Using Big Data and Game Play to Improve Mental Fitness

Digital tools and data analysis to stay sharp, stay well, and overcome illness

This article was written together with Ellen M. Martin and Melinda Speckmann.

Games have been part of human culture for millennia. It is no surprise that elements of play can be powerful digital tools to grab our attention and keep us on a path to taking care of ourselves and others.

Big data is already behind brain games. The use of big data is becoming increasingly mainstream in health play applications. Once we are drawn in, game play (with big data under the hood) can help us to:

  1. Stay sharp,
  2. Stay well, and
  3. Overcome illness.

Staying sharp

Digital tools aim to make brain fitness fun by playing with the mental states our brains experience and project. Brain fitness games exercise different functions: short and long-term memory as well as accuracy and efficiency for processing information and solving problems.

Lumosity entered the consumer market with engaging user interfaces and now offers more than 40 games that challenge and train memory, flexibility, processing, speed, and problem solving. Two examples include Speed Match, which tests speed of visual processing, and Memory Matrix, which challenges the brain’s ability to remember spatial locations. Preliminary studies suggest that these games have beneficial long-term effects.

Using machine-learning algorithms, the games keep you interested by using feedback to deliver personalized questions for your engagement and by finding your learning sweet spot; not too easy but not too hard.

With over 50 million users and 1 billion game plays, Lumosity’s Human Cognition Project has launched 43 ongoing studies, exploring topics such as age-related cognitive decline, interventions for PTSD, and the relationship between physical exercise and Lumosity brain training.

Brain Resource aims to improve brain health, particularly to better diagnose and treat diseases of the mind such as depression and ADHD. The company began by building integrated, standardized data sets from screening questionnaires, cognitive assessments, genetic profiles, and MRI or fMRI scans. By standardizing measurement and procedures, the company can compare neural activity within various regions of the brain to better understand brain circuitry and interconnectedness.

The BRAINnet Database, (a.k.a. the Brain Resource International Database or BRID), available to global academic and research partners, has grown to 50,000 datasets. It includes 5,000 healthy controls from ages 6 to 100, plus more than 1,000 subjects with diagnoses such as depression, schizophrenia, and mild cognitive Impairment. Its standardization feature, unique among such databases, allows the comparison of brain function across disease states.

The insights derived from the BRAINnet Database have been commercialized into a brain assessment and training platform known as MyBrainSolutions. The brain training program is used by corporate wellness programs to promote brain health and resilience among employees. The site features 24 brain training exercises or games to improve cognitive and emotional functioning. In addition, MyCalmBeat facilitates control of stress, anxiety, and panic by providing feedback on heart rate.

Outcomes associated MyBrainSolutions include improved thinking and memory processes as well as emotional balance.

They are also among the first to perform clinical trials in the arena of ADHD and depression. Two global studies under the rubric International Studies to Predict Optimized Treatment Response (iSPOT) aim to identify biomarkers and develop companion diagnostics for these two areas.

CogniFit provides scientific assessments and brain training programs directly to consumers as well as to professionals in the area of cognition.

Both markets are still in their infancy. CogniFit is available in more than 13 languages and offers more than 50 different assessments and training tasks to measure and train this large number of cognitive abilities.

CogniFit dynamically personalizes the training programs it offers to its users on more than 25 key cognitive skills, such as working memory, eye-hand coordination, concentration, and response time.

With more than 150 cognitive variables tracking each training session and millions of data points for variables such as demographics, countries, skills and training programs, CogniFit is building a reliable and exhaustive cognitive database that is being used to develop new training regimens to further study the impact of mental health diseases on cognition and improve the development of preventive solutions for brain health.

Akili Interactive is tackling both game play and big data to build the first therapeutic mobile video games, using technology licensed from neuroscientist Adam Gazzaley at UCSF. A Nature publication shows how gaming can improve cognitive skills.

In the latest version of NeuroRacer, a 3D video game, players choose avatars that travel down a waterway. The game’s back end uses an adaptive algorithm based upon real-time performance metrics to create a real-time learning experience optimized for each player. Engaging individual learning styles and using big data to customize the learning experience, could increase engagement and exercise personal multi-tasking skills.

Digital tools can help close the feedback loop for individuals as well for populations, as shown in Figure 1.

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Figure 1. Positive feedback loop for health.

Staying happy

New digital tools are helping us to stay happier by making it easy and fun to track emotions, mood, sleep, and states of mind.

HeartMath offers a tool to help users stay calm. It reveals Heart Rate Variability (HRV), a measurement of the heart rhythm’s naturally occurring beat-to-beat changes. During positive emotional states, the heart rhythms show a stable and ordered pattern, which facilitates cognitive function. Using a completely different algorithm than MyCalmBeat (discussed earlier), but also providing heart rhythm feedback, HeartMath helps users learn to control their own emotional states.

HeartMath clinical studies have demonstrated a critical link between emotions, heart function and cognitive performance.

Lark is using elements of game mechanics and automated positive coaching to make sleep tracking more fun. It also uses the world’s largest sleep database to make its custom coaching algorithms more accurate. Lark aims to help users understand their own sleep patterns and pathology in order to sleep more effectively and wake up more refreshed. It’s a wrist alarm clock, too!

Headspace is using a game-like approach to make meditation easy and simple to incorporate into everyday life. On the Web or mobile device, daily deliveries of “bite-sized” tools, starting small (10 minutes a day for 10 days), lead the user to a regular meditation habit.

Overcoming illness

Game play and big data are less far along in managing chronic disease, but there are some early signs of progress.

Mango Health is a medication adherence app with a game design. Mango’s app, which sends text reminders and allows users to take pictures of their medication bottles, grants points for medication compliance. Like frequent flyer miles, points can be redeemed at major retailers such as Target or by making charity donations. It’s noteworthy that this app gives medication information and possible interactions for both mainstream and herbal medications. It also offers the ability to track medication history over time.

OneHealth and Ginger.io are two companies working on creating real time behavioral health data. At the front end, OneHealth is combines gaming elements, such as a recovery clock, badges for telling stories and attending meetings, and a variety of online patient support networks that can be customized based on individual needs, with active data collection. Personalized patient data is actively collected from five sources:

  • Programs
  • Utilization
  • Emotional index
  • Connection
  • Community

Feedback loops are used to create dashboards that can help patients see their progress and also be used by population managers.

In contrast, Ginger.io uses the passive collection of data that already exists on the user’s phone. The user installs the app, which then sends data on calling, texting, location and accelerometer data to establish the user’s normal patterns. Deviations from normal patterns can be used to predict early signs of disease. For example, Ginger.io has created algorithms checking changes in communication and movement data, called a “behavior signature,” to predict early signs of depression.

It now seems possible for the combined forces of game play and big data to open new vistas for personalized brain training. In other arenas, combining new digital tools with big data can move users towards a more personalized healthcare experience across the disease spectrum from health and wellness to chronic disease.

Ellen M. Martin is Managing Director, Life Sciences at Haddon Hill Group Inc. She has more than twenty years’ experience in communications for life sciences organizations. Prior corporate communications positions include at XOMA, one of the original antibody biopharmaceuticals developers, DNA Plant Technology, one of the first (and last) publicly traded agbiotech companies, and the Bay Area Bioscience Center (forerunner to BayBio) as well as consulting with Kureczka | Martin Associates. Ellen holds an MBA in marketing and finance from Northwestern University’s Graduate School of Management (now Kellogg). She has a BS in physical anthropology from the University of Illinois (Champaign-Urbana), with graduate work in archeology, population genetics, and osteology

Melinda Speckmann recently graduated from the University of California, Los Angeles with a BS in Biophysics and a minor in French. She currently works at the eHealth software company, Orion Health. While working as a research analyst for DrBonnie360, she crystalized her dream to address and solve complex healthcare issues using data science.

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