The present invention relates generally to a sleeping aid and/or sleeping trainer and/or sleep monitor device.

Overview:

Poor sleep quality costs the UK economy an estimated £40.2 billion in loss of productivity [1]. It is associated with a weakened immune system, an increased mortality rate and an increased risk of chronic health conditions [2]. Poor sleep quality is a growing concern, particularly in children, where the number of diagnosed sleep disorders in children under the age of 14 has tripled in the last decade [3]. Sleep monitoring is a valuable process that allows data on sleep to be collected to manage and improve sleep quality. Current commercial solutions, however, are limited with tracking predominantly conducted using either contact-based tools such as a sensor mat or by video surveillance. Both of these techniques are a form of ‘actigraphy’, which correlates physical movement with phases of sleep. A key drawback for these methods is the high number of ‘false negatives’ they identify, as children may move significantly during REM sleep causing accuracy to be in some cases as low as 20% [3]: one study reported the accuracy of a Fitbit Flex device at just 19.8% [6]. This technique also involves a wearable or wired device around the bed, which in itself may be uncomfortable and hamper sleep.

Devices formed in accordance with the present invention may be referred to generally as “Sleepl”.

In some embodiments the present invention provides a sleep aid and monitor (for example a “Smart Sleepl”) designed to improve sleep for children between the ages of 3 and 8. Using a novel non-contact approach, the Sleepl monitors acoustic parameters that determine breathing cycles and also provides a non-clinical assessment of Sleep Disordered Breathing (SDB). SDB affects 1 in 10 children but is currently only diagnosed with laboratory-based techniques that can be uncomfortable and frightening. By highlight respiratory abnormalities, the Sleepl could help reduce time to diagnosis and ease growing demand for sleep services in the UK. Deriving sleep quality and SDB severity metrics for paediatric sleep using breathing sounds is a unique, complex and high-risk challenge, not yet incorporated into commercially available products.

In 2006, The Institute of Medicine of the National Academies released a report [4] detailing the significant links between sleep deprivation and health. Sleep deprived people are more likely to have a weakened immune system, have chronic health conditions such as obesity and diabetes, and have an increased mortality rate. Furthermore, one in three adults are not getting enough sleep and poor sleep corresponds to a significant loss in economic productivity, with a RAND study (2) estimating that poor sleep results in a cumulative economic impact of over £50 billion, or 2 percent of GDP. Levels of sleep deprivation across all ages as discussed, have a significant impact on the economy and societal health but sleep deprivation among children is more significant still, as caregivers have disrupted sleep as a consequence. The Institute of Labour Economics have released a report on “Child Sleep and Maternal Labour Market Outcomes” (3) demonstrating the impact of child sleeping patterns.

This report demonstrates the economic sensitivity to maternal sleep with key results showing:

• 30 minutes extra in a mother’s sleep duration increases household income by 4.95%

• 30 minutes extra in a mother’s sleep duration increases employment by 2.5 points

• 30 minutes extra in a mother’s sleep duration increases the number of hours worked by the mother by 7%

These findings are significant in demonstrating the importance of childhood sleep.

The present invention may provide or employ cutting edge advancements in digital signal processing (DSP) and Machine Learning to monitor and report sleep quality information, in detail exceeding that of commercially available products. Sleep quality tracking devices are generally targeted towards the adult market, yet for many parents and caregivers, the key to better sleep lies with their children. In some embodiments the present invention aims to help children improve, understand and take more responsibility for their own sleep, while providing parents/carers with the detailed information they need to improve the bedtime routine.

The present invention addresses these problems by measuring sleep differently. In an industry first, embodiments of the present invention aim to derive a sleep quality metric by analysing the sound of a child’s and adult’s breathing during the night.

The child is entertained by the device in the form of an interactive game which is designed to encourage good sleep patterns and rewards the child if they sleep well, thereby making the parents’ lives easier and giving them a better night’s sleep also. In the background, the device is also gathering important data to help inform the parent of their child’s quality of sleep.

There is, at the moment, no other electronic toy on the market which helps children stay in bed through developing a relationship with them, while safely gathering data on the child’s sleep in the background. Embodiments may provide or relate to an interactive sleep device that encourages kids to stay in bed through the night.

Some embodiments may act like an electronic pal for young kids, sitting proudly on their bedside table or nearby surroundings.

Some embodiments may be provided or developed into two versions, LITE and Smart. The Smart version having a full, bespoke monitoring and interactivity technology, and incorporating algorithms designed to detect abnormal sleep breathing disorders or sleep/awake patterns and alert the user via a bespoke mobile app.

Embodiments of the present invention can seek to make parents’ lives easier without compromising on style, innovation or fun. Embodiments will emerge as the all-round solution for reliable, super-innovative lifestyle devices for sleep assistance.

Some aspects and embodiments are designed/configured for children; other embodiments could be designed/configured for older individuals. For example, the overall design, monitoring features, interaction features and displays could be configured to suit a user.

Aspects and embodiments of the present invention may provide or relate to an interactive sleep trainer/aid which is designed to help children sleep better, as well as track the child’s sleep over the period of a week. The Sleepl has three modes: a ‘rest mode’ designed to sooth the child and get them to sleep, a ‘night mode’ during which the Sleepl night light will activate, and a ‘day mode’ during which the Sleepl is on sleep mode.

In some embodiments a device is provided in a form reminiscent of a bird (such as an owl), or cute bird/cat/alien representation and may use a combination of buttons and touch screen interaction to activate and display the different modes, along with a timer system, motion sensors, hand gesture sensors and sound recognition to determine when the child is awake, and produces sounds and coloured lights to help the child go back to sleep. The Sleepl’s eyes may also be activated by the buttons / sound activation within the various modes.

Sleep Monitoring:

Feature: Tracks sleep by listening to breath noises without using a contact-based or surveillance-based system.

Feature: Provides detailed feedback on sleep quality via a mobile app.

Feature: Indicates inconsistent breathing patterns offering a non-clinical recognition tool for sleep disordered breathing.

Sleep Aid:

Feature: Guided breathing exercises and calming music/sounds to encourage mindfulness practice and high-quality sleep.

Feature: Recognises when the child has woken up. Feature: Rewards-based games with animations in the Sleepl’s eyes which encourage good sleep behaviour and provide an educational element which parents can use as discussion points with their children.

Sleep Training:

Feature: Smart Sleepl’s alarm can be set to only wake the child when they have had sufficient sleep.

Feature: Sleepl is a happy little guy who likes his sleep a lot. If the child has slept well, Sleepl will be in a buoyant mood when the child wakes up.

Using a novel non-contact approach, the Sleepl monitors acoustic parameters that determine breathing cycles and also provides a non-clinical assessment of Sleep Disordered Breathing (SDB). SDB affects 1 in 10 children but is currently only diagnosed with laboratory-based techniques that can be uncomfortable and frightening.

The Smart Sleepl employs cutting edge advancements in digital signal processing (DSP) to monitor and report sleep quality information in detail, exceeding that of commercially available products. We aim to help children understand and take more responsibility for their own sleep and provide parents/carers with the detailed information they need to improve the bedtime routine.

Current sleep trackers use two main techniques to provide a sleep quality metric: sensor mats/pad and video analysis. Both of these techniques are a form of ‘actigraphy’, which correlates physical movement with phases of sleep. A key drawback for this method is the high number of ‘false negatives’ they identify, as children may move significantly during REM sleep and as such the accuracy can fall below 80% (1). This technique also involves a wearable or wired devices around the bed, which in itself may hamper sleep. Imagine a child trying to sleep with wires and gizmos all over their body.

The Smart Sleepl addresses these problems by measuring sleep differently. There are no wires. Just a simple, cute device that sits on the bedside table, analysing the sound of a child’s breathing during the night.

Key technological innovations and innovative features:

Non-Contact Sleep Quality Tracking

Non-Clinical Assessment of Sleep Disordered Breathing (SDB) The Smart Sleepl may implement advanced pattern matching and machine learning algorithms on its microcontroller and/or cloud computing platform to further process respiratory audio and make a non-clinical assessment of the severity of SDB detected. Research into the sounds associated with the SDB has highlighted a number of audio parameters such as changes in respiratory rate, spectrum of the audio signal and periods of silence that can be combined into an ‘acoustic biomarker’ and related to the severity of SDB.

The Smart Sleepl may use an innovative app-based interface, designed with user experience in mind, to communicate the severity of SDB. It will also allow parents and caregivers to listen to “problem” segments of their children’s breathing.

Breathing Exercises to Address Behavioural Insomnia in Children (BIC)

The Sleepl helps to ease this anxiety and reduce the burden on the parent/caregiver by provide the unique ability to lead breathing exercises at bedtime. These exercises help to associate sleep with the Sleepl rather than the physical presence of an adult. Sleepl may achieve this by pulsing and changing the colour of its nightlight in time with suggested inhale/exhale patterns. With its constant monitoring of sleep quality, Sleepl can detect whether the child has woken up during the night and initiate the breathing exercises once more.

Communication of Sleep Behaviour through ‘Virtual Friendship’

Providing sleep quality information through the app interface allows parents/caregivers the opportunity to change bedtime routines. In an industry first, however, the Sleepl also presents this information directly to the child in a fun and intuitive manner. The Sleepl contains a number of outputs, including an LCD touch screen with animations and eyes to communicate a ‘mood’ that is related to the sleep quality of the previous night: happy and playful after a night of high sleep quality and solemn after a poor sleep and/or night time wake ups, plus in some embodiments it might have 7 LED lights to signify the days of the week. The intention of this behaviour is to utilise the sympathetic emotions that develop during early childhood to pass some of the responsibility for good sleep from caregiver to child.

Sleep Deficit tracking: The ’Sleep Bank’

The amount of time we sleep is like putting money in a bank account. Whenever we don’t get enough, it’s withdrawn and has to be repaid. Chronically losing sleep has the potential to cause many health problems. It can put individuals at an increased risk for diabetes, a weakened immune system, and high blood pressure. It can also lead to higher levels of cortisol, a stress hormone. This can lead to anger, depression, and even suicidal thoughts. In addition, drowsiness increases the risk of falling asleep behind the wheel and getting into an accident. Getting more sleep can help the body stay healthy. It protects the heart and helps keep blood pressure low, appetite normal, and blood glucose levels in the normal range. During sleep, the body releases a hormone that helps growth. It also repairs cells and tissue and improves muscle mass. Adequate sleep is good for the immune system, helping to ward off infections.

A reporting system will be created which will track the amount of sleep and record it via an accompanying mobile app in a way which shows the parent/guardian how much sleep the child is achieving and how much extra sleep they may need to catch up on.

Further features:

Adaptive Noise Suppression of Non-Respiratory Sounds

An important, and unique, feature of the Sleepl will be the ability to isolate breathing sounds from all other extraneous sounds in the room. The technology derived from this will also be adapted for other devices and made available on the market. Many homes are located in close proximity to railway lines, or in busy cities and towns with constant traffic noises throughout the day and night. Our noise suppression device could cancel out some of those sounds (similar to noise-cancelling headphones which currently exist), creating a more peaceful ambience in the building and making it easier to sleep or concentrate on tasks.

Accurate Derivation of Sleep Quality Metric from Respiratory Audio

Key features identified are:

• Breathing pattern - e.g. cycle time, cycle consistency and intensity. It is anticipated that there will be particular challenges involved in applying this to children as the rate of breathing changes significantly with age.

• Snore properties - features that indicate heavier breathing associated with sleep phases. Again, it is anticipated that the audio properties associated with snoring in children will be significantly different from those in adults.

The Sleepl aids children/adults to calm down and relax, helping them fall asleep using a combination of sound and visual effects.

Other products:

On-device processing using a suitable microcontroller This method would require a powerful microprocessor and suitable storage incorporated into the device electronics. The algorithms would have to be ported to lower-level programming languages such as embedded C to allow them to run on the hardware. The microprocessor required for this approach may be costly in comparison to other components in the Bill of Materials (BOM).

Streaming audio data to a cloud-based compute nodes for processing

This approach would require an “Internet of Things” (loT) platform to be developed on a cloud computing service such as Amazon AWS or Microsoft Azure. Such a system could be developed in a higher-level language such as Python that has a number of machine learning and big-data handling libraries readily available. Wi-Fi connectivity would need to be integrated into the Sleepl so that data could be uploaded and processed quickly, with commands sent back to the Sleepl from the cloud to invoke the required outputs. This system would mean some additional BOM cost for Wi-Fi connectivity and require long-term maintenance and computing expenditure for the lifetime of the product. It would, however, allow data sets to be collated and algorithms to be trained and improved centrally.

Intelligent Content Moderation Platform

Because of the growing appearance of repugnant content on their platforms, technology companies have had to create and implement content policies and content moderation processes that aim to remove these forms of content. They also tend to uncover and block accounts responsible for posting/sharing this content, from their products and services. The companies (online platforms) want to promote greater safety and positive user experiences on their services - but they also need to comply with legal frameworks that prohibit certain forms of content online. On the other side, in many countries worldwide, particularly the Western world, the Law limits the extent to which the government can set the rules for what type of speech is permissible.

In past years many smaller online platforms that host user-generated content have come under increased burden from governments and the public to remove the repugnant content. To fulfil that request, the companies should perform manual moderation, or adopt automated tools to improve their content moderation processes, many of which are based on artificial intelligence and machine learning. These smaller content providers are not able to develop their own automated content cleaner. They often employ personnel to manually clean the content.

Some embodiments of the present invention are aimed towards development of new standalone platform for intelligent content moderation (both text and audio) that will possess significant advantages. It will be an Al-based tool that will perform automated content premoderation (before it is published). Such a new automated moderation tool will reduce the involvement of time-consuming human moderation, and enable the moderation of various types of content (speech, text, images etc.):

1. It will be an independent, custom platform and as such it can be offered on the broader market to all interested clients (content producers and suppliers) that need to clean-up their content. Potential clients will include child storytelling providers, online lecturing, online conferencing etc.

2. Our tool aims to moderate both types of content - spoken and textual. We will create a custom NLP (Natural Language Processing) classifier that will be able to detect rude speech and content and perform sentiment analysis on content. The NLP classifier will be trained on text examples, e.g. large sets of documents that will be annotated by humans in order to indicate whether they belong to a particular category or not (e.g. rude content vs. clean content).

Tale Town Mobile App

The Tale Town mobile app may accompany the product. It will be a requirement to download the app in order to connect to the Sleepl, or other products, and set it up according to the user’s needs. In addition to this the app will act as a book library. Customers will be encouraged to subscribe on a monthly rolling contract basis and they will receive credits to download a set number of audio books per month. The app can act as a stand-alone storytelling device, or the books can be streamed to the Sleepl, giving the child access to their favourite books to listen to before bedtime or whenever they choose.

The concept of the app and device interacting for storytelling: parents/guardians can read stories on the app and at the same time press a button to make the bird (bedside device) react/respond, for example; the app reads ‘the lion -roared’ - and by pressing the button on the app the bird will make a roar sound which will make it seem as if the parent and the bird are telling the story together. Furthermore while the parent is reading a story on the app the story reaches a point where the bird will talk interactively, for example it will say ‘the bird replied “ I can fly’” and by clicking on that section the “I can fly” part will be said by the bird, which will make stories much more interactive and interesting for children to listen to and it will give the impression that the bird is alive and part of the story.

The device enables children to play bedtime stories of their choice. The stories can be updated through the Tale Town app which connects to the device. The bedside device shows emotions with different eye animations played on the LCD screen. The reward system encourages children to sleep on time and wake up on time. If the child presses the button on time, they are rewarded with unlockable cartoon features/animations and visual stickers/stars. The app enables a platform for sharing stories by professional and amateur story tellers. Parents can tell stories which can then be played/purchased both on the app and the device.

Interactive Hologram

The device may provide a fully functioning interactive hologram product with all of the capabilities of the device, but which can be tailored to suit each customer individually. The hologram may be an alternative to the device and may interact with the subject in similar, as well as more advanced, ways.

Interactive Pillow

Custom pillow with sensors to record breathing throughout the night. The pillow can also be a smart pillow which has an alarm and plays music/song/stories at night and can respond to children. The interactive aspect of the pillow will allow children to lay down and listen to the pillow and eventually fall asleep.

Accessories

Sleepl products can also be assisted with a wrist band that uses EMG recording. Other signal recording devices are anticipated (EEG, ECG, etc) in future that can talk with Sleepl products. The signals will be used to monitor sleep and other healthcare conditions.

Examples of Sleepl function:

Bedtime MODE (SLEEPL calms child ready for bed) 7.30pm - 8pm

For 30 minutes the Sleepl will do whatever it can to get the child to sleep. He is playful but calming.

NB: the 30 minutes runs from 7.30pm and not the time the child presses the button - in other words if the child presses the button at 7.45pm the Sleepl will only go into REST MODE for the remaining 15 minutes.

INPUT

BUTTON

At 7.30pm the moon moves over the BUTTON. This gives child opportunity to press button to activate REST MODE. The button glows for 30 minutes (parent can increase/decrease this) - gradually the crescent moon growing to fill the entire button.

The child presses button within this 30-minute window. This activates REST MODE.

After 30 minutes the button is full lit MOON colours. But the window to log a full night in bed has closed. The Sleepl remains like this until the button is pressed. If child presses button after 8pm, the Sleepl goes into NIGHT MODE. But the opportunity to log a full night of sleep has ended, even if the child presses the button at relevant time in morning.

LIGHT

The Sleepl is sensitive to bright lights. Bright light.

Low light (bedside table)

No light.

SOUND

Quick Noise

Long noise (3-10 seconds)

Long noise (10+ seconds)

OUTPUT

BUTTON

Sleepl goes into REST MODE for the remainder of the 30 minutes.

EYES become ‘ALERT’. Sleepl is PLAYFUL but tries to calm child.

Sleepl GLOWS ORANGE.

The Sleepl remains in REST MODE.

Sleepl enters NIGHT MODE (see below).

Sleepl is shy. Turns PINK. EYES express SURPRISE.

Sleepl shines gentle ORANGE. EYES express MILD PLAYFULNESS.

Sleepl body is gentle RED. EYES express WONDER.

LIGHT

Sleepl is shy. Turns PINK. EYES express SURPRISE.

Sleepl shines gentle ORANGE. EYES express MILD PLAYFULNESS.

Sleepl body is gentle RED. EYES express WONDER.

SOUND

Little forks of LIGHTNING appear on eyes (2 seconds). TWIT TWOO SOUND.

WIDE EYES turn to DISAPPROVAL. Sleepl makes IRRITATED sounds.

Sleepl opens his EYES WIDE and then 5 seconds later looks ANNOYED. Body shines soft INDIGO which turns to VIOLET suggesting anger. HUMMING NOISE.

Sleeping MODE (SLEEPL wakes up) 8pm - 7am

The Sleepl wants to look after the sleeping child. Sleepl is calming, gently helping the child to sleep.

INPUT BUTTON

If button is pressed..

If button is pressed and held. If button is pressed repeatedly during night mode.

LIGHT Dark room Light room

SOUND

Loud noise (short)

Loud noise (long) Whistling.

Singing.

OUTPUT

BUTTON WIDE EYES for 3 seconds.

Sleepl opens his EYES WIDE and then 3 seconds later looks CONCERNED. Body shines soft YELLOW which turns to WHITE, brightening the room.

Sleepl looks DIZZY. Sleepl WHISTLES in BROKEN LOOPS.

LIGHT Night light activates. Body glows CALM RED. Calming sleep-friendly colour.

Sleepl body glows calming YELLOW.

SOUND

Sleepl becomes ALERT. Eyes ATTENTIVE.

Eyes express TENDERNESS. Sleepl SINGS comforting TUNES. Sleepl WHISTLES to accompany child.

Sleepl WHISTLES (another melody) to accompany child.

Sleepl goes Ugh hum. (CLEARS THROAT)

Morning mode (SLEEPL goes into SLEEP MODE) 7am - 7.30pm The Sleepl wants to sleep during the day. By interacting with Sleepl during the day you’re essentially waking it up. He is playful to begin, but soon gets grouchy. Nearly all inputs/outputs differ from day to night.

INPUT BUTTON

At 7am the sun rises across the BUTTON. For FIVE MINUTES it rises, gradually growing to fill entire button.

If button is pressed during this 5-minute window (and NIGHT-MODE was activated correctly) the Sleepl CELEBRATES. If button is NOT pressed during this five minute window..

During DAY MODE; If the button is pressed

If the button is held

If the button is pressed repeatedly

LIGHT Light room (daylight)

SOUND

LOUD noise (short) LOUD noise (long)

OUTPUT

BUTTON

Sleepl EYES CELEBRATE.

Sleep hours logged. There are 7 small LED lights on the rear of Sleepl - one for each day of the week. The corresponding day will shine for a full night of sleep. If all 7 LEDs are lit after 7 nights of good sleep, they start to cycle new colours - red, orange, yellow, green, blue, indigo, violet.

Sleepl eyes THINK then expresses NONCHALANCE. Sleepl reverts to DAY MODE (SLEEP).

Sleepl eyes WAKE briefly. Sleepl looks DAZED.

Sleepl eyes suggest OFFENCE which turns to ANGER which turns to CROSSED-

EYES.

Eyes play BAT AND BALL

Sleepl whistles excitedly/plays a jingle.

LIGHT

Body stops glowing.

SOUND

Sleepl eyes WAKE briefly. DAZED. Sleepl eyes are IRKED.

Further examples of the device’s interactive capabilities are shown on pages 5 to 13 of the drawings.

Device Interactivity.

DEVICE INTERACTION

The product makes appropriate responses interacting with children, students, adults, and in general human beings. The device gives the impression of being alive. Several methods have been considered but not limited to for the interaction of the device: • Device-one to one interaction

• Device-audience interaction

• Multi devices interacting with audience

• Presentation support

DEVICE ONE TO ONE INTERACTION

The device can independently interact with a person. The interaction can be time based (device performs a set of activities at specific times), sensor based (movement, light, sound, etc) and can include artificial intelligence. The interaction can be both supervised (through the application) or unsupervised. The device responds when triggered by a user, for example, it reacts to sound inputs e.g. with a clap it whistles, button inputs e.g. if the buttons are pressed for a long time it will say “Ouch!, that hurts” and the eyes will be looking upwards to the area being pressed, light inputs e.g. when the lights are turned off the eyes on the LCD go dark and look tired and the LED on the device is turned on and dimmed. The triggers can be adjusted, edited, defined through the user’s application. The device uses sound analyses to understand a user’s tone. The Sleepl device can adjust its behaviour accordingly.

All adjustments can be made through the device’s application. Blocks are used as an easy way to add remove functions for the device. When a sound block is added in the content e.g. a whistle sound, can be played on -Autoplay- or -Click to play-. In -Autoplay- the sound is played once the bird reaches that section. With -Click to play- the device will stop at that point and wait for the user’s input. When using the command of the user the bird will wait for the user. A range of gadgets/controls/devices can be connected to the bird for activating click features such as mobile phone, computers, presentation clickers, custom built controller, etc.

The user can use built in interactions, stories, songs,... Or they can build custom interaction experiences. The user can also use multiple birds and synchronise them to work with each other and each being part of an act.

Example of the user interface provided:

Product-Human Interaction - Figure 7 Device-Audience Interaction - Figure 8

The product plays a role in talking with an audience. Part of the presentation which needs to be said by the device is integrated into a mobile device. Once it is time for the bird to talk/sing/play animations, the presentation can activate it through the mobile device. The device has a wide range of applications such as for educational purposes. Multi Devices Interacting with Audience - Figures 9-11

Multiple products can be controlled through one mobile device, this enables the product to have unique features where each bird can have a different character and they can role play as separate entities at the same time. The role-playing acts can be purchased from the company or custom built by the consumer who can build their own scripts. In the process of role playing the screens can show relevant images & animations.

Multiple control units connected will work together to control one or all of the devices at the same time which allows for multiple people to work on /control one or several birds at the same time.

Multiple products can be controlled through one mobile device, this enabled for the product to have unique features where each bird can have a different character and they can role play as separate entities but at the same time.

Presenting Support - Figure 12

While presenting to an audience the device can be controlled by other people in the team in order to support the presenter. They can send direct messages to the presenter as suggestions. They can make custom responses for the device. For example, if the bird is responding to a question that has been asked, the support team can type the answer and the Sleepl will say it in its own voice.

The device uses sensors to track the movement of the presenter and provide relevant feedback. This can be assisted with a wrist band for higher accuracy. The movements can be used in the application to trigger commands in the bird.

The present invention is shown, by way of example, in the accompanying drawings, in which: Figure 1

Figure 2 - Example of eye movements.

Figure 3 - Views of the device 50 of Figure 1 .

Table 1 - Parts List

Figure 4 - Views of the device of Figure 1.

Figure 5 - Device Interaction.

Figure 6 - Device-Human Interaction. Figure 7 - Device-Human Interaction.

Figure 8 - Device-Audience Interaction.

Figure 9 - Multi Devices Interacting with Audience.

Figure 10 - Multi Devices Interacting with Audience. Figure 11 - Multi Devices Interacting with Audience. Figure 12 - Presenting Support. Figures 13 to 15 show a device formed according to a further embodiment.

In Figures 13 to 15 a sleep training device is generally indicated 250. The device comprises a body 255 having a display 260. In some embodiments the display is a touch screen; in other embodiments and LED array is used, for example.

The example embodiments are described and shown in sufficient detail to enable those of ordinary skill in the art to embody and implement the systems and processes herein described. It is important to understand that embodiments can be provided in many alternative forms and should not be construed as limited to the examples set forth herein.

Accordingly, while embodiments can be modified in various ways and take on various alternative forms, specific embodiments thereof are shown in the drawings and described in detail below as examples. There is no intent to limit to the particular forms disclosed. On the contrary, all modifications, equivalents, and alternatives falling within the scope of the appended claims should be included. Elements of the example embodiments are consistently denoted by the same reference numerals throughout the drawings and detailed description where appropriate.

Unless otherwise defined, all terms (including technical and scientific terms) used herein are to be interpreted as is customary in the art. It will be further understood that terms in common usage should also be interpreted as is customary in the relevant art and not in an idealised or overly formal sense unless expressly so defined herein.

In the description, all orientational terms, such as upper, lower, radially and axially, are used in relation to the drawings and should not be interpreted as limiting on the invention.

Although illustrative embodiments of the invention have been disclosed in detail herein, with reference to the accompanying drawings, it is understood that the invention is not limited to the precise embodiments shown and that various changes and modifications can be affected therein by one skilled in the art without departing from the scope of the invention. References:

1- D. Goldman, “Investing in the growing sleep-health economy,” 08 2017. [Online]. Available: https://www.mckinsey.eom/~/media/mckinsey/industries/private %20equity%20and%20principal %20investors/our%20insights/investing%20in%20the%20growing%2 0sleep%20health%20econ omy/investing-in-the-growing-sleephealth- economy. ashx.

2- H. Colten and B. Altevogt, Eds., Sleep Disorders and Sleep Deprivation: An Unmet Public Health Problem., Washington (DC): National Academies Press (US), 2006.

3- K. Bonuck, K. Freeman, R. D. Chervin and L. Xu, “Sleep-Disordered Breathing in a Population-Based v Cohort: Behavioral Outcomes at 4 and 7 Years,” Pediatrics, vol. 129, no. 4, pp. 857-865, 42012.

4 K. Bonuck, K. Freeman, R. D. Chervin and L. Xu, “Sleep-Disordered Breathing in a Population-Based Cohort: Behavioral Outcomes at 4 and 7 Years,” Pediatrics, vol. 129, no. 4, pp. 857-865, 4 2012. ); one study reported the accuracy of a Fitbit Flex device at just 19.8% (Source: M. Marino, Y. Li, M. N. Rueschman, J. W. Winkelman, J. M. Ellenbogen, J. M. Solet, H. Dulin, L. F. Berkman and O. M. Buxton, “Measuring Sleep: Accuracy, Sensitivity, and Specificity of Wrist Actigraphy Compared to Polysomnography,” Sleep, vol. 36, no. 11, pp. 1747-1755, 2013.)

5- M. Marino, Y. Li, M. N. Rueschman, J. W. Winkelman, J. M. Ellenbogen, J.M. Solet, H. Dulin, L. F. Berkman and O. M. Buxton, “Measuring Sleep: Accuracy, Sensitivity, and Specificity of Wrist Actigraphy Compared to Polysomnography,” Sleep, vol. 36, no. 11 , pp. 1747-1755, 2013.

6- J. F. Jeon Lee, “Consumer Sleep Tracking Devices: A Critical Review,” Studies in Health Technology and Informatics, vol. 210, pp. 458-460, 2015.