Wearable tech being used to assess healthcare worker stress



Wearable technology for health care workers.

Kinesiology and Community Health Professor Manuel Hernandez is among the researchers across campus who recently received funding through the Jump ARCHES (Applied Research for Community Health through Engineering and Simulation) research and development program. The Jump ARCHES program is a partnership between the University of Illinois and its College of Medicine in Peoria and OSF HealthCare.

Hernandez’s project involves monitoring the stress of healthcare workers, specifically physician trainees, through wearable technology.

The pilot grant of $75,000 for one year, Hernandez said, allows for his team to gather remotely collected multimodal wearable data, and to develop software aimed at integrating sensor data and creating a novel framework for detecting state anxiety.

The study subjects will wear Hexoskin smart shirts, wristbands (Embrace 2 sensors), and use a smartphone app (EARS) that will allow for physiological recordings and passive mobile sensing. The physician trainees will wear sensors for 8-12 hours a day for two weeks at a time, Hernandez said, in two separate, two-week sessions.

Hernandez said he hopes the study will provide a foundation for the development of a novel machine learning/artificial intelligence framework for detecting anxiety in adults.

It could, he added, “Allow us to quantify changes in mental health and wellness in physician trainees due to the ongoing pandemic.”

Third-year physician trainees were specifically targeted as subjects, Hernandez said, because of their exposure to clinical rotations, which is particularly timely because of potential COVID-19 exposure.

Hernandez said he and his colleagues chose trainees, rather than older, established physicians, because of the “long-term implications of mental wellness and health in young adults.” The project serves “as a starting point for future examination of mental health and wellness in adults in stressful environments. For physician trainees, even during normal times, the need to both provide care and learn clinical best practices already presents significant challenges for emotional well-being, let alone when faced with a pandemic.”

The study is vital now, Hernandez said, particularly because of the ongoing pandemic. Healthcare professionals often lack the time for traditional services to assessing their mental health, such as therapy.

“Given the potential long-term ramifications on mental health, such as anxiety, depression, or burnout, and well-being of our frontline healthcare providers, particularly trainees, there is an urgent need for objective measures and monitoring of mental health and well-being.”

Editor’s note:

To reach Vince Lara-Cinisomo, email vinlara@illinois.edu.
 

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Can a wearable device combined with PT improve results?



A new publication from Kinesiology and Community Health assistant professor Manuel Hernandez looks at how use of a wearable device combined with physical therapy can improve patient results.

The paper, entitled, “Design of a Low-Cost, Wearable Device for Kinematic Analysis in Physical Therapy Settings,” was published in the June 2020 edition of Methods of Information in Medicine.

Hernandez said he hoped to learn if test subjects—who were from the Champaign-Urbana area—had a positive or negative experience with a novel wearable device, and to identify key areas for improvement in future versions of the device, so as to improve how well future wearable devices get adopted.

The wearable device, Hernandez said, was a standalone suite of sensors that track movement (using IMUs, or inertial measurement units), together with a power supply and mini computer (i.e., a Raspberry Pi), aimed at aiding physical therapy patients in improving exercise technique, through the classification of different upper extremity exercises, monitoring of progress, and biofeedback.

Participants were asked to complete nine upper-extremity exercises while wearing the device: Standing row; external rotation with arm abducted 90 degrees; external rotation; bicep curl; forearm pronation/supination; wrist curls; lateral arm raise; front arm raise, and horizontal abduction.

The aim, Hernandez said, is to validate the ability of the wearable device to accurately identify different upper extremity exercises using machine learning techniques and improve the ergonomics and usability of the device through further miniaturization, increased wireless connectivity, and development of a companion smartphone app.

“It is important to note that everyone is unique and will benefit from personalized care following an injury,” Hernandez said. “We hope that through the integration of smart devices together with evidence-based physical therapy practices, we can achieve improved rehabilitation outcomes, such as a higher restoration of function and speed up recovery, by providing an affirmation of exercise quality, feedback on progress, and minimization of re-injury.”

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