A project developing an interpretable multimode sensing and AI system for real-time chronic pain assessment in older adults with ADRD.
Read MoreA project to develop an interpretable ML/AI “biological age” metric from multiscale biomarkers to support healthy aging decisions.
Read MoreA Johns Hopkins study using machine learning and mobile cognitive testing to predict post-COVID-19 cognitive decline and Alzheimer’s disease risk in older adults.
Read MoreJohns Hopkins expert in vestibular and balance rehabilitation for older adults.
Read MoreThis project develops video-based pose estimation tools to automate neurologic motor assessments for individuals with stroke and Parkinson’s disease.
Read MoreAn AI-based mitochondria aging clock using long-read sequencing and multiomics to identify frailty biomarkers.
Read MoreA feasibility study of NSite’s AI-enabled “The Scoliosis Solution” for adults aged 60+ to assess acceptance and use.
Read MoreA project using wearable devices to compare real-world and in-person gait assessments in older adults.
Read MoreA study comparing clinic versus at-home gait measures in at-fall-risk older adults using wearable sensors and machine learning.
Read MoreA pilot comparing clinic vs. at-home gait measures in at-fall-risk older adults using a compact real-time foot-tracking wearable (RT-BLE-001).
Read MoreAn approach using EEG-based dynamic network models and AI to help detect and differentiate ADRDs, including distinguishing FTD from AD.
Read MoreWearable tech engineer using sensor analytics to support health monitoring and rehabilitation.
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