By age sixty-five, 1 in 4 Americans will experience functional decline, a "silent killer" defined by life altering loss of independence and limitations performing activities of daily living (ADLs). Poor health outcomes and skyrocketing costs linked to functional decline cut across many diagnoses, leading to national expenditures projected to exceed $1 trillion annually. Routine functional screening assessments are the gold-standard for addressing this condition. However, due to numerous barriers, most older adults are cared for in settings where screening is poor, inaccurate, or not conducted at all. As a result, functional decline often goes unnoticed until obvious disability and adverse outcomes occur. Leaders in geriatrics have long recognized obstacles addressing functional decline and have called for improved screening and treatment approaches. Meanwhile, ownership, adoption, and usage of digital devices has climbed sharply among older adults, particularly during the pandemic. Smyl Fitness Rx, LLC (Smyl) has identified a novel method to use these devices to address functional decline. This Phase I SBIR proposes development of a mobile application powered by technology that will offer a scalable solution to automate functional screening assessments, compute novel digital biomarkers of functional decline, and deliver evidence-based fitness prescriptions with behavior modification features to facilitate ongoing treatment and prevention. Smyl developed a framework for the application in consultation with key opinion leaders from the American Medical Association's (AMA's)Exercise Is Medicine (EIM) advisory board been and tested it with older adults. Commercialization will focus on addressing key pain points and unmet needs identified during Smyl's market research. Aim 1 will focus on developing machine learning models that use computer vision technology to automate routine functional assessments. Computer vision technology has shown to be effective for use among older adults, including those with dementia. Aim 2 will consist of developing analytic models that use parameters from the automated assessment to compute novel digital biomarkers of functional decline. These digital biomarkers will indicate the presence or future risk of functional decline, ongoing severity, and response to treatment. In Aim 3 Smyl will develop a movement quality & fitness prescription model to facilitate safe and effective exercise prescriptions shown to address functional decline. Phase II efforts will focus on optimizing the technology for home use, developing data-driven fitness prescriptions, and enhancing the platform for use among people living with Alzheimer's disease and Alzheimer's disease-related Dementias (AD/ADRD). The scientific and technology developments of this project have the potential to impact over 34 million middle and older age adults. Implementation of the proposed innovation could reduce the loss of independence, poor health outcomes, and skyrocketing health costs associated with functional decline.
Public Health Relevance Statement: PROJECT NARRATIVE This project proposes technology that automates assessments to detect functional decline in older adults and computes novel digital biomarkers to guide ongoing detection, monitoring, and treatment. Commercialization of the proposed innovation has the potential to reduce poor health outcomes, skyrocketing costs, and life altering loss of independence associated with functional decline.
Project Terms: Activities of Daily Living, Activities of everyday life, daily living functionality, functional ability, functional capacity, Adoption, Adult, 21+ years old, Adult Human, adulthood, Age, ages, Elderly, advanced age, elders, geriatric, late life, later life, older adult, older person, senior citizen, Alzheimer's Disease, AD dementia, Alzheimer, Alzheimer Type Dementia, Alzheimer disease, Alzheimer sclerosis, Alzheimer syndrome, Alzheimer's, Alzheimer's disease dementia, Alzheimers Dementia, Alzheimers disease, Primary Senile Degenerative Dementia, dementia of the Alzheimer type, primary degenerative dementia, senile dementia of the Alzheimer type, American Medical Association, Behavior Therapy, Behavior Conditioning Therapy, Behavior Modification, Behavior Treatment, Behavioral Conditioning Therapy, Behavioral Modification, Behavioral Therapy, Behavioral Treatment, Conditioning Therapy, behavior intervention, behavioral intervention, Chicago, Communities, Computer Vision Systems, computer vision, Consultations, Diagnosis, Exercise, Expenditure, Fatigue, Lack of Energy, Future, Geriatrics, geriatric medicine, Gold, Health, Illinois, Joints, Laboratories, Market Research, Medicine, Methods, Movement, body movement, Persons, Ownership, Painful, Pain, Cyclicity, Rhythmicity, Periodicity, QOL, Quality of life, Risk, Self-Administered, Self Administration, Socialization, Technology, Testing, Time, Universities, Measures, Health Care Costs, Health Costs, Healthcare Costs, Step Tests, Caring, base, improved, Site, Area, Clinical, Phase, Medical, Link, Training, disability, Cognitive Disturbance, Cognitive Impairment, Cognitive decline, Cognitive function abnormal, Disturbance in cognition, cognitive dysfunction, cognitive loss, Impaired cognition, Life, Severities, Clinic, Location, Amentia, Dementia, American, early detection, Early Diagnosis, experience, tech development, technology development, novel, economic impact, novel technologies, new technology, Prevention, Devices, Modeling, develop software, developing computer software, software development, preventing, prevent, Address, fitness, Data, Detection, Preventative intervention, intervention for prevention, prevention intervention, preventional intervention strategy, preventive intervention, Small Business Innovation Research Grant, SBIR, Small Business Innovation Research, Monitor, Development, developmental, pandemic disease, pandemic, functional decline, decline in function, decline in functional status, functional status decline, cost, health economics, digital, Outcome, cost effective, aged, innovation, innovate, innovative, handheld mobile device, mobile device, digital computing, prototype, commercialization, aging population, aged population, population aging, evidence base, treatment response, response to therapy, response to treatment, therapeutic response, therapy response, Biological Markers, bio-markers, biologic marker, biomarker, adverse outcome, adverse consequence, screening, mobile application, mobile app, mobile device application, exercise prescription, exercise training, TensorFlow, Alzheimer's disease related dementia, AD related dementia, ADRD, Alzheimer related dementia, Home, machine learning model, machine learning based model
