The three Finalists were:
*WEKIT — Wearable Experience for Knowledge Intensive Training — pitch by Paul Lefrere, Innovation Lead
*Sapien Labs (WINNER) — pitch by Tara Thiagarajan, Founder & Chief Scientist
*MyndYou — pitch by Shira Yama Nir, Project Manager
*Judged by: Bill Tucker, Senior Advisor to the K12 Education Program at the Bill & Melinda Gates Foundation; Eduardo Briceño, CEO and Co-founder of Mindset Works; John Cammack, Angel Investor; Neil Allison, Director of Business Model Innovation at Pearson North America
*Álvaro Fernández, CEO and Editor-in-Chief of SharpBrains
*Sarah Lenz Lock, Senior Vice President for Policy at AARP and Executive Director of the Global Council on Brain Health (GCBH)
*Dr. April Benasich, Director of the Baby Lab at the Rutgers Center for Molecular and Behavioral Neuroscience
*Chaired by: Dr. Cori Lathan, Co-Chair of the World Economic Forum’s Council on the Future of Human Enhancement
Slidedeck supporting session held during the 2017 SharpBrains Virtual Summit: Brain Health & Enhancement in the Digital Age (December 5-7th). Learn more at: https://sharpbrains.com/summit-2017/
Top Brainnovations harnessing Big Data
WEKIT — Wearable
Experience for Knowledge
Intensive Training — pitch
by Paul Lefrere, Innovation
Sapien Labs — pitch by Tara
Thiagarajan, Founder & Chief
MyndYou — pitch by Shira
Yama Nir, Project Manager
Bill Tucker, Senior Advisor to
the K12 Education Program at
the Bill & Melinda Gates
Eduardo Briceño, CEO and
Co-founder of Mindset Works
John Cammack, Angel
Neil Allison, Director of
Business Model Innovation
at Pearson North America
* Eg mirror neurons, UCLA Health Sciences: "Study identifies brain
cells that help us learn by watching others: Neurons also fire during
secret glee of schadenfreude.” ScienceDaily, 9 September 2016
IN 1 SLIDE: NOT Mind Meld fantasies
INNOVATIONS: Mirror neurons* with AR-support
We add wearable learning, inspired by neuroscience*, using
multiple senses/sensors, plus big data on: liminal/reflective
learning, tracking mistakes, becoming an expert, forgetting
WHO WE ARE
• Dr Paul Lefrere (Innovation, presenter) & Dr Fridolin Wild (CEO)
• Our project’s name is “WEKIT”: Wearable Experience For
• We began last year, as a $3m “Horizon 2020” R&D project based in
• Partners include universities, industry (eg helicopters, medical
scanners, space station)
• Collaborators include leaders in the EU’s Key Enabling
Technologies (KET) Ecosystems.
WHAT WE DO
• We leverage R&D from multiple domains to augment human capabilities
eg using big data
• We develop wearable AR platforms and sensor combinations to monitor
and help people
• Our new spin-out, WEKIT ECS: “Experience Capturing Solutions”, is to
raise our profile
• We provide the scientific lead for the IEEE VR/AR P2048 WG
• Our work wins Best Paper awards, eg for our Technology Acceptance
Model for VR/AR
• Our goal: a timely scale-out, starting 2018.
OUR APPROACH AND SOLUTIONS - 1
• The key to our approach is in the phrase ‘knowledge-intensive’. We
find neglected or intractable problems that arise from knowledge
gaps, eg have been the ‘elephant in the room’ for so long that they
are not noticed, or are accepted as ‘just how life is’.
• An example is ‘feeling confused or bored in class’. Another is ‘senior
• We solve such problems using novel and boundary-crossing mixes
of disciplinary knowledge, eg imagine a mix of Technology
Enhanced Learning plus Cognitive Science plus Big Data plus
Complexity Science. That’s what we work with. It can lead to more
affordable, effective, extensible and valued solutions.
OUR APPROACH AND SOLUTIONS - 2
• The WEKIT approach is to add wearable body/brain sensors to
today’s AR devices, to allow learners and experts to capture and
then share and literally feel the details of how they perform a task.
This is what we call a ‘Wearable Experience’.
• Applications: performance augmentation; updating; AR add-ons;
• Possible markets: precision brain health; dementia care
• Novelty, Scalability, Research & IP approach, Impact, Sustainability
• Novelty: “It’s always about timing. If it’s too soon, no one
understands. If it’s too late, everyone’s forgotten.” - Anna Wintour
• We’re timely in our novelty; we offer the first viable mass-market
solutions to the challenge of creating highly-personalized, affordable
and memorable AR experiences for people at all stages of life.
• Scalability: Our architecture got top marks for scalability and
interoperability in an external review by our public-sector funders
• Research: Our research collaborators and advisors include Big Data
labs such as the Knowledge Media Institute, and computer science
and neuroscience researchers eg at UCL.
• IP approach: Free IP where this will drive fast take-up and growth.
• Revenue models
• #1: license ways to add personalized Performance Augmentation
(PA) & Tracking to education & training.
• #2: service-based Freemium (eg to track & remedy fall-off in an
individual’s capability/memory/brain health)
• #3: service-based Premium (eg assisted living; real-time avoidance
of high-consequence knowledge gaps)
• Impact: Our open solutions, open standards and open knowledge
are the basis for many social innovations (eg we are partners of the
UK Open University, which is evaluating our learning-experience
model for possible large-scale adoption).
• Sustainability: Our initial funders, the European Union, have
numerous schemes to support highly-rated projects like WEKIT in
‘crossing the chasm’ from the R&D phase to Venture funding. Their
follow-on support has constraints (direct national/state aid to
subsidize sales is not allowed).
• Our focus is on combining Wearable Technology with Augmented
Reality and community- or team-based Big Data, to provide users
(individually or in teams) with new, valued, ethical and evidence-based
ways not only to acquire new knowledge and skills efficiently and
effectively, but also to improve someone’s ability to re-acquire forgotten
capabilities and facts, and to self-manage key aspects of their
• We have developed an architecture for capturing, editing, recalling and
re-purposing key elements of an individual’s or a group’s professional
or personal experiences and memories. This can provide evidence-
based ways to enhance the speed, accuracy and memorability of AR-
linked techniques for mastering skills and acquiring knowledge.
The need for large scale globally representative normative datasets
If we don’t know what normal looks like, how can we define dysfunction?
Metadata standards to
allow cross dataset
Standard sample sizes of 20-50 subjects are
insufficient given large inter and intra-person
2. Are you on any regular medication? Yes No
PleaseList Last Taken1.
Indoors - offic
Outdoors - sheltered
Indoors - home Outdoors - naturedominant
Indoors - lab Outdoors - urban dominant
Indoors - other Outdoors - open space
Location of Recording (Select all that apply within any one column):
3. If female, are you currently using oral contraception? Yes No
When was approximatelythedateof your last period? / /
nat ed Soda (Coke/
1. Please indicate if you have you consumed/used any of the following substanses in the last twenty four hours?
15. Other (Pleasespecify)
16. Other (Pleasespecify)
12. Please check any physical symptoms you are feeling right no w:
Headache Mild 1 2 3 4 5 Severe
Migraine Mild 1 2 3 4 5 Severe
Any kind of pain Mild 1 2 3 4 5 Severe
Nausea Mild 1 2 3 4 5 Severe
Upset Stomach Mild 1 2 3 4 5 Severe
4. How would you describe your overall mood on a scale from very negative to very positive
5. How physically energetic are you feeling right no w?
6. How mentally alert are you feeling right now?
7. How rested are you feeling?
8. How anxious are you feeling?
hours9. How many hours did you sleep last night?
hours ago10. How many hours ago was your last meal?
11. Are you currently experiencing any neur ological or health issues (please list)?
Verynegative VeryPositive1 2 3 4 5 6 7 8 9 10
Verynegative VeryPositive1 2 3 4 5 6 7 8 9 10
Foggy/Unfocused Very Alert1 2 3 4 5 6 7 8 9 10
Verytired Veryrested1 2 3 4 5 6 7 8 9 10
Relaxed Veryanxious1 2 3 4 5 6 7 8 9 10
Subject Name: Email:
Year of Birth: Gender: M F X
Cleaner, validated data that is not lost when the post doc leaves the lab
Better Data Management
Expanding the scope of
EEG beyond trained
EEG has become cost effective and portable
but the challenge for many is in analysis
Data management and research collaboration
EEG analytics tools
Videos and workshops
Bio engineering Physics
Neuroscientists Cognitive Scientists
Neurolab Partners Citizen Scientists
Novel analytical tools to find new structures and patterns in the EEG signal that are relevant to cognition and behavior
People aged 65+ world wide
An additional 1.1 million home health aides
and nursing assistants will be needed by
Washington Post, 2017
FROM DATA TO ACTIONABLE INSIGHTS
Care action plan
Passively collected voice,
activity, driving and sleep
Setting therapy goals
and assigning training
in day-to- day
Ask Robert about his
does he feel any change
Episodic Memory Training
List the products you need to
buy this week.
Sort the products by the
Real Time voice
analysis - generating
during the call