The assessment of pulmonary function in chronic obstructive pulmonary disease (COPD) increasingly relies on non-invasive and highly accessible auxiliary technologies. Multi-channel respiratory sound analysis (MRSA), lung ultrasound (LUS), and impulse oscillometry (IOS) are the 3 promising tools that provide evaluative information from 3 dimensions: spatiotemporal characteristics of respiratory sounds, imaging of lung structure, and airway mechanical parameters, respectively. MRSA uses multi-channel sensors to suppress noise and locate regional ventilation abnormalities; LUS identifies alveolar ventilation status and interstitial edema through real-time ultrasound imaging; and IOS quantifies airway resistance and lung elasticity based on respiratory impedance. Clinical studies have demonstrated considerable clinical value for these 3 technologies in COPD severity grading, early warning of acute exacerbations, etiological differentiation, and treatment monitoring. However, these technologies still face challenges such as insufficient standardization, low device penetration, and significant operator dependence. Introducing artificial intelligence-assisted diagnosis, establishing multi-center standardized databases, and promoting multi-modal technology integration are key directions to improve their practicality and reliability in the future. This review summarizes the principles, clinical applications, and limitations of the aforementioned 3 technologies, aiming to provide a clinical reference for optimizing the non-invasive assessment system for COPD.