Title: Challenges in Lung and Respiratory Sound Processing: Quantity and Quality of Available Data

Abstract: Respiratory diseases, both acute and chronic, are widespread due to exposure to harmful substances in the environment, workplace, and through personal behaviors. Furthermore, the COVID-19 pandemic has led to both short-term and long-term lung damage in survivors. Therefore, accurate identification of chronic respiratory diseases, in particular, is vital for effective management and treatment. Auscultation, the practice of listening to respiratory sounds, plays a crucial role in diagnosing respiratory diseases. By accurately interpreting these sounds, complemented by other clinical findings, specialists can make reliable diagnoses with minimal errors. However, the effectiveness of auscultation is heavily influenced by the doctor's experience and environmental noise. To address these limitations, automatic classification of respiratory sounds recorded with a digital stethoscope using expert software has emerged as a popular research area. This approach eliminates the reliance on subjective interpretation by specialists. Unfortunately, as with many biomedical signals, researchers face significant challenges. The most pressing issue is the need for high-quality, accurately labeled, and extensive lung and respiratory sound datasets. Additionally, removing noise that distorts these sound signals is another major obstacle. This brief review aims to delve into these two primary challenges and provide examples of potential solutions from relevant literature.

Keywords: lung sound, respiratory sound, data augmentation, noise removal

Başlık: Akciğer ve Solunum Sesi İşlemedeki Zorluklar: Mevcut Verilerin Niceliği ve Niteliği

Özet: Çevresel faktörler, işyeri koşulları ve kişisel alışkanlıklar nedeniyle hem akut hem de kronik solunum hastalıkları sıklıkla görülmektedir. COVID-19 pandemisi ise, uzun vadeli sağlık sorunlarına yol açarak solunum sağlığı üzerinde ek bir yük oluşturmuştur. Bu bağlamda, özellikle kronik solunum hastalıklarının doğru teşhisi ve etkili yönetimi büyük önem taşımaktadır. Solunum seslerinin dinlenmesi (auskultasyon), geleneksel olarak solunum hastalıklarının teşhisinde kullanılan bir yöntemdir. Ancak, bu yöntemin etkinliği, hekimin deneyimine ve çevresel faktörlere bağlı olarak değişkenlik gösterebilmektedir. Bu nedenle, dijital stetoskoplarla kaydedilen solunum seslerinin bilgisayar ortamında otomatik olarak analiz edilmesi, daha objektif ve güvenilir bir teşhis yöntemi olarak öne çıkmaktadır. Ancak, bu alandaki çalışmaların ilerlemesinin önünde bazı önemli zorluklar bulunmaktadır. Bunlardan ilki, doğru etiketlenmiş ve kapsamlı solunum sesi veri setlerinin yetersizliği, ikincisi ise solunum seslerindeki gürültüyü etkili bir şekilde giderme ihtiyacıdır. Bu çalışmada, bu iki temel zorluğa değinilerek, literatürdeki olası çözüm önerileri incelenecektir.

Anahtar kelimeler: solunum sesi, akciğer sesi, veri artırma, gürültü giderme

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