Development of a Living Library of Digital Health Technologies for Alzheimer’s Disease and Related Dementias: Initial Results from a Landscape Analysis and Community Collaborative Effort

Digital health technologies offer valuable advantages to dementia researchers and clinicians as screening tools, diagnostic aids, and monitoring instruments. To support the use and advancement of these resources, a comprehensive overview of the current technological landscape is essential. A multi-stakeholder working group, convened by the Digital Medicine Society (DiMe), conducted a landscape review to identify digital health technologies for Alzheimer’s disease and related dementia populations. We searched studies indexed in PubMed, Embase, and APA PsycInfo to identify manuscripts published between May 2003 to May 2023 reporting analytical validation, clinical validation, or usability/feasibility results for relevant digital health technologies. Additional technologies were identified through community outreach. We collated 172 peer-reviewed manuscripts, poster presentations, or regulatory documents for 106 different technologies for Alzheimer’s disease and related dementia assessment covering diverse populations such as Lewy Body, vascular dementias, frontotemporal dementias, and all severities of Alzheimer’s disease. Wearable sensors represent 32% of included technologies, non-wearables 61%, and technologies with components of both account for the remaining 7%. Neurocognition is the most prevalent concept of interest, followed by physical activity and sleep. Clinical validation is reported in 69% of evidence, analytical validation in 34%, and usability/feasibility in 20% (not mutually exclusive). These findings provide a landscape overview for clinicians and researchers to appraise the clinical utility and relative maturity of technologies for assessing Alzheimer’s disease and related dementias. ### Competing Interest Statement All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: SAL is an employee of the Digital Medicine Society; ES is an employee of Altoida and holds company stock; SLB is an employee of VivoSense, Inc; KB is an employee of Merck & Co and Co-Chair of Mobile in Clinical Trials Conference; JD is an employee of Cumulus Neuroscience, holds company stock, & is coauthor on a pending patent with other Cumulus Neuroscience employees; CFA receives consulting income from Cogniant Pte Ltd.; JCG is an employee of the Digital Medicine Society; AH is an employee of Eli Lilly & Co. and holds company stock; AJ is an employee of Linus Health, Inc. and is listed as an inventor on pending patents on digital biomarkers of cognition and digital assessments for early diagnosis of dementia; RSF is an employee of Eisai Farmaceutica SA; PF is an employee of the Digital Medicine Society, reports consulting income from Sarepta, IQVIA, Clarivate, Open Health, has a leadership or fiduciary role with International Society of Quality of Life, and is president of consulting company SeeingTheta. ### Funding Statement This work was funded as part of a pre-competetive collaboration hosted by the Digital Medicine Society; project partners include Abbvie, Alzheimer's Drug Discovery Foundation, Biogen, Cognito Therapuetics, Eisai, Lilly, Luca, Merck, Oregon Health & Science University, & Roche; digital solutions collaborators include Altoida, Aural Analytics, BioSensics, Cambridge Cognition, Cogniant, Cogstate, Cumulus Neuroscience, Ki Elements, Koneksa, Linus Health, Medidata, SageBionetworks, VivoSense, & Winterlight. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This manuscript is a literature review of previously published studies; no new studies were generated and no new human participant data was collected. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors. * AD : Alzheimer’s disease ADRD : Alzheimer’s disease and related dementias DATAcc : Digital Health Measurement Collaborative Community DHT : Digital health technology EVIDENCE : EValuatIng connecteD sENsor teChnologiEs NOS : Not otherwise specified V3 : Verification, analytical validation and clinical validation