Introducing the Pi-CON Methodology to Overcome Usability Deficits during Remote Patient Monitoring.

Area of Science:

• Biomedical Engineering
• Health Informatics
• Wearable Technology

Background:

• The widespread adoption of telehealth and virtual care has increased the use of Remote Patient Monitoring (RPM) and Patient-Generated Health Data (PGHD).
• Challenges exist with current PGHD devices, particularly regarding device usability outside clinical settings, which can compromise data quality.
• Existing monitoring solutions often require significant user interaction or direct sensor attachment, limiting continuous and passive data collection.

Purpose of the Study:

• To introduce the Pi-CON (passive, continuous, non-contact) methodology for developing user-friendly and intuitive health monitoring devices.
• To address the limitations of current PGHD devices by enabling effortless, continuous health data acquisition.
• To guide the future design of devices that minimize user interaction while maximizing data integrity.

Main Methods:

• Literature review to identify challenges in current RPM and PGHD device usability.
• Introduction and explanation of the Pi-CON methodology principles.
• Exploration of enabling technologies such as radar, remote photoplethysmography, and infrared sensors.
• Discussion of system architecture including omnipresent sensors and cloud-based interfaces.

Main Results:

• The Pi-CON methodology facilitates passive, continuous, and non-contact acquisition of vital signs and other health data.
• Leveraging technologies like radar and remote photoplethysmography enhances data capture without direct patient contact.
• Potential applications include continuous gait and fall monitoring with automatic data collection upon recognition.
• Integration with gateways and cloud platforms enables remote, real-time patient health status monitoring for clinicians and family.

Conclusions:

• The Pi-CON methodology presents a novel approach to overcome usability issues in remote patient monitoring.
• This methodology supports the development of intuitive devices for seamless health data generation, crucial for telehealth expansion.
• Future applications of Pi-CON hold significant promise for proactive health management and remote patient care.