Pilots

New Product Launch: BIDSleep iPhone and Apple Watch App

BIDSleep helps you access wellness data from your Apple Watch, including heart rate, motion, blood oxygen, and sleep stages, all securely stored on your device. App Purpose: BIDSleep is a wellness app that helps users collect heart rate, blood oxygen (SpO₂), motion, and optional sleep stage data during rest or overnight sessions. It is designed solely for personal data logging and self-monitoring purposes. Source: https://apps.apple.com/us/app/bidsleep/id6747012248?platform=iphone

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Open Source AI-model Released: SLAMSS-IFS

To the study team's knowledge, this is the first open-source four-class sleep staging model developed from a multi-night Apple Watch sleepstudy. SLAMSS-IFS, an advanced version of our previous SLAMSS model, for four-class sleep staging using IHR and accelerometry signals fromthese wearable devices. Key innovations in the model, including an intra-epoch learning LSTM, frequency information incorporation, andskip connections, contribute to substantial performance improvements over other SLAMSS variants and other state-of-the-art models. Ourresults show that SLAMSS-IFS outperforms competing models in overall accuracy, sensitivity, specificity, precision, weighted F1 score, weighted MCC, and most clinical sleep metrics. SLAMSS-IFS: The SLAMSS-IFS model builds on the original SLAMSS model with three additional components: an intraepoch learning sequence-to-sequence long short-term memory (LSTM (“I”), a frequency variable (“F”), and a skip connection (“S”). The intra-epoch learning LSTM processes temporal dependencies within individual epochs.…

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Grant Funding: Novel orthostatic vital signs measured by an earlobe wearable device (1R21AG088945)

Principal investigator, Amar Basu, professor of electrical and computer engineering at Wayne State University and CEO of TRACE Biometrics LLC, has received a National Institute on Aging R21 award to further validate the TRACE sensor against gold standard clinical orthostatic measures, which will build upon the pilot award's work towards securing FDA clearance. Project Summary: Orthostatic disorders, including orthostatic hypotension (OH), disproportionately affect older adults, presenting in 30% of older adults and up to 70% of nursing home residents. As OH is a major risk factor for syncope, falls, and cognitive decline, medical agencies stress the public health need for monitoring orthostatic vital signs (OVS) in at-risk individuals. This proposal investigates an NIA award-winning wearable device called TRACE, which addresses fundamental limitations of the current clinical standard, the blood pressure (BP) cuff: 1) The BP…

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Publication: Developing an Equitable Machine Learning-Based Music Intervention for Older Adults At Risk for Alzheimer Disease: Protocol for Algorithm Development and Validation

Authors: Chelsea S Brown, Luna Dziewietin, Virginia Partridge, Jennifer Rae Myers Abstract Background: Given the high prevalence and cost of Alzheimer disease (AD), it is crucial to develop equitable interventions to address lifestyle factors associated with AD incidence (eg, depression). While lifestyle interventions show promise for reducing cognitive decline, culturally sensitive interventions are needed to ensure acceptability and engagement. Given the increased risk for AD and health care barriers among rural-residing older adults, tailoring interventions to align with rural culture and distinct needs is important to improve accessibility and adherence. Objective: This protocol aims to develop an intelligent recommendation system capable of identifying the optimal therapeutic music components to elicit engagement and resonate with diverse rural-residing older adults at risk for AD. Aim 1 is to develop culturally inclusive user personas for rural-residing older adults to understand…

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Publication: Passive Measures of Physical Activity and Cadence as Early Indicators of Cognitive Impairment: Observational Study

Authors: Huitong Ding, Stefaniya Brown, David R Paquette, Taylor A Orwig, Nicole Spartano, Honghuang Lin Abstract Background: Emerging research shows regular physical activity reduces cognitive decline risk, but most studies rely on self-reported measures, which are limited by recall bias, subjectivity, and a lack of continuous monitoring capability. Objective: This study aimed to explore passive physical activity measures as early indicators of cognitive impairment by examining their association with cognitive impairment incidence and neuropsychological (NP) test performance. Methods: We included participants from the Framingham Heart Study (FHS), a community-based cohort with longitudinal cognitive impairment surveillance. Participants wore an Actical accelerometer for at least 3 days, excluding bathing. Thirty physical activity measures were grouped into intensity-specific durations, step and cadence summaries, and peak cadence. Cox proportional hazard models were applied to assess their associations with incident…

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Oral Presentation: Alzheimer’s Association International Conference 2025 – Technology And Dementia Preconference

Jennifer Flexman presented "Improving Access to Dementia Care though AI-Powered Cognitive Rehabilitation Therapy" at the Technology And Dementia Preconference during Session 5: Data Blitz.

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