Non-Invasive Wearable Blood Clot Detection Device for Early Clot Detection

School Name

Spring Valley High School

Grade Level

11th Grade

Presentation Topic

Physiology and Health

Presentation Type

Non-Mentored

Abstract

Blood clots are serious health conditions that when not treated can lead to strokes, heart attacks, and death. Roughly every 6 minutes a person in the U.S. dies from a type of blood clot. Although there are devices such as doppler ultrasounds used to diagnose thrombosis, they usually diagnose the clot when serious symptoms are present. Moreover, almost half of people who develop blood clots such as deep vein thrombosis, will not have any noticeable symptoms, which leaves them without treatment and increases the chance of experiencing life threatening conditions. Wearable devices offer potential continuous monitoring tasks that would be able to detect clots before symptoms arise. The purpose of this study was to create a wearable blood clot device that can detect subtle changes in blood flow using a photoplethysmography (PPG) sensor and an accelerometer and gyroscope to identify early stage thrombosis.It was hypothesized that a wearable blood clot detection device utilizing a PPG sensor in addition to an accelerometer will be able to detect early thrombosis because of its sensitivity in identifying precise changes in blood flow as opposed to traditional models. The device consisted of an Arduino Uno Rev 3, a MAX30102 PPG sensor and a MPU-6050 accelerometer and gyroscope sensor to detect early clot formation utilizing a peristaltic pump powered silicon blood flow tubing model. To model thrombosis three clot groups were created that include cornstarch (early clot), cornstarch and agar (in between early and partial) and agar alone (partial).

Location

Furman Hall 127

Start Date

3-28-2026 10:15 AM

Presentation Format

Oral and Written

Group Project

No

COinS
 
Mar 28th, 10:15 AM

Non-Invasive Wearable Blood Clot Detection Device for Early Clot Detection

Furman Hall 127

Blood clots are serious health conditions that when not treated can lead to strokes, heart attacks, and death. Roughly every 6 minutes a person in the U.S. dies from a type of blood clot. Although there are devices such as doppler ultrasounds used to diagnose thrombosis, they usually diagnose the clot when serious symptoms are present. Moreover, almost half of people who develop blood clots such as deep vein thrombosis, will not have any noticeable symptoms, which leaves them without treatment and increases the chance of experiencing life threatening conditions. Wearable devices offer potential continuous monitoring tasks that would be able to detect clots before symptoms arise. The purpose of this study was to create a wearable blood clot device that can detect subtle changes in blood flow using a photoplethysmography (PPG) sensor and an accelerometer and gyroscope to identify early stage thrombosis.It was hypothesized that a wearable blood clot detection device utilizing a PPG sensor in addition to an accelerometer will be able to detect early thrombosis because of its sensitivity in identifying precise changes in blood flow as opposed to traditional models. The device consisted of an Arduino Uno Rev 3, a MAX30102 PPG sensor and a MPU-6050 accelerometer and gyroscope sensor to detect early clot formation utilizing a peristaltic pump powered silicon blood flow tubing model. To model thrombosis three clot groups were created that include cornstarch (early clot), cornstarch and agar (in between early and partial) and agar alone (partial).