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Leveraging data from wearable devices is a key next step for human-computer interaction and will be vital for frictionless metaverse experiences. The market for seamless, user-governed custodial solutions for wearables holds outsized impact and commercial upside.
All human wearable data will be owned and controlled by individual users through our privacy-preserving infrastructure, which will power safe and rewarding user experiences, including within and beyond the metaverse.
Highly personal wearable data (including brain data) is currently managed and stored by hardware providers and sometimes sold to their third-parties, with no way for users to provide detailed permissions. This raises ethical concerns and also stifles innovation; data is analysed with only proprietary algorithms, and wearable signals are not collated from different devices for holistic analysis. Users do not own or control their own data, they cannot permission exactly how it is shared with third parties, or govern its commercialisation.
LYNX is a backend data management system for real-time biometric user data collected through wearables and interfaces (including brain-computer interfaces (BCIs), fitness trackers and eye-tracking technologies). LYNX is able to amalgamate data from multiple wearables to create a true "digital twin". Users retain ownership over their raw data, while compute-to-data technology ensures safe interactions with third parties — including independent algorithm providers to revolutionise wearable UX, and Web3 marketplaces for tokenised rewards.
Wearables collect biometric data from the human body and digitally stream this for analysis to provide insights. Our initial focus is on neurotech wearables (i.e. non-invasive BCIs) as this data is highly personal. Therefore an ethical, user-centric solution (where users own and control their own data) is key to establish before this technology advances further. Our ultimate goal is for humanity's brain data (including from invasive BCIs) to not be owned or controlled by any one private company, or person. This is particularly important as traditional Big Tech business models exist around data farming. Therefore, there is a great danger to personal privacy and security if we leave this section of the market to these companies.
EEG sensors in particular are increasingly integrated with headphones to provide brain activity measures such as "attention" and "stress", and for training "mental commands". Current neurotech wearables are constrained by the quality of EEG signals and algorithm providers. However, sensors are becoming increasingly sophisticated (see further reading), and our solution enables AI companies to competitively develop algorithms to further advance neurotech.
The integration of wearable signals for holistic analysis has also been missing from current solutions. Currently, "biohackers" attempt to hack together such integrations, as the data infrastructure does not currently exist commercially. Both UX and mind-body understanding would be greatly improved by developing algorithms that integrate signals from multiple devices. For example, heart rate and physical activity data, analysed alongside BCI signals, could provide personalised in-depth insights into sports performance and training, from an integrated physical and mental perspective. The integration of such data is also important for general health monitoring, in addition to "digital medicine" (e.g. algorithms for the treatment conditions such as depression and chronic pain delivered through neurostimulation via BCI).
In addition to the emerging neurotechnologies mentioned above, Web3 technologies offer a new way of bringing together necessary building blocks for a world where individuals can own and control their data.
Web2 and platform economics can be compared to a zero-sum game; the platforms with the greatest number of users (in other words — data) win, and all others lose. However, Web3 technologies flip this business model on its head, and instead personal data is collected and controlled by the user. Users can permission their raw data how they see fit, and can be economically rewarded for doing so.
Furthermore, emerging compute-to-data capabilities (sending algorithms to the raw data so the raw data is never revealed to third parties) allow for personal data obfuscation.
Lastly, the data marketplaces coming to fruition (which are incentivised with tokenised rewards) allow for this data to be made available to not just those with the biggest market forces, but everyone — from a student working on a new idea, to employers looking into stress levels across different teams.
Although many of the technologies that our solution leverages are still emerging, our Web3 path has already been paved by the likes of Basic Attention Network (BAT), which rewards users for their attention. As the first crypto application to have more than 1 million users, this provides a proof-of-concept for this particular user experience, in addition to the wider concept of user-interaction rewards.