Posted on
January 9, 2024

a2 Collective Funds Second Cohort of Pilots to Ignite AI and AgeTech Innovation Across the United States

The 32 pilot projects received awards totaling more than $7 million in the second tranche of a total $40 million earmarked to fund AgeTech pilots over 5 years.


Updated Feb. 9, 2024: In addition to the 32 Cohort 2 pilots announced on Jan. 9, a further four pilots have been funded by JH AITC as part of this award cycle, bringing the total number of Cohort 2 awardees to 36 pilots receiving more than $8.1 million. Visit the Awardees page to learn more about awards made to investigators affiliated with Stanford University, the University of North Texas Health Science Center, and Johns Hopkins University School of Medicine in partnership with EyeFree Assisting Communication Ltd. and Picasso Intelligence LLC.

Las Vegas, NV, Jan. 9, 2024—Today, the a2 Collective announced from a CES AARP AgeTech Collaborative panel the funding of 32 pilot projects in the second year of the a2 Pilot Awards, a national competition aimed at accelerating the use of AI and emerging technologies to enhance care, health outcomes, and quality of life for older Americans, including those with Alzheimer’s disease and related dementias (AD/ADRD), and their caregivers.

Funded by the National Institute on Aging, a part of the National Institutes of Health, through the Artificial Intelligence and Technology Collaboratories (AITC) for Aging Research program—or a2 Collective—the a2 Pilot Awards will distribute $40 million over 5 years to fund promising pilot projects developing novel technologies and algorithms with the potential to improve the lives of older adults.

Among the exciting technologies at the center of projects in the second a2 Pilot Awards cohort are home and wearable sensors to monitor and improve cognitive and physical function, care, and sleep; mobile applications and portable devices to assess cognition, motor performance, and disease progression; and novel algorithms to enhance cognitive screening, diagnostics, and clinician and caregiver decision-making. An overwhelming 91% of projects leverage machine learning, including in combination with natural language processing, computer vision, and ambient intelligence. Continued prominence of machine learning is expected as both pilot awardees and applicants adapt to and integrate advances in generative AI.

Most Cohort 2 projects’ pilot technologies (87.5%) are intended for use in the home, with the goal of augmenting older adults’ ability to age in place with greater quality of life, access to care, and independence. Many can be used in residential living and ambulatory care settings in addition to the home, while others aim to provide critical screening and decision support in clinical settings.

“We are thrilled by the growth that Cohort 2 projects bring to the a2 Collective funding portfolio,” said Rose Li, PhD, MBA, principal investigator (PI) of the a2 Collective Coordinating Center. “In addition to innovative approaches to longstanding challenges such as early detection of cognitive decline and fall prevention, projects address a range of key comorbidities, including emergent topics such as long-term impacts of COVID-19 on cognition.”

Each Cohort 2 project was recommended for funding by one of the a2 Collective’s three AITCs, which are centered at Johns Hopkins University (JH AITC), the University of Massachusetts Amherst (MassAITC), and the University of Pennsylvania (PennAITech). Projects receive awards of up to $200,000 in direct costs over a 1-year period, as well as access to resources and multidisciplinary mentorship from the funding AITC. Projects funded in Cohort 2 build on priority areas of technology development and aging- and AD/ADRD-related needs identified by the AITCs and addressed by projects funded in the first a2 Pilot Awards cohort.

Key trends that emerged in a2 Pilot Awards Cohort 1 and continue among Cohort 2 awardees include a roughly even split between awardee organizations within academia (56%) and outside of it (44%), with many projects representing collaborations between startups and academic or healthcare institutions. The proportion of PIs who identify as women among Cohort 2 awardees (44%) remains comparable to that of Cohort 1 and significantly higher than the estimated 30% rate of female representation in AI globally.

“As the a2 Collective ecosystem grows, we are excited to foster increasing collaboration among entrepreneurs, academic researchers, and clinicians,” said Stephen Liu, MBA, managing director of marketing and business development at the a2 Collective Coordinating Center. “Bringing together innovators across sectors allows them to apply their collective expertise to more rapidly bring paradigm-shifting technologies to market, where they can accelerate progress in the field and have the greatest real-world impact on older adults’ lives.”

Determination of awardees for the third year of competition is currently underway, and the fourth annual a2 Pilot Awards will accept Round 1 applications from March 1 to April 30, 2024. Visit to learn more about the upcoming competition.

a2 Pilot Awards Cohort 2 Project Descriptions

To learn more about these awardees as well as those funded in a2 Pilot Awards Cohort 1, visit our Awardees page.

Machine learning-based, passive monitoring of agitation in individuals with AD/ADRD using wearable devices in the home setting

Awardee organizations: Adiona Inc. | University of Chicago

PIs: James Mastrianni, MD, PhD | Joshua Kim

Wearable light exposure spectrometer device using machine learning to determine optimum light exposure inputs to improve sleep quality for older adults and individuals with AD/ADRD

Awardee organization: Blue Iris Labs

PI: Erik Page

AI-based voice analysis, computer vision, and representation learning for AD/ADRD assessment in clinical settings

Awardee organization: Boston University

PIs: Vijaya Kolachalama, PhD | Rhoda Au, PhD, MBA

Digital twin using wearables, digital biomarkers, and social determinants of health with machine learning for individualized cognitive assessments in home and clinical settings

Awardee organizations: EchoWear | Rhode Island Hospital

PI: Kunal Mankodiya, PhD

AI-enhanced virtual caregiver system to decrease risk of falls in older adults and individuals with AD/ADRD

Awardee organization: Electronic Caregiver

PIs: David Keeley, PhD | Michael Busa, PhD

Radio frequency-based off-body real-time remote monitoring of medication adherence for older adults

Awardee organization: etectRx

PI: Tony C. Carnes, PhD

Druid® impairment mobile app using machine learning to assess cognitive and motor performance decline, enabling older adults to drive safely

Awardee organization: Impairment Science Inc.

PIs: Michael Milburn, PhD | William DeJong, PhD | Anuj K. Pradhan, PhD

Intelligent cognitive assistant leveraging NLP to provide word retrieval support in daily living for older adults and individuals with AD/ADRD

Awardee organization: Institute for Human and Machine Cognition

PI: Archna Bhatia, PhD

In-home cognitive assessment mobile app using machine learning to predict post-COVID-19 cognitive decline and AD/ADRD risk for older adults

Awardee organization: Johns Hopkins University School of Medicine

PI: Tracy Vannorsdall, PhD

Non-invasive AI-powered blood glucose monitoring device for older adults with diabetes

Awardee organization: Kennesaw State University

PIs: Maria Valero, PhD | Katherine Ingram, PhD

Sentiment analysis and generative AI language algorithms to support dementia caregiver interventions in home care environments

Awardee organization: Kinto

PI: Joseph Chung, MS

Home safety monitoring platform using voice, IoT activity monitoring, and machine learning to alert caregivers of falls and other distress-related events in the home

Awardee organization: Livindi

PI: Richard Watkins

AI-supported in-home brain assessments using NINscan wearables for older adults and persons with Alzheimer's disease

Awardee organization: Massachusetts General Hospital

PI: Quan Zhang, PhD

Preparing a technology-ready cohort of individuals with AD/ADRD and their caregivers to pilot test novel digital devices

Awardee organization: Massachusetts General Hospital

PI: Mark Eldaief, MD

AI-based EEG music neurofeedback system to improve working memory and mitigate cognitive decline in older adults with AD/ADRD at home

Awardee organization: Preveal Technologies

PI: Robert N. Hager, PhD

VR fitness platform to remotely assess cognitive and physical function in older adults and individuals with AD/ADRD

Awardee organization: Rendever

PIs: Jennifer Stamps, PhD | Kyle Rand

Passive voice monitoring mobile app using NLP and machine learning to detect early signs of chronic obstructive pulmonary disease exacerbation in older adults

Awardee organization: Stanford University

PI: Jennifer Williams, MD

AI-based continuous and passive health monitoring system using mmWave radar to enable caregivers to monitor AD/ADRD progression and tailor care interventions

Awardee organization: Tellus You Care

PIs: Ryan Gooch, PhD | Rebecca Spencer, PhD

Validating an AI-enhanced remote patient monitoring platform for orthostatic vital signs, with the goal of preventing falls in older adults

Awardee organization: TRACE Biometrics LLC

PIs: Amar Basu, PhD | Michael Busa, PhD

Using novel pressure-sensing insoles to better predict and treat falls in home and clinical settings

Awardee organizations: Tufts University | Arizona State University | Walk With Path

PIs: Linda Denney, PT, PhD | Daniel Peterson, PhD

Validating in-home sleep monitoring devices for older adults with chronic conditions and AD/ADRD

Awardee organization: University of Massachusetts Amherst

PI: Rebecca Spencer, PhD

Development of machine learning models from walking cadence monitoring to assess aging and cognitive health

Awardee organizations: UMass Chan Medical School | Boston University

PI: Honghuang Lin, PhD

Non-intrusive in-home activities of daily living monitoring using a self-supervised multi-sensor fusion model that detects behavior changes associated with AD/ADRD

Awardee organization: University of California San Diego

PIs: Xinyu Zhang, PhD | Alison Moore, MD, MPH

AI-based multimodal sleep staging via wearables to monitor early cognitive decline in older adults at home

Awardee organization: University of Massachusetts Amherst

PI: Joyita Dutta, PhD

Passive wearable sensors using deep learning to create a geriatric functional assessment tool for clinicians

Awardee organizations: University of North Carolina at Chapel Hill | University of Massachusetts Boston

PIs: John A. Batsis, MD | Xiaohui Liang, PhD

AI-based diagnostic clinical decision support system using collective intelligence and imitation learning to improve primary care diagnostics for older adults

Awardee organization: University of Pennsylvania

PI: Gary Weissman, MD, MSHP

Intelligent decision-making tool to connect individuals with AD/ADRD and their caregivers to health app technologies

Awardee organization: University of Pittsburgh

PI: Julie Faieta, PhD, MOT OTR/L

AI-driven AD/ADRD risk prediction models using explainable machine learning and bias identification and mitigation techniques to aid point-of-care clinical decision support

Awardee organizations: University of Virginia | University of Pennsylvania

PIs: Aidong Zhang, PhD | Carol Manning, PhD | Li Shen, PhD | Mary Regina Boland, PhD, MPhil

Web-app tool to support technology use decision making for individuals with AD/ADRD and their caregivers

Awardee organization: University of Washington

PI: Clara Berridge, PhD, MSW

Smart patch and intervention system using RFID technology to prevent medical patch overdose among individuals with AD/ADRD

Awardee organization: Vaaji LLC

PIs: Sandeep Patil, MD, PhD | William Z. Potter, MD, PhD

AI-based device-free Wi-Fi sensing technology to assess daily activities and mobility in low-income older adults with and without cognitive impairment

Awardee organization: Viginia Commonwealth University

PIs: Jane Chung, PhD, RN | Eyuphan Bulut, PhD | Ingrid Pretzer-Aboff, PhD, RN

Speech processing-based novel algorithm for proactive, automated screening of African American home healthcare patients at risk for mild cognitive impairment and early dementia

Awardee organizations: VNS Health | Columbia University Irving Medical Center

PI: Maryam Zolnoori, PhD