Artificial Intelligence-Assisted Identification and Prevention of Chronic Obstructive Pulmonary Disease Using...

Chronic obstructive pulmonary disease (COPD) is a respiratory disease imposing significant economic and health burdens to patients. The long latent period of COPD due to inhalation of PM 0.3 makes it difficult to prevent and identify the disease at an early stage. Herein, an environmentally friendly and long-term reliable nanofiber membrane with detection of COPD and filtration of PM 0.3 function is developed based on piezoelectric poly(l-lactic acid) (PLLA)/lactic acid-based copolyester piezoelectric elastomer (LCPE) composites. The LCPE is synthesized with low elastic modulus and high piezoelectricity, which firmly bonds with PLLA and acts as a stress concentration point in the fiber framework, converting local fiber vibrations into global film vibrations and helping to improve the acoustic-electric conversion of PLLA/LCPE nanofiber filtration membranes (PLNFM), which is 24 times that of neat PLLA under the same airflow. The PLNFM enables COPD identification by acoustic spectrum recognition through artificial intelligence (AI)-assisted algorithms, presenting a high recognition rate of over 92.3%. Meanwhile, the interwoven structure of PLNFM and the induced piezoelectric charge achieve PM 0.3 filtration efficiency as high as 99.975%. The respiratory disease identification function, high PM 0.3 filtration efficiency, and reusable performance of PLNFM provide great potential in intelligent wearable device fields.