About Our Studies

We have several ongoing studies approved by the University of Maryland IRB:

PPG-to-ECG and Physiological Digital Twin

• • Exploration of the ECG-PPG relationship in resting vs. exercising conditions

Video Physio

• • Heart rate and heart rate variability estimation from face videos

  • SPO2 blood oxygen from hand videos

PPG-to-ECG and Physiological Digital Twin

What?

Profs. Min Wu and Sushant Ranadive are conducting a study to investigate the use of automated systems for continuous monitoring of cardiac activity. The goal of the study is to gain insight into the relationships between various non-invasive cardiac monitoring techniques, which can be leveraged for cardiovascular disease monitoring.. You will be hooked up to an ECG and a few PPG sensors for monitoring in two sessions. In the first session you will simply lie on a bed for 10 minutes. In the second session you will peddle on a stationary bike for 20 minutes.

Who?

You must be at least 18 and able to understand English. Your participation in this study will be a one-time event.

How?

The data collection consists of a 60-minute in-person session that will be carried out in the School of Public Health on the University of Maryland, College Park campus.

All devices that make contact with a participant’s skin will be sanitized before your session begins. Moreover, sanitization and social distancing precautions will be taken in compliance with the COVID-19 related guidelines.

Compensation?

You will receive $10 in cash for your participation in this study.

Any risks from participating in this study?

All measurements are non-invasive. There is minimal risk of temporary skin irritation from prolonged contact with the ECG electrode equipment. However, clinical best practices to limit prolonged use of ECG electrodes will be taken to minimize skin irritation. Risks from this study will be low.

Video-Physio

What?

Prof. Min Wu’s group is conducting a study to evaluate the accuracy and reliability of using videos to measure physiological conditions such as the heart rate, breathing rate, and blood oxygen level. In a nutshell, as the heart pumps blood to various parts of our body, the blood flow under the skin of the face, hand, and arm may be captured by a video camera. Although the changes are very subtle and not noticeable by naked eyes, advanced techniques in signal processing, computer vision, and machine learning can make it possible to track them and estimate heart rate and blood oxygen saturation with encouraging accuracy. Similarly, as we breathe, subtle changes in video recordings of our face and body may reveal our breathing rate and patterns. This research opens a promising new way to track physiological conditions when it is difficult or undesirable to have contacts, including in social distancing scenarios due to the recent COVID-19 pandemics.

We currently have several on-going studies that focus primarily on: (1) estimating breathing and cardiac activity from face videos and (2) estimating SpO2 Blood Oxygen levels from face videos.

Who?

You must be at least 18 and can understand English. Your participation in this study will be a one-time event.

How?

You will participate in one of the two modes of data collection to help researchers examine this emerging contact-free modality for health and fitness:

• Mode-A 3 to 4 sessions in which the participant augments their breathing according to the rhythm of a bouncing ball . During this time, face and hand videos will be taken.

or

• Mode-E 2 to 3 sessions in which the participant alternates between holding their breath and breathing normally. During this time, hand videos will be taken.

Compensation?

You will receive a $10 in cash for each mode of data collection in which you participate.

Any risks from participating in this study?

All measurements are non-invasive. You should not experience discomfort from the study. The risks of this study are low.

You can sign up for and/or request more information about each of these studies by scanning the QR codes below or sending an email to Zach Lazri at the following email address: zlazri@terpmail.umd.edu.

Sign-up