The underlying technology and methodology for the pilot funded device, NINscan, was awarded a patent in December 2024. Source: US 12,167,919 B2 (patentsgazette.uspto.gov)
Authors: Ziad A Elhajjaji, Amar S Basu Abstract Orthostatic disorders affect 30% of older adults and increase the risk for falls. The current diagnostic standard, the blood pressure cuff, cannot capture the rapid, multifaceted dynamics of orthostasis physiology, resulting in frequent underdiagnosis. This paper demonstrates multiparameter, real-time measurement of orthostasis using TRACE, an earlobe mounted wearable developed in our group. In prior work, we demonstrated a novel metric called orthostatic hypovolemia (OHV1), the initial loss in cephalic (head) blood volume immediately upon standing. This study significantly advances our prior work by introducing an additional 2 metrics: OHV2, the cephalic blood volume deficit after the body achieves homeostasis after standing; and postural orthostatic tachycardia (POT), the increase in heart rate. The 3 metrics were evaluated in 101 older adults who wore the TRACE device during postural…
This presentation was given on November 20, 2024 by Dr. Susan Murphy as part of the L. Brown Distinguished Lecture series at University of Pennsylvania Abstract: Adaptive sampling methods, such as reinforcement learning (RL) and bandit algorithms, are increasingly used for the real-time personalization of interventions in digital applications like mobile health and education. As a result, there is a need to be able to use the resulting adaptively collected user data to address a variety of inferential questions, including questions about time-varying causal effects. However, current methods for statistical inference on such data (a) make strong assumptions regarding the environment dynamics, e.g., assume the longitudinal data follows a Markovian process, or (b) require data to be collected with one adaptive sampling algorithm per user, which excludes algorithms that learn to select actions using data…
This is an R21 award for $650,000 over a period of 3 years. Their smartphone app prototype capitalizes on the handheld nature of a mobile phone and uses its built-in sensors to gauge grip strength to enhance preoperative screening for potential risks of complications post cardiac surgery. This effort will contribute to the growing portfolio of smartphone-based health monitoring solutions actively being developed by Wang and his research team. Source: https://today.ucsd.edu/story/uc-san-diego-researcher-receives-nih-trailblazer-award
Presented " Quality Management Framework for an Automated, Phone-Based Telehealth Platform for Cognitive Rehabilitation Therapy" at the ASHA Conference in Seattle, WA on November 11, 2024 Source: https://plan.core-apps.com/asha2024/event/6a3d638ef5896a352b49fbfd8b5f1248
Authors: Colin Barry, Yinan Xuan, Ava Fascetti, Alison Moore, Edward J Wang Abstract This paper proposes a smartphone-based method for measuring Blood Pressure (BP) using the oscillometric method. For oscillometry, it is necessary to measure (1) the pressure applied to the artery and (2) the local blood volume change. This is accomplished by performing an oscillometric measurement at the finger's digital artery, whereby a user presses down on the phone's camera with steadily increasing force. The camera is used to capture the blood volume change using photoplethysmography. We devised a novel method for measuring the force applied of the finger without the use of specialized smartphone hardware with a technique called Vibrometric Force Estimation (VFE). The fundamental concept of VFE relies on a phenomenon where a vibrating object is dampened when an external force is…
Dr. Inbal Billie Nahum-Shani (PI) presented work from this pilot project during a talk titled "Adaptive interventions and JITAIs as decision policies: What and why?" as part of Session 1 - Digital adaptive interventions: decision-focused evidence production held on October 16, 2024. Source: NIA Event Page