Low-Effort Respiratory Function Estimation with a Soft Wearable Digital Spirometry Patch.

Area of Science:

• Pulmonary Medicine
• Biomedical Engineering
• Wearable Technology

Background:

• Spirometry is the gold standard for lung function testing but requires forceful exhalation, causing patient discomfort and needing trained personnel.
• Conditions like asthma and COPD require accurate lung function monitoring, often challenging with traditional spirometry.

Purpose of the Study:

• To introduce the Digital Spirometry Patch (DSP), a wearable device for estimating lung function parameters.
• To evaluate the DSP's ability to measure lung function using low-effort breathing maneuvers as an alternative to traditional spirometry.

Main Methods:

• Developed a soft, flexible, wearable Digital Spirometry Patch (DSP) to capture tracheal sound and chest movement.
• Collected data from 18 participants performing both low-effort and forceful breathing maneuvers with the DSP.
• Utilized elastic net and simple linear regression models for spirometric parameter estimation, validated using leave-one-subject-out cross-validation.

Main Results:

• Elastic net models using low-effort maneuvers achieved Root Mean Square Errors (RMSEs) of 0.668 L (FVC), 0.224 L (FEV1), and 0.428 L/s (PEF).
• Models using forceful maneuvers yielded RMSEs of 0.499 L (FVC), 0.304 L (FEV1), and 0.891 L/s (PEF).
• The DSP demonstrated potential for accurate lung function estimation with reduced patient effort.

Conclusions:

• The Digital Spirometry Patch (DSP) shows promise as a wearable, low-effort alternative to conventional spirometry.
• This technology could facilitate easier and more frequent lung function monitoring outside clinical settings.
• The DSP may improve accessibility and patient comfort in managing cardiopulmonary disorders.