Alzheimer's Disease (AD) and AD-Related Dementias (ADRD) are projected to affect 50 million Americans by 2050. In 2019, more than 16 million Americans struggled while providing unpaid care for people with AD/ADRD and they need stigma-free solutions to help remotely monitor challenging AD/ADRD behaviors like falling andwandering. Separate but related, many AD/ADRD clinical trials are siloed and require patient volunteers andtheir caregivers to travel to in-person appointments. This is burdensome for families, increases the cost to conduct studies, and data collected is often non-representative of daily life. Amissa Inc. has developed a stigma-free, prototype solution to significantly advance AD/ADRD patient monitoring, safety, and caregiving whilesimultaneously aggregating high-frequency digital biomarkers to advance medical research. Several competitors have developed hardware devices for tracking elderly individuals who wander and/or fall however, AD/ADRD patients express feelings of stress, anxiety, humiliation, burden, and stigma associated with dementia whenwearing these "special" devices. AD/ADRD caregivers seek "socially-acceptable" devices that improve healthand location monitoring, provide peace of mind, reduce worry, improve patient safety and quality of life withoutloved ones feeling shame or embarrassment. Amissa's prototype software application, created for widely available, consumer-grade smartwatches, enables families to remotely monitor when loved ones fall inside oroutside the home and help prevent dangerous wandering episodes. Our initial software application also sendsemergency push notifications to key stakeholders when loved ones exhibit uncommon behaviors (e.g. sudden change in variable heart rate). This Phase I SBIR proposal is designed to develop a platform which passivelyand unobtrusively collects time-based behavioral and biometric data from AD/ADRD patient smartwatches inreal-life settings to improve caregiving while also establishing a high-frequency cloud database where one does not currently exist for AD/ADRD research. Aim 1 will develop a caregiver-designed AD/ADRD patient monitoring application for off-the-shelf consumer smartwatches and conduct user-experience and user-interface testing tofacilitate feedback for iterative product design improvement. Utilizing opt-in user data from Amissa's caregivermonitoring application, Aim 2 will establish a novel high-frequency behavioral and biometric cloud database toadvance AD/ADRD digital biomarker research capabilities to predict patient falls an wandering. Amissa's projectintends to enable faster collection of multimodal data via broader demographic populations to advance AD/ADRDmedical research. This Phase I SBIR has the potential for high impact by providing a single, low-cost, digitaltechnology solution to improve AD/ADRD patient care and safety while reducing stress for caregivers andfamilies. Furthermore, this research will improve capabilities and reduce costs of conducting decentralizedclinical trials in real-life environments. At scale, our goal is to advance the forecasting of symptom trajectoriesand enable physicians to suggest personalized preventative treatments to delay onset or prevent AD/ADRD. Project Narrative Utilizing consumer-grade smartwatches and a cloud-based analytics platform to support real-time, real- world, passive and unobtrusive collection of biometric and behavioral data, this project aims to develop and test a free downloadable mobile application to significantly improve remote patient monitoring of people with Alzheimer's disease (AD) and AD-Related Dementias (ADRD). This Phase I SBIR aims to reduce caregiver/partner stress and worry by providing a low-cost resource to monitor loved ones with challenging behaviors and, as an easily downloaded mobile application, this project aims to broadly expand capabilities to conduct remote/decentralized clinical trials and support the evaluation of community-based objective outcomes. The proposed research is clinically relevant as it could deliver large sets of high-frequency data to identify and validate digital biomarkers and improve knowledge about the behaviors of people with AD/ADRD in free-living environments. 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