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Projects

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Our group designs, develops, and implements a number of digital health projects, ranging from open-source tools and frameworks that support modern, standards-based and interoperable digital health software development, and real-world digital health applications for medical research and clinical care in partnership with clinicians and researchers from Stanford and beyond.

If you are interesting in joining out ongoing research, check out our research opportunities & open positions.

Open-Source Digital Health Frameworks

Spezi

Build modern, interoperable digital health applications with an open-source ecosystem of modules based on international health data standards such as HL7 FHIR.

HealthKitOnFHIR

An open-source Swift library that allows you to convert Apple HealthKit data to HL7 FHIR resources in your iOS applications.

Phoenix Survey Builder

Build standardized HL7 FHIR-based questionnaires for structured health data collection using a drag-and-drop interface.

Applications of AI in Digital Health

Partner Projects

Quantitative DigitoGraphy

A Comprehensive Real-Time Remote Monitoring System for Parkinson’s Disease consisting of a Bluetooth finger tapping device, Spezi-based mobile application, machine-learning algorithm, and Epic-integrated clinician dashboard.

ENGAGE-HF

Developed by Stanford University in collaboration with DOT HF network, funded by the American Heart Association Health Tech SFRN, this app is designed to make managing heart failure easier and more effective.

LifeSpace

To evaluate how environmental conditions influence health, we have developed a novel measure of the space within which individuals live and move. By mapping the space within which individuals live and move, we can study features of the social and built environment that support health, and identify opportunities for intervention to protect disadvantaged communities.

OwnYourData

OwnYourData aims to increase the representation of women and BIPOC in cancer clinical trials through securely accessing a patient’s health records and automatically generating a list of relevant NCI-supported trials.

Post-Intensive Care Syndrome (PICS)

An app for collection of Patient Reported Outcomes Measures (PROMs) from patients who have undergone prolonged intensive care therapy.

Stronger

An application for helping postmenopausal women to maintain muscle mass and overall health with innovative methods for protein tracking and resistance training.

NeuroNest

The NeuroNest project aims to develop a low-cost, mobile system for early neurodevelopmental screening in children, focusing initially on autism spectrum disorders.

PAWS: Pediatric Apple Watch Study

An application for capturing and analyzing ECG voltage data in pediatric patients with suspected arrhythmias for early diagnosis using the Apple Watch.

PRISMA

An LLM-based conversational agent for personalized health behavior change to encourage physical activity.

Nourish Navigator

Interactive application designed to address the unmet clinical need of individuals with Avoidant/Restrictive Food and Intake Disorder (ARFID) and other high-need populations struggling with low weight.

Balance

A companion application to support patients suffering from eating disorders in-between therapy sessions. Balance tracks emotional regulation in adolescents with anorexia nervosa to reduce their emotional and physiological stress during mealtimes.

U-STEP

An app developed for the University of Utah School of Medicine that allows patients with Peripheral Vascular Disease (PVD) to asynchronously complete PROM surveys and gait tasks to expand the reach and retention of patient data collection and improve outcomes.

PatchTrackr

A way to improve access to diagnosis of allergic contact dermatitis (ACD) in patients with known chronic eczema to facilitate allergen identification and management.

BUDI: Biofeedback Upper Limb Device for Impairment

A digital health solution for individuals with limited upper limb mobility, such as children with cerebral palsy. BUDI is a program embedded into an Apple Watch to track therapeutic movements of the user throughout the day and provide the user with biofeedback to maximize therapy and rehabilitation of the upper limb in the absence of a clinician.

GaitMate: At-Home Functional Mobility Assessment (FMA) for Fall Risk

Falls in older adults are common, costly and preventable yet identification of those at highest risk remains elusive. At home functional mobility assessments could identify perturbations not identified in sparse healthcare encounters. GaitMate is a user-friendly app using Stanford’s CardinalKit that automates at-home safe functional mobility assessments. 

VascTracX

Peripheral Vascular Disease (PAD) affects nearly 10M people in the United States and is the manifestation of atherosclerotic disease in the peripheral arteries and manifests itself in the form of “claudication” in the earliest stages of development- this is calf muscle pain/cramping with activity. We treat this condition with exercise therapy, medications and if severe will place stents. The outcome of stenting procedures is quite poor and we do not have a way to monitor patients individually to see who is developing scarring/recurrence faster than others. The aim of this study is to determine if passive activity monitoring can be used to predict early treatment failure.

MyOIT: Oral Immunotherapy for Food Allergies

MyOIT lets participants of oral immunotherapy (OIT) easily track their food allergy dose amounts, symptoms, and much more! Built with patients and clinicians at the Sean N. Parker Center for Allergy and Asthma Research, MyOIT provides relevant insights, helping to improve shared treatment decision making.

Slocum study for benchmarking function recovery after ankle fracture

For the first time we are able to access both pre- and post-fracture gait metrics and functional status.  Aided by a grant from the Orthopedic Trauma Association (OTA), Slocum are evaluating if iPhone gait metrics can be used to benchmark functional recovery after ankle fracture using a mobile application built using CardinalKit.

S-SMART (Stanford Surgical Mobile Assessment Risk Tracker)

An early intervention tool to track opioid use and evaluate patient daily functioning post-operation. S-SMART (Stanford Surgical Mobile Assessing Risk Tracker) is a smartphone-based health app for a research study by the VA Palo Alto and Stanford University. S-SMART acts as a platform to track surgical patients across a highly structured episode of care, their relationship between opioid use and pain, and self-reporting health-related symptoms.

Care-It

CARE-IT is a mobile digital health app-based intervention that activates patients to communicate their values and health goals with family members and healthcare providers.