Non-Contact Detection of Apnea-like Breathing Cessations Using Laser Speckle Pattern Analysis

Sleep apnea is a prevalent sleep-related breathing disorder characterized by recurrent cessations or reductions in airflow during sleep. It significantly impacts the quality of life, yet current diagnostic methods like polysomnography (PSG) are expensive and uncomfortable, limiting accessibility and ease of use. We developed a novel non-contact biosensing system using secondary laser speckle pattern analysis and dedicated image processing algorithms for apnea-like breathing cessations. The proposed method was tested on 14 healthy subjects with diverse body characteristics, aged 22-50 years (mean 33.1 ± 9.3 years) and body mass index (BMI) ranging from 19.6 to 28.7 kg/m² (mean 24.6 ± 3.0 kg/m²) at different 'simulated' sleeping positions (back-lying, stomach-lying and side-lying), using voluntary breath-holding protocols to simulate apnea-like cessations lasting 10-20 s (short duration) and 20-30 s (long duration). To evaluate the performance of the system without selection bias, two complementary five-fold cross-validation procedures were applied: a participant-level and a class-level stratification. Using class-wise stratification, the system achieved an overall accuracy of 87.0 ± 3.0% (95% CI: [85.3%, 88.7%]), long-cessation sensitivity of 91 ± 12.4%(95% CI:[83.8%,98.2%]) and a short-cessation sensitivity of 88.0 ± 11%(95% CI:[81.6%,94.4%]). The two-class classification strategy confirm the robustness of the approach, supporting the potential of secondary laser speckle pattern analysis as a low-cost, non-contact alternative for home-based sleep apnea screening.