The Pi-CON Methodology Applied: Operator Errors and Preference Tracking of a Novel Ubiquitous Vital Signs Sensor and Its User Interface

Abstract

Remote Patient Monitoring has enjoyed strong growth to new heights driven by several factors, such as the COVID-19 pandemic or advances in technology, allowing consumers and patients to continuously record health data by themselves. This does not come without its challenges, however. A literature review was completed and highlights usability gaps when using wearables or home use medical devices in a virtual environment. Based on these findings, the Pi-CON methodology was applied to close these gaps by utilizing a novel sensor that allows the acquisition of vital signs at a distance, without any sensors touching the patient. Pi-CON stands for passive, continuous and non-contact, and describes the ability to acquire vital signs continuously and passively, with limited user interaction. The preference of vital sign acquisition with a newly developed sensor was tested and compared to vital sign tests taken with patient generated health-data devices (ear thermometer, pulse oximeter) measuring heart rate, respiratory rate and body temperature. In addition, the amount of operator errors and the user interfaces were tested and compared. Results show that participants preferred vital signs acquisition with the novel sensor and the developed user interface of the sensor. Results also revealed that participants had a mean error of .85 per vital sign measurement with the patient-generated health data devices and .33 with the developed sensor, confirming the beneficial impact available when using the developed sensor based on the Pi-CON methodology.

Keywords:

• Telehealth
• remote patient monitoring
• user-centered design
• virtual care
• vital signs
• wearables
• ubiquitous sensors

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Steffen Baumann

Steffen Baumann obtained his PhD degree from the Iowa State University in Human Computer Interaction in 2022. He is studying how to effectively apply user-centered design to the development of medical devices and wearables to increase usability and accuracy of the generated data.

Richard T. Stone

Richard T. Stone. The core of Dr. Stone’s research is in human performance enhancement in both physical and mental domains. He employs multiple approaches toward this goal, including cognitive and physiological engineering, classical and experimental ergonomics, augmented reality, and the incorporation and application of new technologies.

Ulrike Genschel

Ulrike Genschel is an Associate Professor in the Department of Statistics at Iowa State University. Her research interests are in STEM Education and Education Research Methodology.

Fatima Mgaedeh

Fatima Mgaedeh is a PhD student in Iowa State University’s Industrial and Manufacturing Systems Engineering Department. In 2021, she earned her M.S. from ISU and her Bachelor’s in Industrial Engineering from Jordan University of Science & Technology in 2018. Ergonomics, cognitive engineering, and occupational biomechanics are her research areas.