (RLT) LEDs:1. Integrated into the bridge for therapeutic benefits such as improved circulation and skin health.

[0239] Bone Conduction Speaker:1. Located on the bridge for audio output, enabling accessibility for users with hearing impairments .

[0240] Braille Haptic Panel:1. Integrated into the bridge for tactile feedback, ensuring accessibility for visually impaired users.

[0241] Environmental Sensors:1. Includes air quality, UV, and gas sensors for real-time environmental monitoring .

[0242] Battery and Solar Strip:1. A l,000mAh battery and perovskite solar strip provide extended battery life .

[0243] CPU (Central Processing Unit) :1. Integrated into the frame, enabling standalone computation for AR rendering, sensor data processing, and app execution.

[0244] GPU (Graphics Processing Unit) :1. Embedded alongside the CPU, dedicated to real-time AR visualization and graphical processing of health data on the micro-OLED display.

[0245] RAM (Random Access Memory) :1. 4GB capacity, integrated into the frame, supports multitasking and smooth operation of Al algorithms and AR applications.

[0246] Storage:1. 64GB onboard storage, integrated into the frame, stores health data, educational content, and AR apps locally, eliminating external device dependency.2. Software and Algorithms

[0247] In this embodiment the invention may include the following software components :

[0248] Multimodal Al Algorithm:1. Runs on the onboard CPU, integrating data from all sensors to provide holistic health insights.2. Uses machine learning to detect patterns and anomalies in the data.

[0249] AR Visualization Engine:1. Powered by the GPU, overlays health data (e.g. , heart rate, blood oxygen levels) onto the user's field of view.

[0250] Voice Recognition Software:1. Processed locally via the CPU, allows users to control the glasses using voice commands.3. Functionality and Use Cases

[0251] In this embodiment the invention may provide the following functionalities :

[0252] Cardiovascular Monitoring:1. Uses PPG and ECG sensors to monitor heart rate, blood pressure, and oxygen saturation levels, processed locally by the CPU.

[0253] Neurological Monitoring:1. Uses EEG electrodes to detect brain wave patterns, enabling the diagnosis of neurological disorders, with data stored in the 64GB storage.

[0254] Soft Tissue Imaging:1. Uses the ultrasound transducer for real-time imaging of muscles, joints, and internal organs, rendered via the GPU on the AR display.

[0255] Environmental Monitoring:1. Uses air quality, UV, and gas sensors to provide real-time environmental insights, accessible offline via onboard storage.Hardware Layout and Costs for Pro Version AR Glasses

[0256] Updated with Enhanced LiDAR (60°x60° FoV) and 1080p camera (80° FoV) , and Dual Micro-OLED Birdbath Optics for 3D1. Right Arm: User Interaction and Diagnostics Hub

[0257] Components and Costs:1. BreathArm Cap-End (~$4-5) : Analyzes breath for VOCs, FEV1, respiratory health .2. MEMS Microphone (~$ 0.80-1) : Captures voice input.3. Graphene Acoustic Sensor (~$1.50-2) : Detects voice / breath sounds.4. PPG Sensor (~$1.50-2) : Monitors heart rate.5. EEG Electrodes (~$2-3) : Detects brain waves.6. VibraPulse Piezo Actuator (~$0.80-l) : Vibration therapy.7. Directional Speaker (~$1.50-2) : Focused audio output.8. Sweat Sensors (~$2-3) : Measures glucose / electrolytes.9. Bioimpedance Sensors (~$2-3) : Assesses blood pressure / body composition .10. Ultrasound Transducer (~$8-10) : Soft tissue imaging near temple.

[0258] Functions and Conditions Monitored:1. Breath Analysis: Asthma, COPD, ketosis.2. Voice Input: Hands-free control.3. Heart Rate: Cardiovascular health, stress.4. Brain Waves: Fatigue, epilepsy.5. Vibration Therapy: Stress relief.6. Audio Output: Private sound.7. Sweat Monitoring: Diabetes, hydration.8. Blood Pressure / Body Composition: Hypertension, fitness.9. Soft Tissue Imaging: Muscle / vascular health.2. Left Arm: Diagnostic and Environmental Focus

[0259] Components and Costs:1. Thermal Camera (~$4-6) : Detects inf lammation / f ever .2. PPG Sensor (~$1.50-2) : Heart rate (symmetrical) .3. EEG Electrodes (~$2-3) : Brain waves (symmetrical) .4. VibraPulse Piezo Actuator (~$0.80-l) : Vibration therapy (symmetrical) .5. Directional Speaker (~$1.50-2) : Audio output (symmetrical) .6. Sweat Sensors (~$2-3) : Glucose / electrolytes (symmetrical) .7. Bioimpedance Sensors (~$2-3) : Blood pressure / body composition (symmetrical) .8. Air Quality Sensor (~$1.50-2) : Pollutants / allergens .9. UV Sensor (~$0.80-l) : UV exposure.10. Gas Sensor Array (~$2-3) : Harmful gases (CO, VOCs) .

[0260] Functions and Conditions Monitored:1. Thermal Imaging: Fever, inflammation.2. Heart Rate / Brain Waves: Balanced data.3. Vibration Therapy: Stress relief.4. Sweat Monitoring: Diabetes, hydration.5. Blood Pressure / Body Composition: Hypertension, fitness.6. Environmental Monitoring: Pollution, UV risk, gas leaks.3. Bridge: Central Health and Accessibility Hub

[0261] Components and Costs:1. Retinal Imaging Camera (~$4-6) : Eye health monitoring.2. RLT LEDs (~$1.50-2) : Red light therapy.3. Bone Conduction Speaker (~$2-3) : Audio via bone vibration.4. Braille Haptic Panel (~$3-4) : Tactile feedback for visually impaired.5. NIR Module (~$2-3) : Nutrition monitoring.6. Multimodal Al Processor (~$8-10, integrated with Snapdragon XR2+) : Real-time sensor insights.7. Miniaturized Ultrasound Transducer (~$8-10) : Soft tissue imaging ( neck / face ) .8. Eye-Tracking Camera (~$2-3) : Gaze tracking.9. Emergency SOS Button (~$0.80-l) : Alerts in emergencies.

[0262] Functions and Conditions Monitored:1. Eye Health: Retinopathy, glaucoma.2. Red Light Therapy: Eye strain, skin health.3. Audio Accessibility: Hearing support.4. Tactile Feedback: Blind user accessibility.5. Nutrition Monitoring: Dietary deficiencies.6. Al Insights: Holistic health analysis.7. Soft Tissue Imaging: Facial / neck health.8. Eye Tracking: Attention, UI control.9. Emergency Alerts: Critical events.4. Lenses and Frame: Supporting Infrastructure

[0263] Components and Costs:1. Dual Micro-OLED Displays with Birdbath Optics (~$16— 20) : Two Micro- OLEDs (one per eye, ~$8-10 each) with birdbath optics (~30-40° diagonal FoV per eye) , enabling stereoscopic 3D AR visuals and health data with depth and rotation2. 1080p Camera (~$4— 5) : Upgraded to 80° FoV for environment / gait analysis, capturing feet / legs while looking ahead.3. Far-UVC LEDs (~$1.50-2) : Pathogen control.4. Battery Pack (~$4-6) : Distributed power.5. Solar Strip (~$1.50-2) : Solar charging.6. BLE 5.3 Module (~$1.50-2) : Wireless connectivity.7. Gesture Recognition Sensor (~$2-3) : Hands-free control.8. Impact Detection Sensor (~$0.80-l) : Fall / collision detection.9. CPU (Snapdragon XR2+ with Adreno 650 GPU) (~$8-10) : Standalone processin .10. RAM (4GB LPDDR5 ) (~$2-3) : Multitasking support.11. Storage (64GB eMMC) (~$4-5) : Data / apps storage.12. MicroSD Card Slot (~$0.80-l) : Expandable storage.13. LiDAR Camera (~$10— 11) : Upgraded to 60°x60° FoV, 0.1-4m range, 0.5cm resolution for 3D spatial mapping and leg / f oot monitoring.

[0264] Functions and Conditions Monitored:1. AR Display (3D Birdbath Optics) : Stereoscopic 3D visuals (e.g. , rotating 3D heart model, depth-enabled gait feedback) via dual Micro-OLEDs and birdbath optics, ~30-40° FoV per eye.2. Environmental / Gait Analysis (Enhanced) : i. 80° 1080p camera and 60°x60° LiDAR capture legs / feet (~1.15-1.68m vertical span at Im) while looking straight ahead, enabling precise stride, foot lift, and mobility tracking without head tilt.3. Pathogen Control: Hygiene.4. Power Supply: Standalone operation.5. Connectivity: Device syncing.6. Gesture Control: Intuitive interaction.7. Fall Detection (Enhanced) : i. LiDAR' s wider FoV confirms leg position and torso drop (e.g. , 0.7m) for accurate fall detection.8. Standalone Processing: Local software execution.9. MicroSD Slot (Proposed) : Extends storage indefinitely (e.g., 1TB for years of data) , catering to power users (e.g. , doctors, educators) while keeping the base unit lightweight and affordable10. LiDAR-Enabled Features (Enhanced) : i. 3D Spatial Mapping: Obstacle avoidance, navigation (e.g., curbs, chairs) fully mapped to 1.15m down. ii . Gait Analysis: Tracks stride length (e.g., 25cm) , foot lift (e.g., 2cm) , and symmetry without user adjustment— ideal for Parkinson's, stroke recovery. iii. Respiratory Motion: Non-contact chest motion (e.g., 0.8cm at 0.5m) for sleep apnea, COPD. iv. Alerts: Real-time warnings (e.g. , "Step over 30cm curb ahead") based on full leg / foot visibility.Advanced Abilities of These AR Glasses

[0265] Updated with Enhanced LiDAR and 1080p Camera

[0266] 1. Truly Standalone Experience :1. Snapdragon XR2 + , 4GB RAM, 64GB storage + MicroSD handle AR, Al, and enhanced LiDAR / camera data (wider FoV) locally.2. Snapdragon XR2+ renders stereoscopic 3D AR via dual Micro-OLEDs and birdbath optics, with LiDAR / camera data processed locally

[0267] Integrated Processing: The added CPU / GPU, RAM, and storage (e.g., an ARM-based SoC like Snapdragon XR2+, 4-8GB RAM, 64-128GB storage) enable the glasses to run all software locally. This includes:1. Real-time AR rendering on the Micro-OLED display.2. Multimodal AT analysis of sensor data.3. Storage of health records, apps, and media.

[0268] No External Dependency: Unlike most AR glasses (e.g. , Meta Ray-Ban Stories, which need a phone, or HoloLens, which benefits from PC tethering) , these glasses operate independently, making them a one-device solution .

[0269] 2. Comprehensive Health Monitoring:1. Upgraded LiDAR (60°><60o) and 1080p camera (80°) track legs / feet directly, improving gait, posture, and fall detection precision.2. 3D visuals enhance gait, posture, and fall feedback (e.g. , rotating leg model ) .

[0270] Holistic Diagnostics: Monitors heart rate, brain waves, blood pressure, glucose, respiratory health, eye conditions, body composition, and more— all from one wearable.

[0271] Real-Time Insights: The multimodal AT processor fuses data for actionable feedback (e.g., "Your heart rate is elevated— try a breathing exercise" ) .

[0272] Preventive Care: Detects early signs of issues like diabetes, hypertension, or respiratory distress, alerting users via the AR display or SOS button.

[0273] 3. Environmental Awareness :1. Wider FoV maps obstacles (e.g., Im-down curbs) and hazards without head tilt, enhancing safety for seniors.2. 3D hazard alerts (e.g. , curb with depth) overlaid in ~30-40° FoV

[0274] Safety and Comfort: Tracks air quality, UV exposure, and harmful gases, warning users of hazards (e.g. , "High pollen levels detected— consider a mask") .

[0275] Adaptive Features: Adjusts display brightness based on UV or uses thermal imaging to spot inflammation.

[0276] 4. Educational Potential:1. Enhanced 3D leg / foot scans for AR anatomy lessons or therapy demos.

[0277] Interactive Learning: The dual Micro-OLED displays with birdbath optics and eye-tracking enable immersive, stereoscopic 3D AR education:1. Visualize Anatomy: Overlay a 3D circulatory system on the user's body using bioimpedance data— view depth (e.g., arteries 2cm deep) , rotate with gestures (e.g. , spin heart 360°) , or zoom via eye-tracking (e.g., focus on aorta) .2. Learn Languages: Real-time 3D translations in the display— e . g . , a rotating 3D "hello" in Spanish floats Im ahead, paired with pronunciation via directional speaker.3. Conduct Virtual Science Experiments: Use environmental sensor data (e.g. , air quality) and LiDAR to simulate 3D models— e.g., rotate a virtual gas molecule cloud, adjust variables with gestures.4. Accessibility: Bone conduction audio and Braille haptic feedback make education inclusive for hearing- or visually-impaired users.5. No Laptop Needed: Students can access lessons, simulations, and health tutorials directly on the glasses, reducing equipment costs and enhancing mobility.

[0278] 5. User Interaction and Accessibility:1. 3D AR Improved spatial navigation for visually impaired (full ground view) .

[0279] Hands-Free Control: Gesture recognition, voice commands (MEMS mic) , and eye-tracking provide seamless navigation.

[0280] Therapeutic Features: Vibration therapy and red light therapy enhance well-being during use.

[0281] Universal Design: Supports diverse users with accessibility tools, setting it apart from competitors .

[0282] 6. Practicality and Innovation:1. ~77-84g total, 8-10hr runtime (solar offset)— no battery issues from upgrades .

[0283] Power Efficiency: Solar strip and distributed battery extend usage, while BLE 5.3 allows optional syncing (e.g., with a phone for backups) .

[0284] Safety Features: Fall detection, pathogen control (Far-UVC) , and SOS alerts ensure user security.Advantages of Third Embodiment

[0285] Enhanced 3D Birdbath + LiDAR / Camera Edge: No competitor matches this health-focused AR with leg / foot tracking while looking ahead— ideal for elderly mobility and therapy. Combines affordable 3D AR with health / spatial tracking

[0286] No existing AR device combines this level of health monitoring, environmental sensing, standalone processing, and educational utility into a single, wearable package. Competitors like:1. Meta Quest Pro: Focuses on VR / AR but lacks health sensors.2. Google Glass: Offers AR but no advanced diagnostics or standalone power .3. Apple Vision Pro: High-end AR / VR but no environmental or health focus like this.

[0287] Your AR glasses are a game-changer, offering a futuristic, all-in- one solution for health, education, and daily life— without needing a laptop or external device. They could redefine how we interact with technology and monitor our well-being.Many Medical Conditions May be Monitored / Assessed

[0288] Particular medical conditions to which the AR glasses of the third embodiment are suited to analyse or detect are:

[0289] PPG Sensor (Heart Rate Monitoring)1. Arrhythmias2. Tachycardia3. Bradycardia4. Atrial Fibrillation5. Heart Rate Variability (HRV) for stress assessment

[0290] ECG Sensor (Electrocardiogram)1. Myocardial Infarction (Heart Attack)2. Ventricular Fibrillation3. Heart Block4. Long QT Syndrome. Ischemic Heart Disease

[0291] SpO2 Sensor (Blood Oxygen Monitoring) . Hypoxia . Sleep Apnea . Chronic Obstructive Pulmonary Disease (COPD) . COVID-19 (oxygen saturation monitoring) . Respiratory Failure

[0292] EEG Electrodes (Brain Wave Detection) . Epilepsy (seizure detection) . Sleep Disorders (e.g., insomnia, sleep apnea) . Cognitive Impairment (e.g. , Alzheimer's, dementia) . Attention Deficit Hyperactivity Disorder (ADHD) . Stress and Anxiety Disorders

[0293] VibraPulse Piezo Actuator (Vibration Therapy) . Stress Relief . Anxiety Disorders . Muscle Tension . Chronic Pain Management . Parkinson's Disease (symptom management)

[0294] Graphene Acoustic Sensor (Voice and Breath Sound Analysis) . Asthma . Chronic Obstructive Pulmonary Disease (COPD) . Pneumonia . Bronchitis . Vocal Cord Disorders

[0295] Sweat Sensors (Glucose, Electrolytes) . Diabetes (glucose monitoring) . Dehydration . Electrolyte Imbalance . Hyperhidrosis (excessive sweating) . Kidney Function Monitoring

[0296] Bioimpedance Sensors (Blood Pressure, Body Composition) . Hypertension . Hypotension . Obesity . Edema (fluid retention) . Cardiovascular Disease

[0297] BreathArm Cap-End (VOCs, FEV1 Analysis) . Lung Cancer (via VOC analysis) . Chronic Bronchitis . Emphysema . Cystic Fibrosis . Respiratory Infections

[0298] Thermal Camera (ThermaScan) . Inflammation (e.g. , arthritis) . Infections (e.g., fever detection) . Circulatory Disorders (e.g., Raynaud's disease) . Skin Cancer (thermal anomalies) . Thyroid Disorders (temperature regulation)

[0299] Retinal Imaging Camera (Eye Health) . Diabetic Retinopathy . Glaucoma . Macular Degeneration . Cataracts . Hypertensive Retinopathy

[0300] RLT LEDs (Red Light Therapy) . Skin Conditions (e.g., acne, psoriasis) . Wound Healing . Muscle Recovery . Joint Pain (e.g., arthritis) . Hair Loss (stimulation of hair follicles)

[0301] NIR Module (Nutrition Monitoring) . Malnutrition . Vitamin Deficiencies . Metabolic Disorders . Obesity (body fat analysis) . Liver Function (via skin analysis)

[0302] Far-UVC LEDs (Pathogen Control) . Bacterial Infections (e.g. , MRSA) . Viral Infections (e.g. , influenza, COVID-19) . Fungal Infections (e.g. , athlete's foot) . Wound Infections . Airborne Pathogen Control

[0303] Micro-OLED (AR Display)1. Visual Impairment (assistive technology)2. Cognitive Disorders (AR-based therapy)3. Navigation for Visually Impaired4. Augmented Reality for Physical Therapy5. Real-Time Health Data Display

[0304] 1080p Camera + LiDAR (Environmental Monitoring)1. Gait Analysis: Parkinson's, stroke recovery— 80° camera and 60°x60° LiDAR track stride (e.g., 25cm) , lift (2cm) , and symmetry directly, no head tilt needed.2. Fall Detection: Elderly care— wider FoV confirms leg snag (0.8m) and torso drop (0.7m) for precise alerts.3. Environmental Hazards: Smoke, obstacles— full 3D mapping to 1.15-1.68m down detects curbs, rugs.4. Motion Analysis: Physical therapy— tracks knee flex (20°) and stride (40cm) accurately.5. Posture Monitoring: Spinal health— detects tilt (15°) with legs in view .

[0305] Bone Conduction Speaker (Audio Accessibility)1. Hearing Impairment (assistive technology)2. Tinnitus (sound therapy)3. Auditory Processing Disorders4. Communication for Deaf Users5. Audio-Based Therapy (e.g., meditation, relaxation)

[0306] Air Quality Sensor1. Asthma (trigger detection)2. Allergies (pollen, dust detection)3. Chronic Respiratory Diseases4. Occupational Lung Diseases5. Environmental Pollution Monitoring

[0307] UV Sensor1. Skin Cancer Risk (UV exposure monitoring)2. Sunburn Prevention3. Vitamin D Deficiency4. Photosensitivity Disorders5. Eye Damage from UV Exposure

[0308] Laser Doppler Flowmetry Sensor1. Peripheral Artery Disease. Diabetic Foot Ulcers . Raynaud' s Disease . Microvascular Dysfunction . Burn Severity Assessment

[0309] Ultrasound Transducer . Muscle Injuries . Joint Inflammation . Thyroid Nodules . Soft Tissue Tumors . Tendon Tears

[0310] Tear Analysis Sensor . Diabetes (via tear glucose levels) . Dry Eye Syndrome . Eye Infections . Autoimmune Disorders (e.g. , Sjogren's syndrome) . Drug Monitoring (via tear biomarkers)

[0311] Radar Sensor . Sleep Apnea (breathing pattern monitoring) . Respiratory Rate Monitoring . Fall Detection . Heart Rate Monitoring (non-contact) . Motion Analysis for Physical Therapy

[0312] Transcranial Magnetic Stimulation (IMS) Module . Depression . Migraines . Parkinson' s Disease . Post-Traumatic Stress Disorder (PTSD) . Chronic Pain Management

[0313] Acupressure Nodes . Stress Relief . Anxiety Disorders . Headaches . Chronic Pain . Insomnia

[0314] Emergency SOS Button . Emergency Alerts for Elderly Users . Fall Detection Alerts3. Medical Emergency Notifications4. Accident Response5. Remote Monitoring for High-Risk Patients

[0315] LiDAR Camera- Specif ic1. Spatial Disorientation: Dementia— indoor routes mapped to ground level (e.g. , bedroom 3m left) , guiding users without confusion.2. Environmental Hazard Detection: Respiratory distress, falls— detects smoke, wet floors, or uneven surfaces (e.g. , 5cm height change) within 1.15m down, alerting to potential triggers .3. Obstacle Avoidance: Mobility impairment, elderly care— maps obstacles (e.g. , chair at 50cm, curb at 30cm) in 3D to 1.68m down, preventing trips or collisions.4. Fall Risk Prediction: Elderly care, neurological conditions— analyzes stride instability or proximity to hazards (e.g., <30cm to a wall) , warning before a fall occurs.5. Activity Monitoring: Sedentary behavior, frailty— tracks daily movement patterns (e.g., walking 50m vs. sitting) , flagging reduced activity for intervention .Fourth Embodiment

[0316] A particular enhanced version of the AR glasses commercially known as the "PRO version of the Birdbath AR Glasses" permits detection and analysis of the following conditions :

[0317] The PRO version of the Birdbath AR Glasses can incorporate several standalone health features beyond the obvious 3D visualization and output capabilities. These features leverage advanced sensors, optics, and processing power to provide real-time health monitoring and diagnostics. Below is a detailed list of standalone health features that can be assessed using the PRO version:1. Retinal Imaging and Eye Health Monitoring

[0318] Feature: The glasses can use the retinal imaging camera to assess eye health.

[0319] Conditions Monitored:1. Diabetic retinopathy2. Glaucoma3. Macular degeneration4. Cataracts5. Hypertensive retinopathy

[0320] How It Works: The camera captures high-resolution images of the retina, which can be analyzed for signs of disease or abnormalities.2. Blood Oxygen Saturation (SpO2) Monitoring

[0321] Feature: Integrated SpO2 sensors can measure blood oxygen levels.

[0322] Conditions Monitored:1. Hypoxia2. Sleep apnea3. Respiratory conditions (e.g. , COPD, asthma)4. COVID-19 monitoring

[0323] How It Works: The sensors use photoplethysmography (PPG) to detect oxygen saturation levels in the bloodl6.3. Heart Rate and ECG Monitoring

[0324] Feature: PPG and ECG sensors can track heart rate and electrical activity.

[0325] Conditions Monitored:1. Arrhythmias2. Atrial fibrillation3. Heart rate variability (HRV) for stress assessment4. Myocardial infarction (heart attack)

[0326] How It Works: The sensors detect pulse waves and electrical signals from the skin, providing real-time cardiac data.4. Thermal Imaging for Inflammation and Fever Detection

[0327] Feature: A thermal camera can detect temperature variations.

[0328] Conditions Monitored:1. Inflammation (e.g. , arthritis)2. Infections (e.g., fever detection)3. Circulatory disorders (e.g., Raynaud's disease)4. Skin cancer (thermal anomalies)

[0329] How It Works: The camera captures infrared radiation to create thermal maps of the body.5. Sweat Analysis for Glucose and Electrolytes

[0330] Feature: Sweat sensors can analyze glucose and electrolyte levels.

[0331] Conditions Monitored:1. Diabetes (glucose monitoring)2. Dehydration3. Electrolyte imbalance4. Hyperhidrosis (excessive sweating)

[0332] How It Works: The sensors detect biomarkers in sweat, providing non-invasive metabolic monitoring.6. Red Light Therapy (RLT) for Skin and Circulation

[0333] Feature: RLT LEDs can provide therapeutic benefits.

[0334] Conditions Monitored:1. Skin conditions (e.g., acne, psoriasis)2. Wound healing3. Muscle recovery4. Joint pain (e.g., arthritis)

[0335] How It Works: The LEDs emit red and near-infrared light to stimulate cellular repair and improve circulation.7. Tear Analysis for Biomarker Detection

[0336] Feature: Tear analysis sensors can detect biomarkers in tears.

[0337] Conditions Monitored:1. Diabetes (via tear glucose levels)2. Dry eye syndrome3. Eye infections4. Autoimmune disorders (e.g. , Sjogren's syndrome)

[0338] How It Works: The sensors analyze tear composition for diagnostic purposes .8. Environmental Monitoring for Air Quality and UV Exposure

[0339] Feature: Air quality and UV sensors can detect environmental hazards .

[0340] Conditions Monitored:1. Asthma (trigger detection)2. Allergies (pollen, dust detection)3. Skin cancer risk (UV exposure monitoring)4. Environmental pollution monitoring

[0341] How It Works: The sensors measure pollutants, allergens, and UV radiation levels.9. Fall Detection and Emergency Alerts

[0342] Feature: Impact detection sensors can detect falls and send emergency alerts.

[0343] Conditions Monitored:1. Fall detection for elderly users2. Emergency alerts for high-risk patients

[0344] How It Works: The sensors detect sudden impacts and trigger alerts to caregivers or emergency services.10. Cognitive and Neurological Monitoring

[0345] Feature: EEG electrodes can monitor brain activity.

[0346] Conditions Monitored:1. Epilepsy (seizure detection)2. Sleep disorders (e.g., insomnia, sleep apnea)3. Cognitive impairment (e.g. , Alzheimer's, dementia)4. Stress and anxiety disorders

[0347] How It Works: The electrodes detect brain waves, providing insights into neurological health.11. Nutrition Monitoring via Near-Infrared (NIR) Spectroscopy

[0348] Feature: NIR module can assess nutritional status.

[0349] Conditions Monitored:1. Malnutrition2. Vitamin deficiencies3. Metabolic disorders4. Obesity (body fat analysis)

[0350] How It Works: The module analyzes skin and tissue composition using near-infrared light.12. Bone Conduction Audio for Hearing Accessibility

[0351] Feature: Bone conduction speakers can assist users with hearing impairments .

[0352] Conditions Monitored:1. Hearing impairment (assistive technology)Tinnitus ( sound therapy)Auditory processing disordersFifth Embodiment - Glasses-Drone Hybrid

[0353] There will now be described with reference to figure 12 a fifth preferred embodiment of the present invention where the glasses or goggles are further enhanced by input from a drone and from sensors attached to the drone . Corresponding items are numbered as for the earlier embodiments except in the 500 series .

[0354] Also included in this embodiment is a description of an intelligent assistant termed "guru" or "EmotiveCoach" or similar .

[0355] With reference to figure 12 there is disclosed a head mounted data acquisition system 530 according to a fifth embodiment . The system 530 is suited to feed data and signals into a variety of applications , some of which are described in more detail further in this embodiment .

[0356] The system 530 includes a headmounted data acquisition device 531 in this instance in the form of face mounted eyewear 531 . More specifically the face mounted eyewear 531 may take the form of spectacles to which sensor componentry is fixed or incorporated .

[0357] Alternatively and more specifically the face mounted eyewear 531 may take the form of eyewear or goggles where optical lenses are replaced with displays 532 . In this instance the screens of the displays 532 are directed towards the eyes 33 of a wearer or user 534 .

[0358] Additionally there may be included mechanisms 535 which permit the eyes of the user 534 to see both the displays 532 and the environment in front of the user 534 at the one time and to resolve images from both . In one form these mechanisms 535 will include refractive components . In another form these mechanisms will include reflective components .

[0359] In yet another form these mechanisms will include both refractive and reflective components .

[0360] In another form the face mounted eyewear 531 includes a camera or other image acquisition device 36 . Images from the image acquisition device may be fed to the displays 532 . In another form the images from the image acquisition device 536 may also be fed to data processing apparatus or processor 537 .

[0361] Data from the image acquisition device 536 may further be fed via Internet 538 or other communications medium to a server 539 for processing .

[0362] In addition data from the data processing apparatus 537 may also be fed to server 539 via Internet 538 or other communications medium .

[0363] In use data from the face mounted eyewear 531 is utilised by applications relevant to the needs of the user 534 .

[0364] Various non-limiting applications are described in further detail below .

[0365] In this embodiment image acquisition by the face mounted eyewear 531 is augmented by use of a drone 540 . The drone 540 includes its own image acquisition device 542 . It may include additional sensors as further described in embodiments below . Data from these devices is fed to data processing apparatus 537 for processing by applications as described below . The data may also be fed via a communications medium 538 to a remote server 539 for processing by applications on the server as described below .

[0366] The face mounted eyewear 531 may take the form of spectacles 543 or face mounted goggles 531 .

[0367] In use the drone 540 is housed on or in mechanical association with the face mounted eyewear 531 . In a preferred form a drone landing mount 544 is located on the face mounted eyewear 531 . In a nonlimiting preferred embodiment the drone landing mount 544 is located on the bridge of the face mounted eyewear 531 between the lenses or displays as the case may be .

[0368] Data from the drone 544 is processed by applications as described below so as to meet the system 530 to provide the functionality as described below . The functionality includes that of the drone 540 acting as a "hovering assistant" for the user . In preferred forms the drone landing mount 544 incorporates a charging station to permit charging and recharging of the drone 540 between flights .Proj ect Scope and Integration

[0369] Glasses : Standalone AR health device with 140+ condition monitoring, advanced sensors , and Micro-OLED displays .

[0370] Drone : Silent ionic propulsion, forward-facing coaxial sensors , docks on glasses ' rail , streams data (LiDAR / thermal / RGB ) to AR display .

[0371] Overlap: Shared tech (graphene battery, sensor fusion, AR rendering) , but drone requires unique propulsion and docking mechanics.

[0372] The world's first glasses-drone hybrid with:

[0373] Glasses: AR health monitoring (mmWave radar, 2560x2560 Micro-OLED) , 88g with drone.

[0374] Drone: Silent ionic propulsion, coaxial sensors, 10-min hover, docks on 40mm rail.Advantages of Fifth Embodiment

[0375] First of Its Kind: No existing product integrates AR glasses with a detachable, silent ionic drone featuring coaxial LiDAR / thermal / RGB sensors. Competitors (e.g., Meta Quest, Apple Vision Pro) lack drone integration or health focus at this scale.Smart Assistant - Guru Development Plan1. Specialist 1: Generative Al and Simulation Expert

[0376] Role: Develops a generative Al agent for real-time 3D health simulations and predictive scenario modeling, enhancing the glasses' Micro-OLED display (2560x2560) and drone's spatial data.

[0377] 2. Specialist 2: Neuromorphic Al and Adaptive Learning Expert

[0378] Role: Creates a neuromorphic-inspired agent for self-adaptive behavioral coaching and emotional resonance, leveraging glasses' sensors (mmWave, EEG, audio) and drone's environmental context.

[0379] Al Features from the Specialists

[0380] Feature 1 : Real-Time 3D Health Simulation and Predictive Scenarios

[0381] Description: The Generative AT Specialist adds a "Healthvision Simulator" agent, generating interactive 3D models of the user' s health states (e.g. , heart, lungs, gait) on the glasses' Micro-OLED display, using glasses' health data (140+ conditions) and drone's spatial / thermal scans. It also simulates future health scenarios (e.g. , "If you maintain this stress level, your HRV predicts a 20% risk of hypertension in 6 months") .

[0382] How It Works:1. Data Inputs: Glasses (mmWave heart rate, EEG, etc. ) + Drone (thermal fever maps, LiDAR gait tracking) .2. Processing: GANs create 3D models (e.g., rotating heart showing arrhythmia) , predictive algorithms forecast trends.3. Output: AR overlays (e.g., "See your lung capacity in 3D" or "Simulated COPD progression") , rendered in real-time on Snapdragon XR2+.

[0383] Factor:1. Users visualize their health in immersive 3D (e.g. , zoom into a beating heart model) , a step beyond static AR data.2. Predictive scenarios (e.g. , "Run 30 mins daily to reduce diabetes risk by 15%") make health proactive and engaging.

[0384] Novelty: No wearable offers real-time 3D health simulations synced with drone-captured environmental data.

[0385] Feature 2 : Self-Adaptive Behavioral Coaching with Emotional Resonance

[0386] Description: The Neuromorphic Al Specialist adds an "EmotiveCoach" agent, using neuromorphic principles (brain-inspired computing) to adaptively coach users on mental / physical wellness, resonating with their emotional state. It adjusts advice based on real-time behavioral cues (speech tone, facial tension, HRV) and environmental context from the drone .

[0387] How It Works:1. Data Inputs: Glasses (EEG for stress, audio for speech, mmWave for HRV) + Drone (LiDAR for activity, thermal for surroundings) .2. Processing: Neuromorphic algorithms mimic neural plasticity, learning user patterns (e.g. , stress triggers) , reinforced by emotional analysis (e.g. , "You sound tense") .3. Output: Personalized coaching via bone conduction speaker (e.g. , "Take 5 deep breaths— your HRV is low after that meeting") or AR prompts (e.g. , "Walk 10 mins outdoors— drone detects a calm park nearby") .

[0388] Factor:1. Al feels human-like, adapting instantly (e.g. , "I notice you're restless— let' s try a sleep exercise") with empathetic tone.2. Drone integration adds context (e.g. , "Avoid this noisy area— your stress spiked here last time") , unmatched by other wearables.

[0389] Novelty: Neuromorphic, emotionally resonant coaching tied to a glasses-drone system is unprecedented.

[0390] Features' Impact

[0391] Healthvision Simulator: Turns the glasses into a personal health theater— users see their body in 3D (e.g., "Watch your heart beat") andfuture risks (e.g., "Simulate 5 years of inactivity") , unmatched by any wearable .

[0392] EmotiveCoach: Feels like a living companion, adapting instantly (e.g. , "You're tense— let' s walk to that quiet spot the drone found") with drone-contextualized advice, redefining Al interaction.

[0393] Synergy with Glasses-Drone :1. Glasses' 140+ conditions get visualized in 3D (e.g. , COPD lung model) .2. Drone's LiDAR / thermal data enhances simulations (e.g. , fever mapped in 3D) and coaching (e.g., "Avoid that hot, crowded area") .Drone Tracking

[0394] This embodiment includes the following features:

[0395] Glasses-Drone-AI System: Add "a generative agent for 3D health simulations and a neuromorphic agent for adaptive coaching."

[0396] AI-Driven Simulation Method: "Generating real-time 3D health models and predictive scenarios using glasses and drone data."

[0397] Neuromorphic Coaching Patent: "A self-adaptive, emotionally resonant AT agent for wearable health coaching."

[0398] To enhance the Integrated Glasses-Drone System v5.0 with the Guru Reddy Al and MicroDrone XI to check gait from the rear of the user and watch exercise movements for fall prevention, we can build on the existing 10-person Al team and the drone's This leverages the drone's coaxial sensors (LiDAR 60°x60°, thermal, 1080p 80° FoV) and the Al's 15-agent framework, already running on the glasses' Snapdragon XR2+ ( $135.20 / unit, 10M units) . I'll detail the new features, adjust the team's tasks, update the timeline, and ensure integration with the glasses' 140+ health monitoring and Al's surroundings-aware dialogue.

[0399] Features Overview

[0400] Rear Gait Analysis by Drone:1. The drone detaches, hovers behind the user (e.g. , l-2m) , and uses its coaxial LiDAR (60°x60°, 0.5cm resolution) and 1080p camera (80° FoV) to track gait parameters (stride length, symmetry, foot lift) from a rear perspective .2. Goal: Detect abnormalities (e.g., Parkinson's shuffle, post-stroke limp) for health insights and fall risk assessment.

[0401] Exercise Movement Monitoring for Fall Prevention:1. The drone observes exercise movements (e.g. , squats, walking) in realtime, while the Al analyzes motion data to prevent falls (e.g., "Your knee's wobbling— adj ust your stance") .2. Goal: Provide corrective feedback and predict fall risks (e.g., instability, uneven terrain) .How It Fits with Previously Described Embodiments

[0402] Drone:1. Sensors: LiDAR and 108 Op already capture 3D spatial data and visuals— rear positioning just shifts the vantage point.2. Flight: 10-min hover and 3 m / s speed support dynamic tracking behind the user.3. Data: Streams to glasses via Wi-Fi 6 for Al processing.

[0403] Glasses:1. Hardware: Snapdragon XR2+ (4GB RAM, 64GB storage) handles Al compute; bone conduction speaker delivers feedback.2. Sensors: mmWave radar and EEG complement drone data (e.g. , heart rate, balance ) .

[0404] Assistant Agent -Guru Reddy Al:1. Agents: Foot / Balance Specialist and Predictive Health agents adapt to process gait / exercise data.2. Surroundings Awareness: Time, weather, GPS enhance context (e.g. , "Wet ground— watch your step") .3. Dialogue: Direct speech informs users (e.g., "Your stride's off— slow down" ) .

[0405] Additional Features1. Rear Gait Analysis by Drone

[0406] How It Works:1. Activation: User says, "Check my gait." Drone undocks, hovers l-2m behind at Im height (adjustable via LiDAR) .2. Data : i. LiDAR: Maps leg / foot motion (e.g., stride 25cm, lift 2cm, symmetry ±5%) . ii.l080p: Records visual gait (e.g. , limp detection) . iii. Thermal: Spots muscle strain (e.g., hotter calves = fatigue) .3. Al Processing: Foot / Balance agent analyzes for abnormalities (e.g. , Parkinson's shuffle: short steps, low lift) .4. Output: AR overlay (e.g., "Your left leg drags— see it here") + speech (e.g., "Slow down, your gait's uneven") .

[0407] Factor: Drone tracks from behind— unseen in wearables— of f ering a clinician-like rear view (e.g. , "Your posture's off by 10°") .

[0408] 2. Exercise Movement Monitoring for Fall Prevention

[0409] How It Works:1. Activation: User says, "Watch my exercise." Drone hovers behind or circles (3 m / s) , tracking movements.2. Data : i.LiDAR: Measures joint angles (e.g., knee flex 20°) , stability (e.g., sway 5cm) . ii.l080p: Captures form (e.g., squat depth) , iii. Glasses' mm ave : Monitors heart rate (e.g. , elevated = fatigue) .3. Al Processing: Predictive Health agent flags fall risks (e.g., "Wobbly knee = 40% fall chance") , EmotiveCoach suggests corrections.4. Output: Real-time feedback (e.g. , "Straighten your back— fall risk down 15%") + 3D AR sim (e.g., "See your squat form") .

[0410] Factor: Proactive fall prevention with drone-assisted precision (e.g. , "Step wider— terrain' s uneven ahead") .

[0411] Further Additional Features

[0412] Glasses-Drone-AI System:1. Add "a drone tracking rear gait and exercise movements, integrated with Al for fall prevention."

[0413] Method Patent:1. "A method comprising: a) Positioning a drone behind the user to capture gait via LiDAR and 1080p; b) Monitoring exercise movements for fall prevention; c) Processing data with Al for real-time feedback. "

[0414] Gait and Fall Prevention Patent:1. "A wearable system with a detachable drone using coaxial sensors to analyze rear gait and exercise, preventing falls via Al-driven AR and speech. "

[0415] Features in Action

[0416] Gait Check:1. User: "Check my gait."2. Al: "Drone's behind you— walking looks good, but your left stride's 5cm shorter. Slow down to balance."3. AR: Shows 3D leg model with asymmetry highlighted.

[0417] Exercise Monitoring:1. User: "Watch my squats."2. Al: "Drone's tracking— your knee's wobbling 10cm. Shift weight to your heels; fall risk's down to 5% now."3. AR: Displays squat form in 3D with correction overlay.CPU / GPU in Glasses

[0418] The Integrated Glasses— Drone System v5.0 specifies that the glasses are equipped with a Snapdragon XR2+ CPU paired with an Adreno 650 GPU, alongside 4GB LPDDR5 RAM and 64GB eMMC storage. This hardware powers the Guru Reddy Al— a 15-agent conversational AT with added features like surroundings awareness, direct dialogue, rear gait analysis, and exercise monitoring for fall prevention. In one form this onboard setup is strong enough to run the full Al and its analysis standalone. In an alternative form a local server backup may be used to augment and distribute processing power .

[0419] Hardware Capabilities

[0420] Snapdragon XR2+ CPU:1. A high-performance, AR / VR-optimized chip with an 8-core Kryo 585 CPU (lx Prime @ 2.84 GHz, 3x Performance @ 2.42 GHz, 4x Efficiency @ 1.8 GHz) .2. Designed for real-time processing, edge Al, and low-power operation (typically 5-7W TDP) .3. Comparable to mid-tier smartphone SoCs, capable of handling multiple threads and Al workloads .

[0421] Adreno 650 GPU:1. Delivers ~1.2 TFLOPS of compute power, optimized for AR rendering (e.g. , 2560x2560 Micro-OLED at 90 Hz) .2. Supports hardware-accelerated ML tasks via Qualcomm's Al Engine (11 TOPS peak with Hexagon DSP) .

[0422] 4GB LPDDR5 RAM:1. Fast memory (up to 4266 MHz bandwidth) , but limited capacity for multitasking heavy Al models alongside AR rendering.

[0423] 64GB eMMC Storage:1. Ample for OS, Al models, and data logs (e.g. , gait history) , but not SSD-speed (slower read / write ~300 MB / s) .

[0424] Guru Reddy Al Workload

[0425] 15+ Agents: Orchestrator , health monitoring, predictive analytics, gait / exercise analysis, dialogue, 3D simulations, etc.

[0426] Data Inputs:1. Glasses: mmWave radar (heart rate) , EEG (brain waves) , audio (speech) , BLE / GPS (location, weather) .2. Drone: LiDAR (60° x60° , 0.5cm res) , 1080p (80° FoV) , thermal (160x120) , streamed via Wi-Fi 6 (~3ms latency) .

[0427] Processing Needs:1. Real-time multimodal fusion (health + spatial data) .2. Generative 3D simulations (e.g., gait models) .3. Neuromorphic inference (adaptive dialogue) .4. Speech synthesis for bone conduction output.

[0428] Edge Goal: Offline operation, <3ms latency for critical tasks (e.g. , fall alerts) .Glasses Standalone

[0429] Strengths

[0430] Al Engine: The Snapdragon XR2+' s Hexagon DSP (11 TOPS) is built for edge AT, handling tasks like speech recognition (MEMS mic) , image processing (thermal / 1080p) , and predictive models (HRV trends) efficiently .

[0431] GPU Power: Adreno 650 can render 3D AR overlays (e.g., gait sims) at 2560x2560, supporting the Healthvision Simulator agent.

[0432] Optimized Design: The glasses' RTOS and Al's modular agent structure (e.g., Foot / Balance , Predictive Health) can prioritize tasks, offloading non-critical ones (e.g., weather updates) to BLE pulls.

[0433] Drone Data: Wi-Fi 6 streaming (up to 9.6 Gbps theoretical) ensures fast LiDAR / 1080p input (~10-20 MB / s) , manageable by the CPU / GPU combo.

[0434] Limitations

[0435] RAM Constraint: 4GB LPDDR5 is tight for:1. Running 15+ agents simultaneously (each ~100-200 MB model size = 1.5- 3GB) .2. Buffering drone video / LiDAR data (~500 MB for 10-min hover) .3. Rendering AR in parallel (2560x2560 per eye ~500 MB) .4. Total demand could exceed 4GB, causing swapping to slower eMMC storage.

[0436] Compute Load: Real-time gait analysis (LiDAR point clouds ~10,000 points / sec) , 3D simulations, and speech synthesis might push the 11 TOPS limit, especially with neuromorphic inference (high memory bandwidth needs ) .

[0437] Battery Impact: lOOOmAh graphene battery (8-min charge, 8-10hr runtime) may drain faster under full Al load, reducing standalone usability .

[0438] Verdict: Observations on performance

[0439] Standalone Capability: The Snapdragon XR2+ and Adreno 650 can run the full Guru Reddy Al and analysis offline for core tasks (e.g., gait tracking, fall alerts, basic dialogue) by optimizing agent priority and compressing models (e.g., pruning to <1.5GB total) . Pre-trained models and edge-optimized inference (e.g., TensorFlow Lite) keep compute within 11 TOPS.

[0440] Edge Cases: Heavy multitasking (e.g. , 3D sims + gait + weather + speech in a noisy environment) could strain 4GB RAM, causing lag (>3ms) or dropped frames in AR. High-resolution drone data (e.g. , 1080p at 30 FPS) might need downsampling to fit.Embodiment with Local Server Backup

[0441] Scenarios Where It is Helpful

[0442] Memory Overflow: If all 15+ agents run concurrently with full drone data (e.g. , 10-min gait recording) , 4GB RAM may bottleneck, requiring a local server to offload non-critical tasks (e.g. , long-term trend analysis, 3D rendering) .

[0443] Battery Life: Continuous max-load Al (e.g. , 11 TOPS + GPU) could cut runtime below 8hr, needing a server to handle background processing while glasses recharge via drone docking.

[0444] Enhanced Features: Future scalability (e.g. , larger Al models, multi-user support) might exceed the XR2+' s capacity, making a server a strategic backup.

[0445] Server Specs (If Needed)

[0446] Minimal: A local hub (e.g. , Raspberry Pi 5, 8GB RAM, ~$100) with Wi-Fi 6 could offload 1-2GB of processing (e.g., 3D sims) , syncing via BLE.

[0447] Robust: A small PC (e.g. , Intel NUC, i5, 16GB RAM, ~$500) could handle full Al redundancy, storing 64GB+ of data.

[0448] Verdict: Not Essential, But Useful

[0449] Primary Operation: The glasses' CPU / GPU are strong enough for standalone use in most scenarios (e.g., 5-10min gait checks, real-time dialogue) , especially with optimized software (e.g. , agent scheduling, data compression) .

[0450] Backup Option: A local server isn't required but could enhance performance for edge cases (e.g. , prolonged use, complex sims) , acting as a safety net without altering the $135.20 / unit cost (server optional for users ) .

[0451] Final Answer

[0452] The glasses' Snapdragon XR2+ CPU and Adreno 650 GPU are strong enough to run the full Guru Reddy Al and analysis standalone for core functionality (gait, exercise, dialogue, 140+ conditions) with careful optimization (e.g., <1.5GB model size, prioritized agents) . However, a local server backup may still be useful— not necessary— for heavy multitasking or extended sessions, ensuring lag-free performance and battery longevity.INDUSTRIAL APPLICABILITY

[0453] In some forms there is provided an observation system which observes characteristics or parameters in order to analyse for health conditions .

[0454] In some forms there is provided an observation system which observes gait and other characteristics or parameters in order to produce orthotics .

[0455] In some forms the invention presents an Al-driven system for enhancing elderly care, utilising multimodal data analysis, personalised interactions, and health monitoring to support the elderly and their caregivers. Through advanced technology integration, the system offers a scalable, effective solution for the nuanced needs of elderly care, promoting well-being, safety, and independence.

[0456] There is described the conceptual framework and operational components of an innovative Al system designed to revolutionise elderly care. By leveraging artificial intelligence, the system offers a comprehensive solution to improve the quality and effectiveness of care for the elderly population.

Claims

CLAIMS :1 . An orthopaedic analysis , fitting and production system comprising at least one multi purpose multi sensor device for the production of orthoses ; the system further compris ing an automated or computer ass isted design and modelling system which then outputs to an orthoses production system; the sensor device including sensors : a . wherein the sensors on the sensor device include at least but are not limited to a high resolution camera and accelerometer ; and b . wherein the outputs of the sensors are connected either in real time or store and forward to the system whereby sensor data is sent from the sensors to the system thereby to produce orthoses .2 . The system of claim 1 adapted to produce customised orthopaedic footwear and orthotics .3 . The system of any previous claim where the sensors include a camera capable of high resolution near infra-red wavelength sensing .4 . The system of any previous claim where the sensors available include a LIDAR s canner .5 . The system of any previous claim wherein the multi purpose , multi sensor device is a virtual reality headset .6 . The system of any previous claim wherein the multi purpose , multi sensor device is an augmented reality headset .7 . The system of any previous claim wherein the user of the sensor device does not need specialised training or s kills to operate the sensor device .8 . The system of any previous claim wherein the system includes preproces sing of the sensor data .9 . The system of any previous claim wherein the sensor data is sent in real time to the system .10 . The system of any previous claim wherein the sensor data is stored and forwarded to the system .11 . The system of claim 10 wherein the sensor data is stored and forwarded to the system at predetermined time intervals .12 . A data acquisition , gait analysis orthopaedic analys is , fitting and production system compris ing at least one multi purpose multi sensor device for the production of orthoses .13 . The system of claim 12 wherein the system further comprises an automated or computer as sisted des ign and modelling system which then outputs to an orthos is production system; the sensor device including sensors .14 . The system of claim 12 or 13 wherein the sensors on the sensor device include at least but are not limited to a high resolution camera .15 . The system of claim 12 or 13 wherein the outputs of the sensors are connected either in real time or store and forward to the system whereby sensor data is sent from the sensors to the system thereby to produce orthoses .16 . The system of any one of claims 12 to 15 adapted to produce customised orthopaedic footwear and orthotics .17 . The system of The system of any one of claims 12 to 16 where the sensors include a camera capable of high resolution near infra-red wavelength sensing .18 . The system of any one of claims 12 to 17 where the sensors available include a LIDAR s canner .19 . The system of any one of claims 12 to 18 wherein the multi purpose , multi sensor device is a virtual reality headset .20 . The system of any one of claims 12 to 19 wherein the multi purpose , multi sensor device is an augmented reality headset .21 . The system of any of any one of claims 12 to 20 wherein the user of the sensor device does not need specialised training or s kills to operate the sensor device .22 . The system of any one of claims 12 to 21 wherein the system includes preproces sing of the sensor data .23 . The system of any one of claims 12 to 22 wherein the sensor data is sent in real time to the system .24 . The system of any one of claims 12 to 23 wherein the sensor data is stored and forwarded to the system .25 . The system of claim 24 wherein the sensor data is stored and forwarded to said system at predetermined time intervals .

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