# Adding technology that will enhance commercialization of our neuroscience-based innovative assistive technology platform for living with Alzheimer's disease and Alzheimer's disease related dementia

> **NIH NIH SB1** · MAPHABIT, INC. · 2024 · $1,246,208

## Abstract

Individuals living with Alzheimer’s disease and Alzheimer’s related dementias (AD/ADRD) have the same quality of life
needs as individuals without dementia, however, in the setting of progressively diminishing memory and worsening
abilities for self-care, individuals living with AD/ADRD experience progressive losses in independent decision-making
capacity and quality of life. The MapHabitTM system (MHS), (NIH/NIA 1st place Eureka Award; 2 SBIR awards; 2 non-
provisional patents approved), is a neuroscience-based assistive technology app that leverages the science of visual
mapping, together with the neuroscience of habit formation, to help memory-impaired individuals accomplish activities
of daily living, maintain their independence, and improve overall quality of life for users, including caregivers. In this CRP
application, MapHabit will further enhance its commercialization and marketing potential by implementing three
Specific Aims (SAs): In SA1, our goal is to strengthen our platform infrastructure and security to enable new predictive
analytics components. In the Phase I/II aims (AG065081) we built out capabilities of gamification, predictive analytics,
artificial intelligence, and Alexa Voice. We now seek new technical assistance to enhance our technology stack with
SOC2 certification, optimize the backend infrastructure, and to apply artificial intelligence (AI) methods to mine usage
patterns. As examples, we will build, train, and deploy generative AI models to intervene ahead of a participant churn, (a
decrease in user activity after an initial period of heavy use (as in SA2) and behavioral changes that could signal onset of
cognitive change. Effective management of these by AI or machine learning models (MLs) will be a key
commercialization metric to engage upstream business partners (payors) and position the platform to address ADRD
population health. In SA2, our goal is to enhance user appeal. Gamification enhancement of the platform began in our
Phase II. Games will be accessed by approaches proven to enhance engagement, e.g., cumulating points for using visual
maps to complete ADLs and that reflect independent functioning (e.g., attending meals with others). New AI/ML models
will gamify the experience and upgrade our serious games with reward systems. We will tailor ML models from SA1 with
an emphasis on applicability to sociodemographically diverse communities, including data from social determinants of
health in SA3. These will be packaged into programs that can be upsold to B2B clients. We will consult with experts at
the Mayo Clinic to advise on strategic initiatives for virtual care consultations and for hard-to-treat domains, like Lewy
Body Dementia. In SA3, the goal will be to enhance customer care processes utilizing social determinants of health
(SDOH) Z codes. We will use technical assistance to apply standards endorsed by the CDC National Center for Health
Statistics to update our intake process to include variables of S...

## Key facts

- **NIH application ID:** 10931315
- **Project number:** 1SB1AG087924-01
- **Recipient organization:** MAPHABIT, INC.
- **Principal Investigator:** Matthew Golden
- **Activity code:** SB1 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $1,246,208
- **Award type:** 1
- **Project period:** 2024-05-15 → 2027-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10931315

## Citation

> US National Institutes of Health, RePORTER application 10931315, Adding technology that will enhance commercialization of our neuroscience-based innovative assistive technology platform for living with Alzheimer's disease and Alzheimer's disease related dementia (1SB1AG087924-01). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10931315. Licensed CC0.

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