# Developing mobile software that uses visual mapping techniques as habit-based assistive technology for individuals with Alzheimer's disease and Alzheimer's related dementias and their caregivers

> **NIH NIH R43** · MAPHABIT, INC. · 2020 · $498,557

## Abstract

Alzheimer’s disease and Alzheimer’s disease related dementias (AD/ADRD) are age-associated
neurodegenerative diseases that are reaching epidemic proportions. Progression of AD is characterized by
losses in memory, orientation, independent decision-making capacity, and self-care. Gains in understanding
AD pathogenesis have not yet translated into pharmacological therapies that effectively slow or halt disease
progression. Evidence-based behavioral approaches are rapidly becoming recognized as methods to provide
effective neurocognitive and therapeutic support for AD/ADRD patients and their caregivers1.
 Behavioral approaches such as lifestyle changes and risk reduction are non-pharmacological therapies
that are accessible, personalizable, have no side effects, and are low in cost. To that end, we are developing
mobile device software that is patient and caregiver centered, and provides behavioral-based assistance
through visual mapping. The MapHabitTM system (MHS) uses pictures and keywords to assist memory-
impaired patients and caregivers in organizing and successfully accomplishing their activities of daily living.
This approach is innovative through its unique recruitment of the brain’s habit learning system (neostriatum)
rather than the hippocampal structures damaged in AD. Preliminary work revealed that commercially available
visual mapping software is too complicated for memory-impaired and technology-naïve individuals to use
effectively. Commercially available software is proprietary and cannot be modified to meet their needs.
 In this Phase 1 SBIR application, we propose to further develop and enhance MHS by integrating three
novel specific aims that involve (1) development of adaptive user interfaces which can be personalized and
dynamically adjusted for cognitive status, allowing for a greater range of memory-impaired individuals to
benefit from visual mapping; (2) linkage of personalized visual maps to smart devices, including wearables
(e.g., Apple iWatch) and audio interfaces (e.g., Amazon Echo); (3) establishment of a predictive analytics tool
that will accurately track and predict changes in functional status.
 We are advantaged in this SBIR Phase 1 application by having access to patients and caregivers,
including underrepresented minority populations, who are currently involved in our preliminary studies
assessing the impact of visual mapping on quality of life measures. All of these individuals are already well-
characterized in terms of their cognitive and emotional behavior, both before and after the use of visual
mapping (see letters of support from Dr. E. Vaughn, Atlanta VA Health Care System, Dr. M. Parker, Emory
University Alzheimer’s Disease Research Center, and F. Boatman, RN, Speak Life Management). Those
studies will contribute to the preliminary data section of our planned SBIR Phase 2 application that will: assess
the effectiveness of MHS on a broad range of large clinical populations, improve the user-experience for...

## Key facts

- **NIH application ID:** 9993188
- **Project number:** 5R43AG065081-02
- **Recipient organization:** MAPHABIT, INC.
- **Principal Investigator:** Matthew Golden
- **Activity code:** R43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $498,557
- **Award type:** 5
- **Project period:** 2019-08-15 → 2021-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9993188

## Citation

> US National Institutes of Health, RePORTER application 9993188, Developing mobile software that uses visual mapping techniques as habit-based assistive technology for individuals with Alzheimer's disease and Alzheimer's related dementias and their caregivers (5R43AG065081-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/9993188. Licensed CC0.

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