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Unlocking the potential of wearable sensors to measure physical activity and predict clinical worsening in pediatric pulmonary hypertension

Award Number: R01HL183262
ORGANIZATION: NATIONAL HEART, LUNG, & BLOOD INSTITUTE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 08/11/2026
PERIOD OF PERFORMANCE END DATE: 05/31/2031

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Unlocking the potential of wearable sensors to measure physical activity and predict clinical worsening in pediatric pulmonary hypertension - Pediatric pulmonary hypertension (PH) carries a nearly 30% 5-year mortality. However, only 2 medications are approved for children while 12 are approved for adults. Treatments remain limited as there are no validated clinical trial endpoints that accommodate the pediatric population to enable medication testing. Since physical activity (PA) limitations are characteristic of PH, adult trials often test improvement in functional measures such as the 6-minute walk distance (6MWD), but this test is impossible in most children due to age or ability. There is an urgent need to identify new endpoints applicable to all children regardless of age or developmental status to design clinical trials, increase treatments, and improve outcomes in pediatric PH. PA estimated by a wearable sensor correlates with 6MWD and other disease markers in adult studies and small, single-center pediatric studies. But prior studies are inadequate due to major obstacles including 1) the absence of standardized data processing methods with use of proprietary sensor software, “black box” data processing algorithms, and narrow reference populations that limit generalizability across devices, wear locations (hip, arm, etc.) and age groups, and 2) lack of tools to process multidimensional raw sensor data beyond local desktop computers to scale to larger clinical networks. Our team’s approach will overcome the inadequacies of prior studies by using an innovative cloud-based, modular platform to 1) apply open-source computational tools and scoring algorithms including GGIR (Raw Accelerometer Data Analysis) and MIMS (Monitor Independent Movement Summary) to raw PA data to assign age and sex specific PA percentile rankings from nationally representative National Health and Nutrition Examination Survey data and 2) develop machine learning models to detect PA patterns associated with clinical status in pediatric PH. We are poised for translation and scaling of this methodology to a well- established clinical network, the Pediatric Pulmonary Hypertension Network Registry. Our multi-disciplinary team with expertise in pediatric PH, PA, wearables, bioinformatics, and machine learning will analyze longitudinal raw sensor data from 200 registry participants from 6 sites to 1) establish PA metrics including MIMS-PA percentile ranking and GGIR-derived metrics (volume, number/duration of PA bouts, intensity gradient) as indicators of disease severity (Aim 1) and 2) train and validate a novel machine learning model incorporating PA metrics to predict clinical worsening in pediatric PH (Aim 2). This proposal is strengthened by my foundational experience processing raw sensor data in pediatric PH patients and healthy children through K23HL150337. Aligned with NHLBI’s Strategic Vision and Research Priorities, these studies will “identify (digital) biomarkers of PH that could better identify individuals at high risk…and guide treatment.” Upon successful completion of these aims, we will standardize methods for estimating PA from a wearable sensor and establish the clinical relevance of PA in pediatric PH. Our approach will facilitate testing of new therapies in PH clinical trials and can be generalized to other cardiopulmonary conditions to augment patient monitoring, expand treatments, and improve outcomes.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2026 ( Subtotal = $1,068,774 )
2026	2026	THE CHILDREN'S HOSPITAL OF PHILADELPHIA	3401 CIVIC CENTER BLVD	PHILADELPHIA	PA	19104	PHILADELPHIA	USA	Lung Diseases Research	000	1	8/13/2026	NEW	$1,068,774
														Subtotal = $1,068,774

Grand Total All Awards = $1,068,774

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Unlocking the potential of wearable sensors to measure physical activity and predict clinical worsening in pediatric pulmonary hypertension

Award Number: R01HL183262

ORGANIZATION: NATIONAL HEART, LUNG, & BLOOD INSTITUTE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 08/11/2026

PERIOD OF PERFORMANCE END DATE: 05/31/2031

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