A Pervasive Pulmonary Function Estimation System with Six-Minute Walking Test.

Area of Science:

• Biomedical Engineering
• Respiratory Medicine
• Wearable Technology

Background:

• Home spirometry accuracy and repeatability are often insufficient for monitoring lung disease progression.
• Accurate self-monitoring of pulmonary function is crucial for managing respiratory conditions and assessing rehabilitation effectiveness.

Purpose of the Study:

• To develop and validate a pervasive spirometry estimation system using the six-minute walking test (6MWT).
• To create predictive models for per step distance (PSD), forced vital capacity (FVC), and forced expiratory volume in one second (FEV1) implemented in a wrist-worn device.

Main Methods:

• A system integrating information management, communication protocols, predictive algorithms, and a wrist-worn device was developed.
• Sixty respiratory disease patients underwent pulmonary function tests and 6MWT; data were used to build predictive models.
• Models were implemented in a wrist-worn device for real-time pulmonary function estimation.

Main Results:

• Predictive models for PSD, FVC, and FEV1 using 6MWT data were successfully created.
• Estimated differences for PSD, FVC, and FEV1 showed acceptable accuracy.
• The system demonstrated high sensitivity (90.9%) for detecting obstructive lung diseases post-6MWT.

Conclusions:

• The developed wrist-worn system effectively estimates pulmonary function using the 6MWT.
• This pervasive system offers a practical tool for self-estimation of FVC and FEV1, especially for individuals with limitations in home spirometry.