Moving beyond fitness tracking to wearable diagnostic solutions

Contact: Cindy Wagner
January 23, 2025
Dr. Simin Masihi, electrical and computer engineering
Dr. Simin Masihi, assistant professor of electrical and computer engineering

KALAMAZOO, Mich.—Competitive athletes represent physical strength, speed, power, endurance and health. Sadly, a small number of young athletes die from sudden cardiac death (SCD), commonly caused by undiagnosed arrhythmias and other electrical disorders. According to the American Academy of Pediatrics, sudden cardiac death accounts for nearly 2,000 deaths annually in the United States among individuals younger than 25 years old.

Now, researchers at Western Michigan University’s Center for Advanced Smart Sensors and Structures are advancing the capabilities of a wearable electrocardiogram (ECG) device that continuously monitors the user’s heart to detect the intermittent arrhythmia that may lead to SCD. 

“Ultimately, our goal is to develop a wearable diagnostic solution for arrhythmia detection that functions beyond fitness tracking and can be seamlessly integrated into daily activities,” says Dr. Simin Masihi, assistant professor of electrical and computer engineering and lead researcher for the project.

Current athletic pre-participation exams and personal ECG devices such as Apple Watch do not continuously monitor the heart rhythm. Traditional exams involve isolated ECG screenings in a medical setting and can miss the atypical, intermittent problems that occur during physical activity and can lead to sudden cardiac death. Smart devices such as Apple Watch cannot constantly look for arterial fibrillation or detect heart attacks and do not store the necessary data for medical evaluation. Additionally, obtaining an accurate reading requires the user to remain still and follow the on-screen instructions during the measurement, which is often impractical during many daily activities.

"Even though the recent features in these high-end costly wearable devices are very helpful and will let us track our heart rhythm in an easier and more frequent manner, these devices are still mainly designed for fitness tracking purposes and are far behind the standard ECG examinations, in terms of providing a reliable and timely medical diagnosis,” says Masihi.

In addition to monitoring the heart of athletes during activity, the wearable ECG device uses machine learning and cloud computing techniques to allow for continuous monitoring by medical personnel.

Since sudden cardiac death occurs most frequently to apparently healthy, young adults, the wearable system can be used as part of participation screening to identify predisposed athletes before they engage in physical activities that could be life threatening. 

“Through this project, we will use flexible hybrid electronics and machine learning techniques to develop a smart, wearable ECG monitoring system in the form of a chest band or compression shirt that can enable early diagnosis of pre-existing cardiac arrhythmias in young athletes before they become fatal,” adds Masihi.

The project combines fabrication technology and computing ingenuity that have driven development of wearable devices for continuous health monitoring and provided the data for the AI-driven processes. These approaches are being increasingly adopted into patient care paving the way to minimally invasive or non-invasive treatment modalities.

The ECG device would serve as the first step towards developing better therapeutic strategies for the timely treatment of cardiac arrhythmia. This will be accomplished by enabling the detection of intermediate arrhythmia which are not usually detectable in regular ECG screens, thus decreasing the possibility of misjudgments in players’ screenings while helping doctors to better understand the underlying symptoms of sudden cardiac death.

The project is led by Masihi in collaboration with Department of Electrical and Computer Engineering faculty members Dr. Massood Atashbar, professor; Dr. Bradley Bazuin, professor: and Dr. Dinesh Maddipatla, assistant professor. 

An integral part of the work, graduate and undergraduate students

  • Doctoral students: Abdulrahman Yusuf, Alimohammad Adineh, Tony Hanson and Masoud Panahi.
  • Undergraduate students: Frazana Mahbub and Alexander Marsh, both studying computer engineering

Mahbub and Marsh have been recognized for their work on the project: Mahbub earned WMU Undergraduate Research and Creative Scholarship Excellence Award and Marsh received a Michigan Space Grant Consortium grant.

The team is also initiating collaborations with external universities and hospitals to incorporate advanced machine learning methods and to establish clinical support for data collection and validation.

WMU’s Center for Advanced Smart Sensors and Structures develops sensor technologies to address real-world challenges, with a focus on designing and engineering devices utilizing flexible hybrid electronics. Recently, CASSS has been harnessing sensor technologies combined with AI to provide intelligent monitoring solutions. Some current projects include the following: 

  • Technology for “mind-controlled” prosthetics, including electroencephalogram systems, leveraging sensor and robotic technologies combined with AI and machine learning techniques to analyze and model brainwave patterns collected to control a prosthetic arm.
  • Wearable shoe insoles capable of improving the healing process of diabetic foot ulcers by delivering a synergistic dose of electrical stimulation and heat to improve healing rates and accurately predict oxygen saturation.
    For more information on CASSS projects or to connect with researchers, visit the center’s website.

For more WMU news, arts and events, visit WMU News online.