Anthromap

Traditional health services lack a holistic approach meaning that crucial patterns in a patients presentation are often missed. Technological advancements such as quantitive self devices, big data, and artificial intelligence allow us to bridge the gap between all services, and even a patients activity away from the hospital environment. The difficulty is, providing a system with a front-end that is understood by all stakeholders, including the service-user, carers, clinicians, researchers, and the developers/engineers developing new technology. It becomes even more difficult when you are dealing with conditions such as chronic fatigue, epilepsy, rare genetic mutations, and mental health conditions, where the pathology is unknown or difficult to quantify and/or accurately record.

A great example of a condition which highlights these deficits in the system and also the potential of such technology lies in the origins of Anthromap:

Matthew Francis Thompson, now 31, suffers from a genetic mutation called Dravet Syndrome. The syndrome is characterised by severe developmental delay and Epilepsy, with the highest incidence of SUDEP (Sudden Death by Epilepsy) in Dravet sufferers. 

Matthew was diagnosed at 16, prior to which, our family experienced many years of frequent, long and violent seizures. Clinical intervention was somewhat effective, but often the side-effects of medication outweighed the benefits. The stress of the situation led us to engage in our own research, which resulted in Matthew trying the Ketogenic diet and eventually a wheat/dairy and gluten-free diet. Although we cannot be sure, the interventions in diet led to a mammoth reduction in the severity, frequency and duration of his seizures. 

We were also aware of the following seizure triggers:

• Extreme temperatures or abrupt temperature change.
• If Matthew became shocked by external stimuli, i.e. dog barking. Also, if he tripped and fell.
• If he was tired and/or had not slept properly.
• Perfume/deodorant – strong odours.
• Allergy to animal fur.

With the aforementioned technological advancements, it is clear that most of the above seizure triggers can now be quantified. The trouble is, finding a methodology that allows all stakeholders involved in Matthew's care to accurately record and analyse this data.

Matthew's oldest brother, Craig, had always been aware of discreet patterns and triggers in Matthew's behaviour and seizure activity. It was not until 2008, when Craig attended University, while Matthew received genetic testing, that he began to investigate his curiosity.

When presented with the project title ‘Mapping your emotions’, Craig instantly thought of his love for his younger brother and the continuing struggle of living with a sibling whom has highly-complex needs. In turn, Craig decided to record a ‘day in the life of…’ Matthew. 

After recording everything Matthew did every 2-5minutes over a 24 hour period, Craig was not only exhausted, but also left with several thousand words with no obvious congruence and only 12 hours before his final deadline to create a map.

A moment of clarity led to the production of a 24-hour clockface, onto which he began to plot the data into concentric rings. Each ring allowed Craig to categorise the data into differing aspects of Matthews day, such as ‘nutrition’ or ‘ambient environment’. The radial order of the data was determined by the ‘distance’ of the data from Matthews body: meaning that the physiological data would appear at the centre and ‘ambient environment’ would appear on the outer-most concentric ring. Craig converted each piece of data into an icon or coloured shape and then plotted it on to the relevant ring, at the relevant time of occurrence. 

It wasn’t until during the critique when Craig noticed the potential in the Map he had created. A potential reflected in his head lecturer’s advice to ‘take things further’. Craig realised that if Matthews seizure activity had been plotted onto the Map, then they could visually track the behavioural pattern pathway leading to each seizure. 

Anthromap is a data visualisation tool, mapping cause and effect in service-user data. The initial application is epilepsy, aiming to allow the lay person to visually identify patterns and triggers in seizure activity, leading to interventions which will ultimately lessen the frequency, severity and duration of seizures, reducing the risk of SUDEP (Sudden Death caused by Epilepsy) and enriching the lives of those affected by epilepsy.

Once developed for epilepsy intervention, Anthromap will be extrapolated across other complex conditions. There is also scope for Anthromap to be used in the research field, identifying patterns and triggers which medical science has not yet discovered.

The interface will allow the user to alter the complexity of the data to suit their needs: for instance, selecting a red circle on the nutrition ring would then display a breakdown of that meal (imagine augmented reality/exploded diagram). This tool would also allow data to be overlayed/cross-referenced with data from previous hours, days or months, or even against other user data: A future hope is to use artificial intelligence and a universal database to identify links between distant users.

Often due to lack of funding, those with rare conditions battle with systems focused on more common conditions, providing inadequate linear interventions which treat one part of the condition, failing to address the comorbidity or over-arching, more fundamental condition.

Anthromap provides a holistic solution for the more complex, rare, and undiagnosed conditions, searching for the root cause of symptoms by utilising smart devices, mobile technology, and artificial intelligence to collect more subjective 'hard-to-reach' data and map it against other more robust datasets in the hope of identifying previously unknown patterns.

Anthromap will be accessible, because the focus is breaking down the barrier between clinicians, researchers, developers, and the service-user by creating a user-interface and visual language which can be understood by the lay person. 

The hope is to sooner provide answers to desperate service-users and their carers, and provide rigorous interventions which curtail the impact of those critical incidents, such as seizures, and the direct (brain damage) and indirect impact (stress on family members) that these incidents have on people. The patterns will then be used to streamline research and development processes, to ensure that clinical research and medical devices are developed in line with the heart of the problem - the service user.

Matthew had his first seizure at 6 months, when I was 4 years old. It lasted three hours, he turned blue due to lack of oxygen, and spent a week in hospital. 

I witnessed this.

There is nothing more potent than personal experience such as this. 

As a graphic designer, with a passion for and understanding of tech, and also sole creator and owner of Anthromap, I not only have an in-depth understanding of complex health conditions, but also of the technology we can use to solve these problems. 

I also have the skills to design and develop the visual language and user-interface for anthromap. 

Anthromap is essentially the Feynman Diagram of a person.

it looks beyond the existing available pathologies and provides a comprehensive overview of the past, present, and future of a service-users condition; including informal transactions and ambient/environmental data which wouldn’t normally be considered in the traditional clinical methodology.

Unlike most health-focused innovations which have a data-first approach, where the user-interface is a secondary fascade which is retrospectively applied to the data or the medical device, Anthromap is a user-interface led project which proposes the development of a holistic visual language which puts the power of identifying patterns and therefore pathology into the hands of the lay person and breaks down the existing dichotomies in global health services. 

Anthromap asks, what technology is available? how can we use this tech to bridge gaps? what links are there between services and conditions? How can we use design to make data accessible? What datasets are there available to us beyond the clinical realm? 

That said, I am under no illusion that my concept is fraught with difficulties. The most obvious is that links could be made between critical incidents in datasets which have no true link. However, I see Anthromap as a conceptual step into the unknown. Anthromap is the process of exploration which leads us to break down the seemingly impossible challenges that our modern health systems face. It asks, What if? rather than, 'but we can't'.

Anthromap provides an accessible platform which allows those with no prior knowledge of health conditions or research methodologies to spot the pattern of cause and effect in critical incidents present in complex health conditions in order to make accurate deductions about a service users needs and also implement rigorous interventions to help alleviate the symptoms of such conditions without the need for direct clinical input. 

Anthromap will strive to provide the most affordable insights and interventions ensuring that nobody is left behind, regardless of social economic status. 

Anthromap’s visual language will use simple visual devices such as using the colour red to denote critical incidents/dangers, without the complexity of the rigorous underlying data, meaning that we will have a primordial understanding of what a critical incident looks like. 

data input will come from:

* smart tech such as smart watches, seizure monitors, cameras (monitoring movement in the home)

* data entry by the service user or clinician into an iPad or smart phone app.

* historical database.

- data will be converted into visual datapoints on a 24-hour clockface.

- Links will be made across datasets, within the app and across historical datasets. Patterns will be identified and then insights presented to the service user/carer.

- neural networks and quantum computing will be harnessed to test out patterns and potential interventions against real-world scenarios.

- Machine learning will be used to learn from the 'hive mind' created by the Anthromap system.

- Blockchain technology such as taraxa will be used to provide fast and immutable recording of informal transactions. This will ensure the security go the system as well as the speed of transactions across the Anthromap network

The biggest risk is identifying links which aren't really there coupled with interventions which then prove dangerous, however this is the fundamental crux of traditional health systems. We need to explore the potential for connections in seemingly unrelated datasets in order to identify novel solutions to these problems.

Data entry will have to be simplified in a way which allows for the most comprehensive acquisition of data while also being understood by the lay person to prevent inaccurate data input. 

The Ai will have to be self-critical in a way which tests the theories before implementation. This could be done in a sandbox neural network which tests the patterns against real-world scenarios/conditions pre-implementation, mitigating the risk to the service-user.

As mentioned, blockchain (blockDAG) tech such as taraxa will be used to ensure the system is robust, fast, and secure. I see the Anthromap system as a matrix of 'blocks' where each study, such as Matthew and his epilepsy, will be a 'block' within a network of smaller and larger blocks. The system will be able to grow infinitely without ever jeopardising the structure or security of the system.

In the first year, my initial goal is to produce a proof of concept based around Dravet Syndrome (or possibly chronic fatigue), building a simple prototype which allows several stakeholders to input information, visually identify patterns, and implement low-risk interventions. I will hope to build a network of people across the whole spectrum of the Dravet Syndrome ecosystem, including service-users, carers, families, clinicians, nutritionists, researchers, charities, medical device manufacturers... etc. and also a network of developers with a common goal of looking at what the main dichotomies are, the technology which is now available, and how this can be utilised to break down those barriers in the system. 

The development of a sandbox for identifying patterns across datasets will occur organically as this project develops or I will find an existing system which can be adapted and bolted onto my project. 

In the second year, I will look at applying the same process to similar conditions, or a larger cohort of those with Dravet Syndrome.

In the third year, I would hope to have a visual language which helps to make complex datasets understandable to the lay person.

In the fifth year, I would hope to have a system which can help the lay person visually identify patterns of cause and effect in Dravet Syndrome, utilising the sandbox Ai to implement rigorous interventions, reducing seizure activity and stress of wider support system.

Me. But team development will be a fundamental part of the first year at CURE.

On and off since concept inception in 2008. Probably a few months to a year of work in total.

I am diagnosed autistic and possibly have adhd. Anthromap is pretty much a visual representation of the way I think.

My approach to life has always been to never take things at face value. To always question what is infront of me. And to strive to make things better for everyone. 

With firsthand experience as a carer for someone with complex needs, and also someone with my own disability, I can empathise wholly with anyone who has struggled.

I have also trained as an art teacher so have experience of differentiating my approach to suit the needs of a vast array of individual learning styles, attributes, and disabilities.

Currently, I do not have a structured plan for implementation. This is due to only discovering this opportunity a couple of days ago, realising that a project I had sidelined (Anthromap), was exactly what this SOLVE project was looking for. I realised several years ago that I would be unable to self-fund this project and also faced difficulties when trying to pursue my ideas locally - I was essentially silenced by the local NHS services. 

Excuses aside, below are some of the first steps I would take:

My primary goal will be to develop a strong presentation about Anthromap which I can take to networking events, conferences, and potential stakeholders in order to ruse their interest and develop partnerships.

I will develop an online portal which will allow potential stakeholders to engage and contribute. I will need to pay a web developer to do this.

The proof of concept will be ongoing development utilising my own skills as a designer, strategist, and animator, as well as paying for the services of a developer.

I will then engage with clinicians and service-users, utilising a simple surveying platform to discover the crux of the problems facing all stakeholders. I will require funding to travel and meet with these individuals.

I will require funded partnerships with a university or multiple universities, potentially exploring the potential of Anthromap as a phd and/or research project. As I have no experience of formal academic research, this would be a very robust way of embarking on this project. This does however require an academic supervisor/sponsor.

The development of a data entry app would also require the input of a developer. 

I may need volunteer service-users which will have to be paid expenses. Due to the rarity of Dravet Syndrome, this could mean travelling great distances to foster involvement.

My focus would be spread between the following areas:

1. A single application for Anthromap:

Dravet Syndrome - cause, effect, critical incidents in Dravet Syndrome. Discovering patterns in Dravet Syndrome we have not discovered before and developing unique interventions.

2. The technological aspects:

- Creating a technological system for the above process: developing a data entry app, an online portal for breaking down the dichotomy between the service-user, clinicians, and developers. Developing Ai to identify patterns. A sandbox for testing deductions and suggesting interventions.

3. The user-interface and user-experience.

- Developing a visual language which helps to 'map' out complex datasets and aid visual identification of the pattern of cause and effect across critical incidents.

My hope would be to develop a network and small team who could pursue research and development in the above 3 areas.

My hope would be to perk the interest of those across health services, including government commissioners who would see the potential in an application of this nature, providing funding for research and development. I would have an online presence; website, social media, and engage in online presentations to spread awareness of the project and its goals. I would hope that these presentations would be strong enough to facilitate paid speaking engagements at conferences/events.

Technological funding streams:

In the short-term, the development of small-scale data entry and analysis applications for Dravet Syndrome, or other complex conditions which could be sold on the App Store or sold on to bigger entities.

In the longer term, Anthromap as a multi-condition application which bridges the gap between service-user, clinicians, researchers, and developers. A system which helps to streamline the diagnosis and treatment of those with rare or complex health conditions.

I would develop datasets which could then be sold on to researchers and developers. 

current operating costs:

Cost of MacBook Pro - £3,000

Design Software - £50/month

Expenses - £1,000/month

projected operating costs:

Web development: £3,000 upfront, £200 monthly after initial outlay (approx.)

Software development: part time employment £25,000/year

funded research (phd or research project): £30,000/year

Expenses, including travel to Dravet Syndrome service-users and various scientists, clinicians, researchers...etc: £30,000/year

$100,000

The size of Anthromap as a concept is potentially huge, as is it's impact. Ensuring a robust research project and proof of concept is essential in ensuring the longevity of this project.

I need to dedicate full-time hours in research and design to ensure I fully understand the crux of Dravet Syndrome (or another complex condition) by engaging with many stakeholders, and also to understand the potential of technological advancements available to me.

The above requires employment of someone who can patch up my knowledge gaps so we can design and build an application which excites those who use it. 

I have not included my living expenses in the above, but believe the strength of my concept will help me find someone willing to host me in New York for the length of the residency.

Being in an environment where people are excited by innovation is a world away from what I am used to. I live in the North East of England where thinking like I do is more likely to get you into trouble than get you a funding opportunity.

Being surrounded by likeminded people whop can simultaneously plug my knowledge gaps will help give myself and Anthromap the platform it needs to excel in the world of medical tech.