Adaptable stimulation system and method

Abstract

An adaptable stimulation system, such as but not limited to an extended reality (XR) system 5, for presenting a personalised environment to a user 20, and an associated method, computer program produc

Description

Background Extended reality (XR) technologies have been employed in a wide range of applications including in architecture, gaming, operation of machinery, health, training and others. Extended reality technologies include virtual reality (VR) in which the environment to which users are exposed is entirely provided by the system and is often computer generated, augmented reality (AR) in which real environments are overlaid with computer generated or other system provided components, and mixed reality (MR) in which computer provided or generated and real features are juxtaposed and can interact with each other. XR technologies have been applied for medical applications. However, improving the efficacy of these XR technologies would be beneficial. At least some examples of the present disclosure set out to provide more effective XR systems and methods. Summary Various aspects of the present invention are defined in the independent claims. Some preferred features are defined in the dependent claims. According to a first example of the present disclosure is an adaptable stimulation system, which may be or comprise an extended reality (XR) system, such as a virtual reality (VR) system, for delivering a personalised environment to a user, wherein the stimulation system comprises a stimulation delivery system that provides the personalised environment to the user and comprises at least one, any or all of:: at least one visual delivery system for delivering a visual environment for the user as part of the personalised environment; an audio system for delivering audio stimulation to the user as part of the personalised environment; an olfactory stimulation system for providing one or more scents to the user as part of the personalised environment; and / or a haptic delivery system for delivering tactile sensations to the user as part of the personalised environment. The adaptable stimulation system further comprises a controller for controlling the stimulation delivery system to control the personalised environment delivered to the user by the stimulation delivery system; and a plurality of sensors for monitoring the user, e.g. for monitoring one or more physiological parameters of the user; wherein the controller is configured to control and / or adapt the personalised environment delivered to the user based on output from the plurality of sensors, e.g. on the one or more physiological parameters of the user. The stimulation delivery system may be or comprise an XR delivery system such as a VR delivery system. The visual delivery system, which may be configured to deliver visual content to the user, which may be 3D visual content, such as stereoscopic 3D visual content, holographic content, or other volume representing visual content. The visual content may be or comprise at least one or each of: video, animation, and / or images. The stimulation delivery system may comprise a headset, such as a VR headset. The stimulation delivery system may be comprised in the headset. The controller may be integral with the headset or separate or distributed between the headset and a location remote from the headset. The visual environment provided by the visual delivery system may be an immersive environment. The visual delivery system may comprise left eye and right eye displays. The left eye display may be configured to supply visual content predominantly or exclusively to the left eye. The right eye display may be configured to supply visual content predominantly or exclusively to the right eye. The left and right eye displays may be configured to provide stereoscopic or other 3D images of the same scene. The visual content may be or comprise a mechanism of action (MOA) video. The adaptation of the personalised environment may comprise playing the same video content with different executions and / or display parameters, e.g. with different colour pallet, different brightness, different contrast, different gamma correction value, different music or audio content, or the like. The audio delivery system may be comprised in the headset. The audio system may be configured to deliver audio content, such as a spatial or 3D audio. The audio content may comprise music. The adaptation of the personalised environment may comprise changing the audio content, e.g. changing music, changing a tempo or speed of the music or other audio content, changing the tone or pitch of the music or other audio content, and / or the like. The olfactory stimulation system may be configured to selectively deliver the scents to the user according to at least one of: the visual content currently or about to be delivered to the user, the audio content currently or about to be delivered to the user, user-specific preferences, and / or a user profile. At least one or each of: the visual content, the audio content, data of the scents, and / or data of the tactile sensations may be computer generated or retrieved from data storage, e.g. long term data storage. The visual and / or audio content may be preprovided to the system, e.g. before use. The haptic delivery system may comprise at least one of: vibration, force feedback, electrical stimulation or other suitable mechanism for delivering tactile sensations. The XR system may be a virtual reality (VR) system and may be a fully immersive system, i.e. the user is provided with a personalised environment in which a majority or substantively all of the visual and / or audio experience of the user is provided or providable by the VR system. The controller may be configured to control and / or adapt the personalised environment delivered to the user based directly and / or indirectly on the one or more physiological parameters of the user from the plurality of sensors, e.g. based at least in part on a function or property that depends on or is derived from the one or more physiological parameters of the user from the plurality of sensors. The plurality of sensors may be configured to collect data simultaneously, e.g. for a corresponding or same time. At least one of the sensors may be or comprise an electroencephalogram (EEG) system, which may be configured to detect, record and / or analyze brainwave signals or other electrical brain activity of the user. The EEG system may comprise one or more electrodes, which may be arranged or locatable on the head of the user, e.g. on the scalp or forehead of the user, to detect, record and / or analyze the brainwave signals or other electrical brain activity of the user. The EEG system may be configured to detect, record and / or analyze electroencephalogram (EEG) signals specifically from the frontal lobes of a user's brain, e.g. in use whilst the user is experiencing the personalised environment provided by the stimulation delivery system. The EEG system may be configured to detect, record and / or analyse at least one or each of: alpha, beta, delta and / or gamma waveforms of the EEG signals. The output of the at least one of the sensors may comprise the EEG signals, e.g. at least one or each of: alpha, beta, delta and / or gamma waveforms of the EEG signals. The EEG system may be configured to collect data in a plurality of channels, e.g. 32 channels, or 64 channels or more. The EEG system may be configured to extract specified channels or otherwise reduce the number of channels from the collected channels. For example, a subset of one or more of the collected channels may have little or no impact, or an effect less than a threshold, on the final determination, and the process can be limited to those channels having most effect on the process by excluding the subset of channels. This may increase response time and / or decrease the resources required. This is particularly advantageous in examples that use device-to-device communications, such as Wi-Fi, cellular or other communications, such as communications between wearable or user devices and remote controllers, remote party systems and / or other remote or cloud computing resource. The system may be configured, e.g. by pre-training, training in situ, and / or training in real-time, to determine a unique brain signature specific to each user based on the data obtained from the EEG signals, e.g. the EEG signals recorded from the frontal lobes of the user's brain in use whilst the user is exposed to the personalised environment. At least one of the sensors may be a photoplethysmography (PPG) sensor. At least one or more of the sensors may be biosensors, configured to measure physiological parameters of the user. The at least one biosensor may be or comprise one or more of: at least one heart rate sensor, at least one electrocardiogram (ECG) sensor, at least one blood pressure sensor, at least one skin conductance sensor, at least one temperature sensor, at least one oxygen saturation such as a peripheral oxygen saturation (SpO2) sensor, at least one eye sensor, at least one sweat sensor, at least one movement sensor for measuring movement or activity of part or all of the user such as at least one accelerometer or gyroscope or the like, and / or at least one respiratory rate sensor. The at least one eye sensor may be configured to determine eye opening and closing, eye movement and / or dilation, and / or changes therein. At least one of the sensors may be or comprise at least one user activity sensor for monitoring activity of the user such as motion and / or actions performed by the user. The at least one user activity sensor may be or comprise at least one inertial measurement unit (IMU), at least one magnetometer, at least one optical tracking sensor, at least one pressure sensor, at least one quantum sensor, at least one eye tracking sensor fortracking the user’s eye movements and / or gaze direction, at least one haptic feedback sensor, and / or the like. The IMU may be configured to monitor linear and angular motion of the user's head. The controller may be configured to adjust the personalised environment in realtime based on the IMU data to match the user's head movements. The magnetometer may be configured to measure the Earth's magnetic field and / or provide absolute orientation tracking. The controller may be configured to vary the content provided by the stimulation delivery system based on the orientation and / or location determined from the magnetometer. The controller may be configured to correct drift in the orientation data of the headset using the magnetometer data. The at least one optical tracking sensor may be positioned on the headset. The at least one optical tracking sensor may be configured to track the headset's position and orientation and / or the position and orientation of the user’s head. The controller may be configured to vary the content provided by the stimulation delivery system based on the orientation and / or location determined from the at least one optical tracking sensor. The at least one pressure sensor may be configured to detect motions by the user such as user inputs such as hand and / or finger movements. The controller may be configured to adjust interactions with virtual objects in the personalised environment in real-time based on data from the at least one pressure sensor. The at least one quantum sensor may be configured to provide position and / or orientation of the headset, user’s head or hands and / or a controller. The controller may be configured to the provision of or rendering and / or interactions in the personalised environment based on the position and / or orientation derived from the quantum sensor. The controller may be configured to adjust provision, rendering and / or interactions in the personalised environment based on the user’s gaze direction and / or eye movements derived from the eye tracking sensors. The at least one haptic feedback sensor may be integrated into the controllers and / or the headset. The controller may be configured to provide the haptic or other tactile feedback to the user as part of the personalised environment based on output from the at least one haptic feedback sensor, which may be based on interactions with virtual objects and / or environmental conditions. At least one of the sensors may be or comprise at least one environmental sensor for monitoring an environment around a user. The at least one environmental sensor may be configured to monitor at least one of temperature, humidity, and / or air quality in the physical environment around the user. The controller may be configured to The physiological parameters measured may comprise one or more physiological parameters directly measured from the one or more sensors and / or may comprise one or more physiological parameters derived from the data measured by the one or more sensors. The one or more physiological parameters derived from the data measured by the one or more sensors may comprise one or more of: heart rate variability, variability in respiratory rate and / or variability in at least one of the physiological parameters directly measured by at least one of the biosensors. The controller may be configured to determine one or more states of the user, such as an emotional state, a physical state, a mental or mental health state of the user, attention level, excitement level, engagement level, and / or the like. Examples of the emotional or mental or mental health state of the user can include stress, anxiety, and / or the like. The controller may be configured to determine the one or more states of the user from at least the output of the plurality of sensors or properties derived therefrom or indicative thereof, and / or from the profile for that user. The determining of the one or more states of the user, such as an emotional state, a mental state or mental health state of the user may comprise receiving the EEG signals, which may be or include but may not be limited to alpha, beta, delta, and gamma waveforms. The determining of the one or more states of the user, such as an emotional state, a mental state or mental health state of the user may comprise combining the EEG signals, which may be or include but may not be limited to alpha, beta, delta, and gamma waveforms, which may comprise linear or non-linear combinations, to derive a signal profile or other function or property. The comprehensive signal profile or other function or property may be or comprise but may not be limited to an alpha to beta ratio (RAB), e.g. a ratio of values of the alpha waveform to those of the beta waveform). The determining of the one or more states of the user, such as an emotional state, a mental state or mental health state of the user may comprise utilising the signal profile or other function or property as the input to a network, model or algorithm, which may apply machine learning or other deep learning, artificial intelligence, generative techniques, and / or the like. The network, model or algorithm may be configured to integrate and analyse the individual and combined effects of the EEG signals or parts of the EEG signals such as at least one of: alpha, beta, delta, and gamma EEG signals, e.g. in a linear or non-linear fashion. The network, model or algorithm may be trained or otherwise configured to identify the most suitable combination or combinations, e.g. linear or nonlinear combinations, of sensor signals or outputs or properties derived therefrom, and may be further configured to derive an index or metric, which may be indicative of the user state. The controller may be configured to control and / or adapt the personalised environment delivered to the user based on the index or metric, e.g. by varying the personalised environment to optimise the value of the index or metric. The use of a combination of different EEG signals or different components of EEG signals, such as by using the RAB, may improve the efficacy in indicating stress or the absence of stress in adult participants, and improve the reliability and precision of the system. At least one of the sensors may be or comprise an imaging sensor, such as a camera, which may be configured to image at least part or all of the user. The imaging sensor may be configured to image at least part or all of a head or face of the user, e.g. the eyes of the user. The imaging sensor may be or may be comprised in the eye sensor. The one or more states of the user may be derived from the outputs of at least one of the plurality of sensors, e.g. from the eye movement or other eye sensor, from the EEG system, from the heart rate sensor, and / or the like. The one or more states, e.g. the mental or mental health state or attention level, of the user may be derived at least in part from the eye movements and / or pupil dilation determined using the at least one eye sensor. The one or more states and / or physiological parameters of the user may be determined at least in part from the EEG system, e.g. the one or more states and / or physiological parameters may comprise a level of calmness or stress, which may be based on an objective scale using identified signatures of calmness or stress derived from the EEG signals recorded from the frontal lobes of a user's brain, e.g. in use whilst the user is exposed to the personalised environment. At least one, some or all of the plurality of sensors may be comprised in a wearable device worn or wearable by the user, such as a smart watch or an ear mounted sensor. For example, one or more sensors from the group comprising: the heart rate sensor, the eye sensor, the skin temperature sensor, the motion and / or activity sensor such as at least one accelerometer or gyroscope, the inertial measurement unit (IMU), which may be configured to monitor linear and / or angular motion of the user’s head, the magnetometer that may be configured to measure the Earth's magnetic field and / or provide absolute orientation tracking, the EEG system, the ECG sensor, and / or the sweat sensor, may be comprised in the smart watch, ear mounted sensor, the headset and / or other wearable device. The wearable device may be configured to communicate the sensor data to the controller. At least one, some or all of the plurality of sensors may be comprised in a user device, such as a portable user device, of the user. The user device may be a device carried by the user. The user device may be a smartphone or other mobile phone, a tablet, or other personal computing device. The user device may be configured to at least partially implement the controller. The controller may be distributed between any of: the headset, the user device and / or a remote computing resource such as a server, cloud computing resource, or the like. The user device may be configured to communicate with the wearable device and / or the remote computing resource. The wearable device and / or the user device may be configured to communicate with the controller and / or the remote computing resource and / or a remote party system over a cellular communications network such as a 3G, 4G, LTE or 5G or any form of successor network or similar. The wearable device and / or the user device may be configured to communicate with the controller and / or the remote computing resource and / or a remote party system via wireless communications, preferably a high capacity wireless communications such as Wi-Fi, preferably Wi-Fi 6, Wi-Fi 6E, IEEE 802.11ax or a successor or similar standard. In such communications, the features designed to reduce bandwidth, lag and / or processing or other computing resources required are particularly beneficial. The use of such high capacity communications such as 5G and Wi-Fi 6 or the like can beneficially reduce lag. The controller may implement a content adaptation engine. The content adaptation engine may receive the data from the at least one sensor and adapt the personalised environment delivered to the user by the at least one stimulation delivery system based at least in part on the output of the plurality of sensors, e.g. from the at least one physiological parameter and / or the brainwave signals of the user. The content adaptation engine may receive or be configured to determine the at least one state of the user and adapt the personalised environment delivered to the user by the stimulation delivery system based at least in part on the determined at least one state of the user. The content adaptation engine may be configured to analyze the data from the at least one sensor, which may include at least the output of the EEG system, to determine the one or more states of the user, which may comprise at least one of: the user's cognitive state, the user’s physical state, the user’s mental or mental health state and / or the user’s emotional state or responses, and may adapt the personalised environment accordingly. The content adaptation engine may be or comprise a closed loop adaptation engine. The controller may be configured to adapt the personalised environment provided to the user in real time or near real time, on the fly and / or while in use. For example, the controller may be configured to adjust the personalised environment based on the IMU data to match the user's head movements. As an example, the controller may be configured to correct drift in the orientation data of the headset using data from the magnetometer. The adaptation engine may be configured to adapt the personalised environment based at least in part on the data from the at least one sensor and / or a profile based on data from the output from the at least one sensor. The adaptation engine may be configured to determine adjustments to the personalised environment, e.g. adjustments to at least one or any of: the immersive visual environment, the audio stimulation, the one or more scents provided, and / or the tactile sensations provided, based at least in part on the data from the at least one sensor and / or a profile based on data from the output from the at least one sensor. The adaptation engine may be configured to determine the adjustments based in part on the profile. For example, the adaptation engine may be configured to adapt the personalised environment when the data from the at least one sensor and / or a profile based on data from the data from the at least one sensor is outwith a set or pre-set range associated with a target state of the user, e.g. a calm or normal state of the user, or is otherwise indicative of the target state of the user. The adaptation engine may be configured to maintain and / or not adapt the personalised environment when the data from the at least one sensor and / or a profile based on data from the data from the at least one sensor is within the set or pre-set range associated with a target state of the user, or is otherwise indicative of the target state of the user. The profile may be a user specific profile specific to a user or group of users. The profile may comprise physiological data from the at least one sensor for that user or group of users, or properties of the user derived therefrom or indicative thereof. The user specific profile may contain user preferences for that user or group of users, which may be input or otherwise selected by the user and / or automatically generated, e.g. using an algorithm, model, machine learning engine, artificial intelligence (Al), generative models, or the like. The preferences may comprise user preferences for the personalised environment, e.g. relating to the content, display and / or any other provision of the personalised environment. The user specific profile may contain biometric response patterns of that user or group of users. The profile may be stored in data storage that is accessible by the controller. The data storage may be provided on, or distributed between, any or all of: the headset, the user device and / or a remote computing resource such as a server, cloud computing resource, or the like. The controller may be configured to identify a current user and to retrieve the user specific profile for that user from the data storage. The adaptable stimulation system may be, or may comprise or be comprised in, a therapy delivery system. The adaptable stimulation system may be configured to deliver therapy, such as an XR based therapy, which may be a therapy for stress or anxiety or a similar condition. The adaptable stimulation system may be a VR delivery system and the personalised environment may be a fully immersive VR environment. The personalised environment may be a soothing or calming environment. The controller may be configured to determine a value of an index representing the state of the user, wherein the index may comprise at least one of at least one of: a stress index, calmness metric or at least one other metric from the outputs of the one or more sensors or a parameter derived therefrom, which may be determined in real time or on the fly. The index may be based on at least the output of the EEG system, and / or at least one parameter based thereon, and the determined one or more physiological parameters of the user and / or the determined one or more states of the user and / or trends in any of the above. The index may be or comprise a multi-dimensional profile based on at least the output of the EEG system, and / or at least one parameter based thereon, and the one or more physiological parameters of the user and / or the one or more states of the user and / or trends in any of the above. The index may be based at least in part on the cognitive states and emotional responses of the user. The controller may be configured implement a machine learning or other model to determine the value of the index. This may comprise, for example, applying artificial intelligence (Al), generative techniques such as a generative adversarial network (GAN) and / or the like to determine the value of the index. The machine learning or other model may be trained on training data, which may relate the output of the EEG system and the one or more physiological parameters of the user, and / or at least one parameter based thereon, to a stress or calmness value, which may be manually input by a user or obtained using any other suitable technique. The stress or calmness value may be indicative of at least one state, e.g. emotional, mental or mental health state of the user. The machine learning or other model may be trained or otherwise configured to output a value for the index based on inputs comprising the outputs of the plurality of sensors and / or parameters derived therefrom, which may comprise at least the output of the EEG system and the one or more physiological parameters, and / or at least one parameter based thereon. The adaptation engine may be configured to control, e.g. adapt, the personalised environment delivered to the user based on the value of the index, e.g. based on the change or other trend in the index. The content adaptation engine may be configured to adapt the personalised environment delivered to the user in a feedback loop, e.g. a closed feedback loop, based on changes in the index. That is, the stimulation delivery system may be configured to present the personalised environment to the user. The controller may be configured to receive the output of the plurality of sensors from the user whilst the user is experiencing the personalised environment. The content adaptation engine may be configured to determine the value of the index based on the output of the plurality of sensors from the user whilst the user is experiencing the personalised environment The content adaptation engine may then be configured to adapt the personalised environment based on the determined value of the index or trend or change in the value of the index, e.g. according to adaptation logic, and the adapted personalised environment may be presented to the user. The adaptable stimulation system may be configured to receive the output of the plurality of sensors from the user whilst the user is experiencing the adapted personalised environment. The content adaptation engine may then be configured to further adapt the personalised environment based on the value of the index determined for the user whilst the user is experiencing the adapted peronalised environment, and the further adapted personalised environment may be presented to the user, and so on in a feedback. For example, if the value of the index, e.g. stress index, is increasing or is increasing by at least a threshold amount, then the controller may be configured to adapt the virtual reality environment delivered to the user. The adaptation of the personalised environment delivered to the user may comprise varying a dominant colour or a colour palette of the personalised environment, switching between different audio or visual presentations, and / or the like. The adaptation of the persoonalised environment may comprise selecting or adapting at least one of: colour, music, darkness, lightness, contrast, gamma correction value, or the like. The adaptation of the personalised environment delivered to the user may comprise switching between different pre-stored visual and / or audio and / or haptic presentations, which may comprise fading between different pre-stored visual and / or audio and / or haptic presentations. The adaptation of the personalised environment delivered to the user may comprise modifying the difficulty level or complexity of the virtual reality content, e.g. to match the user's cognitive states and emotional responses determined by the controller. The adaptation engine may be provided with adaptation logic that relates changes in the plurality of sensor outputs and / or the parameters based thereon with corresponding adaptations to the personalised environment. For example, particular values or ranges of values of the plurality of sensor outputs and / or the parameters based thereon can be associated with particular adaptations to the personalised environment, e.g. with one or more of: particular predominant colours or colour pallets, particular visual presentations, particular audio presentations, particular haptic feedbacks, and / or the like. The association of the particular values or ranges of values of the plurality of sensor outputs and / or the parameters based thereon and the particular adaptations to the personalised environment may be comprised in, specified by or governed by the adaptation logic. The adaptation logic may be implemented as a machine learning or artificial intelligence model, algorithm, look up table, mapping, other form of deep learning or generative technique such as a GAN, and / or the like. In this way, for any given combination of values of the plurality of sensor outputs and / or the parameters based thereon, the adaptation logic may specify an associated adaptation to the personalised environment, e.g. a predominant colour or colour pallet, a particular visual presentation, a particular audio presentation, a particular haptic feedback, and / or the like. In this way, the stimulation system may dynamically adapt the personalised environment presented to the user on the fly based on real time or near real time cognitive, physiological and / or psychological state of the user, which may be derived from physiological data, psychophysiological data and other bio-parameters of the user. This may be done as part of a closed loop feedback control. In this way, the calming I relaxing effect of the VR environment presented to the user may be personalised to the specific user. As different users may respond differently to different calming VR environments, an enhanced more effective calming effect may be achieved. According to a second example of the present disclosure is a method of operation of a personalisable stimulation system, such as an extended reality (XR) system, for presenting a personalised environment to a user. The stimulation system may be a stimulation system according to the first example. The stimulation system comprises: at least one extended reality delivery system for delivering an extended reality environment for the user; and a plurality of sensors for monitoring the user. The method comprises controlling and / or adapting the extended reality environment delivered to the user based on output from the plurality of sensors. According to a third example of the present disclosure is a computer program configured such that, when implemented on a controller of an adaptable stimulation system, such as an extended reality (XR) system, for presenting a personalised environment to a user, causes the controller to control and / or adapt the personalised environment delivered to the user based on output from a plurality of sensors. The stimulation system may comprises a stimulation delivery system that provides the personalised environment to the user; and a plurality of sensors for monitoring the user. According to a fourth example of the present disclosure is a feedback based presentation system, the presentation system being configured to provide a visual presentation to a user, and comprising or being configured to communicate with one or more sensors for monitoring the user, wherein at least one of the sensors comprises at least one imaging sensor for imaging at least part of a user, and a processing system of the presentation system being configured to determine, based at least in part on the imaging of the user by the at least one imaging sensor, the an attention level of the user whilst viewing the presentation; and to adapt the presentation based at least in part on the determined attention level. The presentation may be or comprise a video or one or more images. The presentation may comprise a mechanism of action (MOA) presentation, e.g. video. The at least one imaging sensor may be for imaging at least part or all of a head or face of a user, such as eyes of the user. The at least one imaging sensor may be configured to track head movements of the user. The at least one imaging sensor may be configured to track eye movements, eye opening and closing and / or pupil dilation of the user. The processing system may be configured to determine the attention level of the user at least in part on the imaging of at least part or all of the head or face of the user by the at least one imaging sensor. The processing system may be configured to determine the attention level of the user at least in part on at least one of: the determined head movements, eye movements, eye opening and closing and / or pupil dilation of the user. The adaptation of the presentation may comprise adapting at least one playback parameter of the presentation. The at least one playback parameter of the presentation may comprise an aspect of the presentation other than the visual content, e.g. video images, of the presentation, i.e. the same video images may be played but may be displayed differently or with different audio or otherwise differently executing the same video images. Alternatively, the adaptation of the presentation may comprise varying the visual content, i.e. by selectively switching visual content. The at least one playback parameter may comprise at least one of: colour, music or other audio, darkness, lightness, brightness, contrast, gamma correction value, and / or the like. The adaptation of the presentation may comprise adjusting the colour scheme of the presentation based on the detected attention level, e.g. so that vibrant or more vibrant colours are used to enhance viewer engagement when a user attention index is trending downwards, e.g. for at least a threshold period of time or amount, or is below a threshold. The adaptation of the presentation may comprise adjusting, switching or otherwise varying audio accompanying the visual content. The adjusting, switching or otherwise varying of the audio may comprise making the audio louder or switching to more dynamic, faster or more attention-grabbing audio when the user attention index is trending downwards, e.g. for at least a threshold period of time or amount, or is below a threshold. The adaptation of the presentation may comprise adjusting the darkness or lightness levels or contrast, or brightness of the visual content based on the detected attention levels of the user. The adjusting of the darkness or lightness levels may comprise increasing or decreasing luminance, e.g. by increasing luminance with decreasing interest level or attention of the user and vice versa. The presentation system may comprise or be configured to access computer readable storage storing a plurality of pre-defined adaptations to the presentation and an attention level or attention level trend or profile associated with each pre-defined adaptation. The processing system of the presentation system may be configured to adapt the presentation by selecting and applying a pre-defined adaptation from the plurality of pre-defined adaptations having an associated attention level or attention level trend or profile associated matching or closest to the determined attention level. The presentation system may be configured to thereafter provide the presentation having the selected adaptation applied to it. Alternatively or additionally, the presentation system may comprise or be configured to access a presentation adaptation model, which may be an artificial intelligence (Al) model, which may be trained or otherwise configured to output a most appropriate adaptation of the content for a given input attention level or other state or index of the user. The processing system of the presentation system may be configured to adapt the presentation by inputting the determined attention level of the user into the presentation adaptation model and obtaining the adaptation to the presentation output by the presentation adaptation model based on the input attentional level of the user. The presentation system may be configured to apply the adaptation to the presentation output by the presentation adaptation model based on the input attentional level of the user to the presentation and thereafter provide the presentation having the adaptation applied to the user. The presentation system may be configured to dynamically train or otherwise update the presentation adaptation model based on determinations of user attention in use. For example, the presentation system may comprise or be configured to access a recommender model or generative model configured to identify trends or other patterns or profiles in attention level and recommend associated adaptations to presentations based on or associated with the identified trends or other patterns or profiles in attention level. The presentation system may be configured to dynamically adapt the presentation, i.e. whilst the user is viewing the presentation, based on the determined attention level of the user. According to a fifth example of the present disclosure is a telehealth system comprising, or configured to communicate with, the adaptable stimulation system of the first aspect. The telehealth system may comprise: a data reception module configured to receive data such as real-time user biometric data, user activity data, and / or user environmental data from the adaptable stimulation system; a data processing unit configured to analyze the received data to identify health-related trends from the received data, and generate health insights or alerts based on the analyzed data, e.g. at least ion part from the identified related trends; a communication interface configured to communicate, e.g. in real-time with a remote party system, such as a system of healthcare professionals or caregivers. The communication interface may be configured to communicate, e.g. in realtime with the remote party system using high capacity data communications such as via 5G cellular communications, Wi-Fi 6 or 6E or the like. This may beneficially reduce lag and improve the alerting. The telehealth system may comprise a data integration system. The data integration system may be configured to aggregate and / or integrate the data (for example the real time data), e.g. the real time user biometric data, user activity data, and / or user environmental data from the adaptable stimulation system with additional health-related data, which may include but not is limited to microbiome data, health tracking data, and / or historical health data. The data integration system may be configured to correlate and / or analyze the integrated data to provide health status assessments, which may be in real time. The telehealth system may comprise a feedback and / or alerting system. The feedback and / or alerting system may be configured to provide health feedback, e.g. real time health feedback, to the user and / or the remote party system. The feedback and / or alerting system may be configured to provide the health feedback in use and / or on the fly based on the analyzed data. The feedback and / or alerting system may be configured to generate real-time alerts or recommendations, and may be configured to provide these to the user and / or the remote party system (e.g. of healthcare professionals and / or caregivers) when specified patterns such as unusual or critical health patterns are detected. The feedback and / or alerting system may be configured to facilitate telehealth consultations and / or remote monitoring of the user's health by the remote party system, e.g. by healthcare professionals or caregivers using the integrated health data. The feedback and / or alerting system may be configured to store historical health data and trends for subsequent analysis, monitoring, and / or user engagement. According to a sixth example of the present disclosure is a method for determining mental and / or emotional states. The method may comprise receiving EEG signals, which include but are not limited to alpha, beta, delta, and / or gamma waveforms. The method may comprise combining at least two or more of the EEG signals, and / or any of the component waveforms. The method may comprise processing these signals through linear or non-linear combinations to derive a comprehensive signal profile, including but not limited to a specifically defined alpha to beta ratio (RAB). The method may comprise utilising this signal profile to inform an AI / AGI engine. This method is characterised by its capability to integrate and analyse the individual and combined effects of alpha, beta, delta, and gamma EEG signals in a linear or non-linear fashion. The inclusion of the RAB, as exemplified in a controlled clinical study, demonstrates the method's efficacy in indicating stress or the absence of stress in adult participants, evidenced by statistically significant differences in RAB values. This validation underscores the method's precision and reliability in interpreting mental and emotional states based on EEG signal analysis. The method may comprise method steps corresponding to any of the features described above in relation to any other example. According to a seventh example of the present disclosure is a method for optimising the assessment of mental and emotional states in real-time and offline modes. The method may comprise receiving and processing a plurality of biosignals, including but not limited to at least one or more or any of: EEG signals (encompassing alpha, beta, delta, and gamma waveforms), ECG signals, PPG signals, and / or respiratory rate data. The signals may be simultaneous signals. The method may comprise utilising an artificial (general) intelligence (A(G)I) engine capable of operating in both real-time and offline modes to identify the most suitable linear or non-linear combinations of these biosignals. The method may comprise generating an optimised metric for immediate or subsequent mental and emotional status monitoring. The method may comprise method steps corresponding to any of the features described above in relation to any other example. This method is characterised by its flexibility in processing, allowing for instantaneous analysis and feedback in real-time applications, as well as comprehensive data analysis and interpretation during offline processing. The Al engine is designed to adaptively learn from both real-time data streams and accumulated offline data, continuously refining its analysis and ensuring accuracy and reliability in diverse operational contexts. This dual-mode approach enables versatile applications, ranging from immediate monitoring in clinical or high-stress environments to detailed retrospective evaluations in research or therapeutic settings. The individual features and / or combinations of features defined above in accordance with any aspect of the present invention or below in relation to any specific embodiment of the invention may be utilised, either separately and individually, alone or in combination with any other defined feature, in any other aspect or embodiment of the invention. Furthermore, the present invention is intended to cover apparatus configured to perform any feature described herein in relation to a method and / or a method of using or producing, using or manufacturing any apparatus feature described herein. Brief Description of the Drawings Various examples of the present disclosure will now be described by way of example, and with reference to the accompanying drawings, of which: Figure 1 is a schematic of an adaptive XR system; and Figure 2 is a flowchart showing a process of operation of an adaptive XR system. Detailed Description of the Drawings Examples described herein relate generally to a sensory stimulation system for providing sensory stimulation to the user and in which a plurality of sensors are provided to monitor the user, the environment and / or other factors and a closed loop control process is used to vary the sensory stimulation provided to the user in order to optimise or improve a target metric, which could be indicative of a state or condition of the user such as stress, calmness, activity, unwanted activity, or the like, based on the output of the plurality of sensors. Particularly, the output of the plurality of sensors may be used to derive an index that reflects the target metric, wherein the index is optimised or improved by varying the sensory stimulation provided to the user as part of the closed loop control of sensory stimulation provided to the user. In examples shown here, the system is in the form of an adaptive XR system, particularly an extended reality (XR) system for delivering an immersive therapy, in which the XR system is adaptive to the user of the XR system, on the fly during use of the XR system, in order to tailor an immersive environment being delivered to the user in real time or near real time. However, the present disclosure is not limited to this and the stimulation, e.g. any or all of the visual, audio, haptic and olfactory aspects of the stimulation environment provided by the system, could be delivered by other stimulation delivery devices such as screens, displays, projectors, holographic projectors, smart glasses or other visual display devices (for visual aspects), speakers, headphones, earphones or buds, surround sound systems or other audio delivery devices (for audio aspects), wearable vibration devices, air or other gas blowing devices, electrical stimulators or other haptic delivery devices (for the haptic aspects) and / or scent release devices (for olfactory aspects). An example of a suitable XR system 5 is shown in Figure 1. The XR system 5 shown in Figure 1 is a fully immersive virtual reality (VR) system that comprises a headset 10, the headset 10 comprising a visual display component 15 for visually displaying an immersive environment to a user 20 of the XR system 5, and an audio presentation component 25 for providing an audio presentation to the user 20. The XR system 5 comprises a processing system 35 that controls the headset 10. The processing system 35 comprises a processor 40, a communications module 45, data store 50 and a power source 55. The processor 40 executes a computer program or app to control the immersive environment experienced by the user when using the XR system 5, including any content provided to the user 20 by the XR system 5. The communications module 45 is configured to communicate with the headset 10 and any other devices that contain biosensors 30 whose output that might be used by the processor 40 to determine how to adjust the immersive environment provided to the user 20 by the XR system 5. In examples, the communications module is a wireless communications module, e.g. a Bluetooth or Bluetooth low energy (BLE), orZigBee or Wi-Fi communications module, but could alternatively or additionally be a wired communications module for communication via physical connections. The data store 50 is configured to store the computer program or app executed by the processor 40 to perform the methods described herein. Optionally, the data store 50 stores images, video, audio, haptic and other content for provision to the user 20 by the XR system 5 to create the immersive environment. Additionally or alternatively, these can be obtained from a remote server or other remote or cloud based system. Optionally the data store 50 can also, at least temporarily or enduringly, store time stamped values for bioparameters of the user 20 collected using biosensors 30. The power source 55 could comprise a battery, generator or other power supply, particularly a portable untethered power supply, that is used to power at least the processing system 35 and optionally also the XR headset 10 and any biosensors 30. The processing system 35 could be embodied in a dedicated processing system comprised in or otherwise associated with the XR headset 10 and / or could comprise or be comprised in a user device such as a smartphone, tablet or laptop computer, and / or could be comprised in a remote server or cloud resource that is in communication with the XR headset 10 via the internet, the cloud or via a WAN, or the processing system 35 could be distributed between any or all of the above. In examples, the remote server or cloud resource that is in communication with the XR headset 10 and / or user or werable device via cellular or other wireless communications, particularly using high data apacity communications such as 5G, Wi-Fi 6 or 6E or the like, which may reduce lag. As such, the present disclosure is not limited to any one implementation of processing system 35. In examples, the headset 10 comprises a set of goggles, and the visual display component 15 is comprised in the goggles. In this example, the visual display component 15 comprises a pair of displays 15a, 15b optionally configured for stereo vision such that each display 15a, 15b is viewable by one respective eye of the user 20, so that an appearance of depth or 3D is conveyable by provision of images or video in each display 15a, 15b from a suitable perspective, as is known in the art. As alternatives to stereo vision, the visual display component 15 optionally could be or comprise a holographic display or comprise some other volume or virtual volume displaying device. Beneficially, the goggles can be configured to block out the real environment external to the user 20, so that the user only sees the visual aspects of the immersive environment provided via the displays 15a, 15b of the visual display component 15. Similarly, the audio presentation component 25 comprises a pair of speaker units 25a, 25b provided in respective ear enclosures for respectively providing audio components of the immersive environment to the ears of the user 20. The audio presentation system 24 is optionally configured for directional, surround, ambisonic or other immersive sound presentation to make it appear to the user as if the sound is originating at a location controlled by the XR system 5. The ear enclosures can be configured to exclude at least some, most or all sound from the environment around the user external to the XR system 5 so that the audio component of the immersive environment is substantively all the user hears. In examples, the audio presentation system 25 can be provided with a noise cancellation system for cancelling out external noise using mechanisms known in the art. Although the visual display component 15 and the audio presentation component 25 have been described in detail, other mechanisms for conveying the immersive environment such as haptic feedback (e.g. using electrodes, air emission devices or the like), scent release, and / or the like could optionally also be used. In examples, the XR system 5 is configured to provide a therapeutic immersive environment to the user 20. In some examples, the therapeutic immersive environment may be a stress reducing or calming immersive environment, designed to present a calming, tranquil immersive environment that blocks out the world around the user 20, in order to lower stress and increase calmness. The immersive environment can be designed to completely immerse the user 20 in an imaginary world or other environment that is designed to be without known stressors and to incorporate known calming features, e.g. calming colour schemes, slow gentle music or other audio, simple uncomplicated images and sounds and the like. However, it has been found that different users respond differently to different immersive environments and the efficacy of a given immersive environment can vary between users. Beneficially, the XR system 5 is provided with a plurality of sensors, which comprise biosensors 30 configured to monitor physiological parameters of the user 20. The biosensors 30 are configured to simultaneously measure physiological parameters of the user 20 so that the physiological parameters can be considered together to identify a state of user 20 (e.g. a calmness or stress index of the user 20) at a given moment in time and also the trends in the state of the user over time (e.g. increasing, decreasing or static calmness or stress index). The state of the user 20 or the trend in the state of the user 20 is used as basis for adapting the immersive environment provided by the XR system 5. The sensors could also include user activity sensors for monitoring the user, such as the head, eye and / or hand motion or orientation or other activity of the user. The sensors could also include environmental sensors for taking into account the physical environment around the user. In examples, the biosensors 30 include one or more or each of the group of sensors comprising: at least one electroencephalogram (EEG) sensor 30a, at least one heart sensor 30b, at least one oxygen saturation (SpOz) sensor 30c, at least one respiration sensor 30d, at least one user temperature sensor 30e, at least one skin conductance sensor 30f and / or at least one eye sensor 30g, or any combination thereof, which may include one or more other biosensors. The EEG sensor 30a may comprise a plurality of electrodes 30a’ on the scalp of the user 20 to detect brain activity of the user 20, i.e. at least one of the physiological parameters of the user 20 that is monitored is the brain activity of the user 20 in the form of an EEG signal. Particularly, the electrodes 30a’ can be arranged in the headset 10 so as to detect activity specifically from the frontal lobes of the user 20, e.g. by appropriate location on the headset. This is beneficial as the headset 10 sits on the user 20 in a defined way, so that the goggles cover the eyes of the user and the ear enclosures cover the ears of the user 20. As such, it is possible to locate the electrodes 30a’ of the EEG senor 30a in such a way as to collect frontal lobe brain activity of the user 20 in use. The at least one heart sensor 30b is configured to determine physiological parameters of the user 20 such as pulse or heart rate of the user and / or blood pressure of the user, e.g. via electrodes or an optical heart rate monitor. In examples, the at least one heart sensor 30b could be clipped to the ear of the user 20 or part of the ear enclosures of the headset 10 or could be incorporated in a smartwatch, chest strap or other separate device that wirelessly communicates with the processing system 35. The oxygen saturation (SpO2) sensor 30c, e.g. an oximeter, is configured to determine the oxygen saturation of the user 20 as a physiological parameter of the user 20, e.g. using optical techniques. This could also be clipped to the ear of the user 20 or part of the ear enclosures of the headset 10 or could be incorporated in a smartwatch, chest strap or other separate device that wirelessly communicates with the processing system 35. The respiration sensor 30d is configured to monitor breathing of the user 20 and can evaluate physiological parameters of the user 20 such as breathing I respiratory rate of the user 20. The at least one temperature sensor 30e is configured to measure the temperature of the user 20, e.g. the skin temperature of the user 20, as a physiological parameter of the user 20. The temperature sensor 30e could comprise an infra-red detecting temperature sensors, thermocouple, resistance thermometer, or other suitable temperature measurement device. The skin conductance sensor 30f is configured to measure conductance of the skin as a physiological parameter of the user 20 and is dependent on factors such as the amount of sweating of the user, blood flow of the user, amongst others. The skin conductance sensor 30f could comprise a plurality of electrodes in contact with the user’s skin, for example. The eye sensors 30g are configured to monitor the eyes of the user and could be configured, for example, to determine physiological parameters of the user 20 such as eyelid shutting or blinking, or eye I gaze tracking or other motion. This could be indicative of a user state such as a level of interest or tiredness, or the like. The biosensors 30 can be arranged in any suitable manner, and some or all of the biosensors 30 could be arranged in the virtual reality (VR) headset 10 or in a separate device that could be wearable or otherwise. For example, the EEG sensor 30a could be provided on the VR headset worn by the user 20 so that electrodes of the EEG sensor 30a contact the scalp of the user 20. Others of the biosensors 30 such as one or more or any of: the at least one heart sensor 30b, oxygen saturation (SpO?) sensor 30c, at least one temperature sensor 30e and skin conductance sensor 30f could be incorporated in part of the VR headset, e.g. in an on-ear device such as a clip-on on-ear device, which may or may not be comprised in the ear enclosures of the audio presentation component 25. In another example, the eye sensors 30g could be incorporated in the VR headset, e.g. in the visual display component 15 such as in the goggles and / or a housing covering the eyes of the user 20 and housing the displays that are viewable by respective eyes of the user 20. In certain examples, one or more of the biosensors 30 could additionally or alternatively be provided on at least one separate device worn or carried by the user 20. For example, one or more or any of: the at least one heart sensor 30b, oxygen saturation (SpO2) sensor 30c, the at least one respiration sensor 30d, at least one temperature sensor 30e and skin conductance sensor 30f could be incorporated in a chest strap or a smart watch or wrist band or other user mountable sensor device worn by the user. The at least one separate device could be configured to communicate, e.g. wirelessly communicate, with the processing system 35, so that the system has access to a suit of bio-parameters of the user 20 for any given time whilst the user is immersed in the immersive environment. The processing resource 35 is configured to dynamically adapt the immersive environment provided to the user 20 by the XR system 5 based on the values of the bioparameters of the user 20 collected by the biosensors 30 while the user 20 is experiencing the immersive environment, e.g. on the fly in real time or near real time. Beneficially, in some examples, the processing resource is configured to adapt the immersive environment dependent on a plurality of the bio-parameters of the user 20 that are analysed to determine a current (and optionally prior) state of the user 20, e.g. a cognitive, emotional and / or physiological state of the user, and to adapt the immersive environment based on the determined state of the user using a model or other adaptation logic. This process is outlined in Figure 2. In step 205, the XR system 5 is configured to provide an immersive environment to the user 20. The immersive environment can include one or more or each of: visual (e.g. images and / or video), audio and / or haptic content. Initially, the immersive environment could be a default environment, a selected or pre-programmed environment, a previous environment most recently provided to that user 20, an environment previously found to be beneficial to that specific user 20 or category of user 20, or the like. The processing system 35 is configured to adapt that virtual environment based on the bio-parameters of the user 20 obtained whilst subject to the immersive environment. In step 210, the plurality of bio-parameters of the user 20 whilst they are subject to the immersive environment are collected using the plurality of biosensors 30 described above, i.e. any, some or all of: the at least one electroencephalogram (EEG) sensor 30a, the at least one heart sensor 30b, the at least one oxygen saturation (SpO2) sensor 30c, the at least one respiration sensor 30d, the at least one user temperature sensor 30e, the at least one skin conductance sensor 30f, the at least one eye sensor 30g, at least one other type of biosensor 30, and / or any combination thereof. As examples, the bioparameters of the user 20 could comprise one or more or any of: an EEG of the user 20, the heart rate of the user 20, blood pressure of the user 20, the oxygen saturation of the user 20, the breathing rate of the user 20, the temperature of the user 20, the skin conductance or skin sweatiness of the user 20, a degree of eye closure, a degree of eye motion, a degree of correlation between eye motion and motion of one or more objects presented in the immersive environment, and / or the like. At step 215, the processing system 35 analyses the plurality of bio parameters to determine if, and how, the immersive environment is to be altered. In an example, the plurality of bio-parameters output by the plurality of bio-sensors 30, or derived from the outputs of the biosensors 30, is input into a model implemented using machine learning or other suitable technique (e.g. that comprises the application of artificial intelligence, generative networks, other algorithms, or the like). For example, the model may have been trained using suitably labelled training data or otherwise configured to output a value for one or more states (e.g. a cognitive state, a physiological state and / or a psychological state) of the user 20 based on inputs comprising the plurality of bioparameters of the user 20 determined from data collected whilst the user 20 is using the XR system 5 and exposed to the immersive environment. Optionally, the plurality of bio parameters output by the plurality of bio-sensors 30, or derived from the outputs of the biosensors 30 is time stamped with the time that it was collected to assist with determination of trends in the bio-parameters. The one or more states of the user 20 can be represented by at least one index, for example, at least one or each or any of: a calmness index value indicative of a degree of calmness of the user 20, a stress index value indicative of a degree of stress of the user 20, an attention index value indicative of an attention level of the user 20, a tiredness index indicative of a degree of tiredness or awakeness of the user, and / or the like. For example, the model may comprise a convolutional neural network (CNN) or other artificial neural network (ANN) or other appropriate machine learning or Al or generative model, and may be trained on manually or automatically labelled training data comprising previously collected or generated bioparameter data labelled with values indicating the state of a user associated with the bioparameter data. In examples, the model may comprise an input layer for accepting the input of the plurality of bio-parameters of the user 20 for a particular time, one or more convolutional layers configured to process the plurality of bio-parameters of the user 20 and an output layer for outputting the one or more states of the user 20. In step 220, it is determined if the parameters of the immersive environment need to be adjusted. This may comprise applying an adjustment logic that determines if the immersive environment is to be adjusted based on at least the values of the one or more states of the user 20 determined in step 215 and / or trends in the values of the one or more states of the user 20 determined in step 215. The adjustment logic could be implemented in any of various ways. For example, the adjustment logic could comprise an artificial intelligence (Al) model trained or otherwise configured to determine values, e.g. optimal values, of parameters of the immersive environment. These determined values of the parameters can be compared to the current values of the parameters of the immersive environment to determine if they need to be adjusted and, if so, to adjust the parameters of the immersive environment to the determined values in step 225. The adjustment logic could take other forms. For example, the adjustment logic could comprise a look-up-table (LUT), or an equation, or mapping that relates the values of the one or more states of the user 20 and / or the trends thereof to optimal parameters of the immersive environment, and the parameters of the immersive environment could be adjusted to the optimal parameters (225). In another example, the adjustment logic could comprise one or more criteria, such as a drop or rise in a trend of the index value or values of the at least one state of the user 20 being above or below a threshold. For example, if the state of the user is represented by a calmness index and the trend in the values of the calmness index exhibits a drop greater than a threshold, then the parameters of the immersive environment are changed to values associated with a more calming environment or an alternative calming environment. However, the above are provided as examples and the present disclosure is not limited to these examples of adjustment logic. The adjustment of the parameters of the immersive environment can take a variety of forms intended to change between different calming environments or to vary the extent of any calming effect provided. In examples, the parameter of the immersive environment that is adjusted comprises a playback parameter of the visual and / or audio and / or haptic content, such as one or more or any or each of: colour, music, darkness, lightness, brightness, contrast, volume of audio, different executions of the same video, and / or the like. For example, adjusting the parameters of the immersive environment could comprise adjusting the colour palette or colour histogram of the visual content delivered by the visual presentation component 15, e.g. shifting, skewing or otherwise changing the colour palette towards the blue or green end of the spectrum, and / or music or other audio can be made slower, calmer, or quieter or at least one of the visual presentation component, the audio presentation component and / or the haptic presentation component is switched to an alternative component associated with a higher degree of calmness and / or a greater reduction in stress, when it is determined that a calmness index is trending downwards or is below a threshold or a stress index is trending upwards or is above a threshold. In other examples, at least one or each or any of: the colours of the visual content delivered by the visual presentation component 15 can be made more vivid and / or brighter, the music or other audio can be made faster, more lively, louder and / or more strident, or the visual content and / or audio content and / or haptic content can be switched to content associated with a more stimulating effect responsive to a trend of values of the attention index dropping or being below a threshold or responsive to a trend of values of the tiredness index increasing or being above a threshold. However, the aim is to vary the parameters of the immersive environment to address changes in state of the user 20 and the variations in the parameters of the immersive environment are configured to achieve this. For example, if a value of a stress index is too high (e.g. above a threshold) or trending upwards, then more calming changes to the immersive environment are made and / or similarly if a calmness index is too low (below a threshold) or trending downwards. Conversely, if an attention index is too low (e.g. below a threshold) or trending downwards, then the immersive environment may be adapted to make it more exciting. If it is determined that the parameters of the immersive environment should not be adjusted, e.g. if the optimal parameters of the immersive environment haven’t changed or have changed less than a threshold amount, then the process simply loops back to step 205 and the same immersive environment continues to be provided to the user with the same parameters. This XR system 5 and method can be used in a range of applications. One application is as an adaptive therapy system for lowering stress or increasing calmness of the user 20. In this case, the XR system 5 is configured to determine values of a stress index or calmness index and adjust the immersive environment in a closed feedback loop process to try to minimise or reduce the stress index or maximise or increase the calmness index values of the user 20 or keep the stress index below a threshold or keep the calmness index above a threshold. In another application, the XR system 5 can be used to maintain user 20 interest in the immersive environment by determining values of an attention index and adjusting the immersive environment in a closed feedback loop process to maximise or increase the attention index values of the user 20 or keep the attention index above a threshold. Another example of use of the XR system 5 is to determine a mental state or status of the user 20. This may be done on the basis of biosignatures derived from the data obtained using the sensors 30. In this example, particularly beneficial examples of biosensors 30 that could be used to derive the biosignatures for the user include a photoplethysmography (PPG) sensor, the ECG sensor and / or the EEG sensor and any properties of the user derived therefrom as described above, but the example is not limited to these sensors and alternative or additional sensors could be used. The processing resource 35 is configured to configured to analyse the data from the sensors 30, e.g. the shape of the signals from the sensors, absolute values, relative values between sensor outputs and / or the like, and identify the biosignatures therefrom. The sensor data or properties derived therefrom (e.g. the biosignatures) can be used to identify communications between distinct regions of brain and topographies in sensor space (e.g. most informative EEG channels). These can be compared to representative data or analysed using a suitable model or algorithm to determine the user’s mental state or status. The determined mental status and / or the identified biosignatures of the user can be used to control the personalised XR environment provided to the user, e.g. by the stimulation delivery system. This could be used to manage the user, e.g. to vary the audio or other stimulations provided to the user in order to manage neurodegeneration. Whilst various specific examples have been provided above to aid understanding of the present disclosure, the scope of protection is defined by the claims and modifications to the specific examples described above within the scope of the claims is envisaged. For example, whilst specific examples described above are implemented in a VR or other XR system, the present disclosure is not limited by this. For example, the personalised environment need not be immersive and any or all of the visual environment, audio environment, haptic or other tactile sensations and / or olfactory or other scents delivered to the user as part of the personalised environment could be provided by other stimulation delivery devices such as screens, displays, projectors, holographic projectors, smart glasses or other visual display devices (for the visual environment), speakers, headphones, earphones or buds, surround sound systems or other audio delivery devices (for audio stimulation), wearable vibration devices, air or other gas blowing devices, electrical stimulators or other haptic delivery devices (for the haptic or other tactile sensations) and / or scent release devices (for scents or other olfactory aspects). Method steps of the invention can be performed by one or more programmable processors executing a computer program to perform functions of the invention by operating on input data and generating output. Method steps can also be performed by special purpose logic circuitry, e.g., an FPGA (field programmable gate array) or an ASIC (application-specific integrated circuit) or other customised circuitry. Processors suitable for the execution of a computer program include CPUs and microprocessors, and any one or more processors. Generally, a processor will receive instructions and data from a read-only memory or a random access memory or both. The essential elements of a computer are a processor for executing instructions and one or more memory devices for storing instructions and data. Generally, a computer will also include, or be operatively coupled to receive data from or transfer data to, or both, one or more mass storage devices for storing data, e.g., magnetic, magneto-optical disks, or optical disks. Information carriers suitable for embodying computer program instructions and data include all forms of non-volatile memory, including by way of example semiconductor memory devices, e.g. EPROM, EEPROM, and flash memory devices; magnetic disks, e.g., internal hard disks or removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks. The processor and the memory can be supplemented by, or incorporated in special purpose logic circuitry. To provide for interaction with a user, the invention can be implemented on a device having a screen, e.g., a CRT (cathode ray tube), plasma, LED (light emitting 5 diode) or LCD (liquid crystal display) monitor, for displaying information to the user and an input device, e.g., a keyboard, touch screen, a mouse, a trackball, and the like by which the user can provide input to the computer. Other kinds of devices can be used, for example, feedback provided to the user can be any form of sensory feedback, e.g., visual feedback, auditory feedback, or tactile feedback; and input from the user can be 10 received in any form, including acoustic, speech, or tactile input.

Claims

1. An adaptable stimulation system for providing a personalised environment to a user, wherein the stimulation system comprises:a stimulation delivery system that provides the personalised environment to the user and comprises at least one, any or all of:at least one visual delivery system for delivering an visual environment for the user as part of the personalised environment,an audio system for delivering audio stimulation to the user as part of the personalised environment,an olfactory stimulation system for providing one or more scents to the user as part of the personalised environment, and / ora haptic delivery system for delivering tactile sensations to the user as part of the personalised environment;a controller for controlling the stimulation delivery system to control the personalised environment provided to the user by the stimulation delivery system; anda plurality of sensors for monitoring the user; whereinthe controller is configured to control and / or adapt the personalised environment delivered to the user based at least in part on output from the plurality of sensors.

2. The stimulation system of claim 1, wherein the controller is configured to control and / or adapt the personalised environment delivered to the user based in part on preferences of the user and / or contextual information.

3. The stimulation system of any preceding claim, configured to create a user profile based on the output of the plurality of sensors for monitoring the user and optionally also the preferences of the user and / or the contextual information.

4. The stimulation system of any preceding claim, wherein at least one of the sensors comprises an electroencephalogram (EEG) system configured to detect, record and / or analyze brainwave signals or other electrical brain activity of theuser.

5. The stimulation system of claim 4, wherein the EEG system is configured to detect, record and / or analyze electroencephalogram (EEG) signals specifically from the frontal lobes of a user's brain whilst the user is experiencing the personalised environment provided by the stimulation delivery system.

6. The stimulation system of claim 4 or any claim dependent thereon, wherein the EEG system is configured to collect data in a plurality of channels and to extract and use only specified channels that form a subset of the collected channels.

7. The stimulation system of claim 4 or any claim dependent thereon, wherein the system is configured to determine a unique brain signature specific to each user based on the data obtained from the EEG signals whilst the user is exposed to the personalised environment.

8. The stimulation system of any preceding claim, wherein the plurality of sensors comprise at least one biosensor configured to measure physiological parameters of the user, wherein the at least one biosensor comprises one or more from: at least one heart rate sensor, at least one electrocardiogram (ECG) sensor, at least one blood pressure sensor, at least one skin conductance sensor, at least one temperature sensor, at least one oxygen saturation such as a peripheral oxygen saturation (SpO2) sensor, at least one eye sensor, at least one sweat sensor, at least one accelerometer, gyroscope or other movement sensor, and / or at least one respiratory rate sensor.

9. The stimulation system according to any preceding claim, wherein the controller is configured to determine one or more states of the user from at least one of: the one or more physiological parameters of the user from the plurality of sensors, the user profile and / or one or more trends in the one or more states of the user, the one or more states of the user comprising at least one of: an emotional state of the user, a cognitive state of the user, a physiological state of the user, a physical state of the user, a mental or mental health state of the user, and / or a psychological state of the user.

10. The stimulation system according to claim 9, wherein the one or more states of the user are represented by values of at least one of: a calmness index, a stressindex, an attention level index, an excitement level index, and / or an engagement index.

11. The stimulation system according to claim 8 when dependent on claim 3 or any claim dependent thereon, wherein the one or more states of the user comprise a value of the calmness index and / or stress index determined from identified signatures of calmness or stress derived from the EEG signals recorded from the frontal lobes of a user's brain whilst the user is exposed to the personalised environment.

12. The stimulation system of any preceding claim, wherein the controller is configured to control and / or adapt the personalised environment delivered to the user at least in part by:based on at least one or all of: the one or more physiological parameters of the user from the plurality of sensors, the determined one or more states of the user, and / or the user profile:controlling the audio system to control and / or adapt the audio stimulation to the user; and / orcontrolling the olfactory stimulation system to control and / or adapt the one or more scents provided to the user.

13. The stimulation system of any preceding claim, wherein the controller is configured to control and / or adapt the personalised environment delivered to the user at least in part by controlling the at least one stimulation delivery system to control and / or adapt the visual environment provided to the user.

14. The stimulation system of any preceding claim, wherein the stimulation delivery system is, comprises or is comprised in a virtual reality (VR) system and the personalised environment is a fully immersive environment in which a majority or substantively all of the visual and / or audio experience of the user is provided or providable by the VR system.

15. The stimulation system of any preceding claim, wherein the at least one stimulation delivery system comprises a headset that includes at least onedisplay unit configured to deliver visual aspects of the visual environment to the user.

16. The stimulation system of claim 11, wherein the controller is integral with the headset.

17. The stimulation system according to any preceding claim, wherein at least one of the plurality of sensors is provided in the headset and / or at least one of the plurality of sensors is provided in a wearable device worn or wearable by the user or a mobile device carried by the user.

18. The stimulation system according to any preceding claim, wherein one or more sensors from the group comprising: the heart rate sensor, the eye sensor, the skin temperature sensor, the motion and / or activity sensor such as at least one accelerometer or gyroscope, the EEG system, the ECG sensor, and / or the sweat sensor, are comprised in the headset or in an ear mounted sensor19. The stimulation system of claim 11 or any claim dependent thereon, wherein the visual content is or comprises a mechanism of action (MOA) video.

20. The stimulation system of any preceding claim, wherein the adaptation of the personalised environment comprises playing the same video content with different executions and / or display parameters.

21. The stimulation system according to claim 16, wherein the adaptation of the personalised environment comprises playing the same video content with a different colour pallet, different brightness, different contrast, different gamma value and / or different music or audio content.

22. The stimulation system according to any preceding claim, comprising an audio delivery system, the audio delivery system being configured to deliver audio content to the user, and the adaptation of the personalised environment comprises at least one or any of: changing the music or other audio content, changing a tempo or speed of the music or other audio content, changing theloudness of the music or other audio content; and / or changing the tone or pitch of the music or other audio content.

23. The stimulation system according to claim 7 or any claim dependent thereon, wherein the controller is configured to implement a content adaptation engine that receives data from the at least one sensor and adapts the personalised environment delivered to the user by the at least one extended reality delivery system using a feedback loop, wherein the feedback loop comprises:(i) providing the personalised environment to the user;(ii) determining the one or more states of the user and / or the trend in the one or more states of the user and / or a bio-parameter of the user derived from the one or more sensors whilst the user is experiencing the personalised environment; and(iii) adapting the personalised environment based on the determined one or more states of the user and / or the determined trend in the one or more states of the user and / or the determined bioparameter of the user derived from the one or more sensors.

24. The stimulation system according to claim 19, wherein the content adaptation engine is configured to implement adaptation logic or an adaptation artificial intelligence model that relates changes in the plurality of sensor outputs and / or the parameters based thereon with corresponding adaptations to the personalised environment.

25. The stimulation system according to claim 14 or any claim dependant thereon, which is or is comprised in a therapy delivery system configured to deliver an XR based therapy for stress or anxiety.

26. The stimulation system according to claim 20, wherein the controller is configured to determine a stress index or calmness index for the user from the outputs of the one or more sensors or a parameter derived therefrom.

27. The stimulation system according to claim 21, wherein the controller is configured implement a machine learning or other model to determine the stress index or calmness index.

28. A method of operation of stimulation system for presenting a personalised environment to a user, the stimulation system comprising: at least one stimulation delivery system for delivering the personalised environment to the user; and a5 plurality of sensors for monitoring the user; the method comprising controllingand / or adapting the extended reality environment delivered to the user based on output from the plurality of sensors.

29. A computer program configured such that, when implemented on a controller of10 a stimulation system for presenting a personalised environment to a user, causesthe controller to control and / or adapt the personalised environment delivered to the user based on output from a plurality of sensors.

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