Published on in Vol 9, No 1 (2021): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/22753, first published .
A Low-Cost, Ear-Contactless Electronic Stethoscope Powered by Raspberry Pi for Auscultation of Patients With COVID-19: Prototype Development and Feasibility Study

A Low-Cost, Ear-Contactless Electronic Stethoscope Powered by Raspberry Pi for Auscultation of Patients With COVID-19: Prototype Development and Feasibility Study

A Low-Cost, Ear-Contactless Electronic Stethoscope Powered by Raspberry Pi for Auscultation of Patients With COVID-19: Prototype Development and Feasibility Study

Journals

  1. Ahuja V, Kini P, Nileshwar A. Evaluation of the electronic stethoscope (FONODOC) as a cardiac screening tool during the preoperative evaluation of children. Indian Journal of Anaesthesia 2022;66(9):625 View
  2. Dramburg S, Dellbrügger E, van Aalderen W, Matricardi P. The impact of a digital wheeze detector on parental disease management of pre-school children suffering from wheezing—a pilot study. Pilot and Feasibility Studies 2021;7(1) View
  3. Zhu J, Jiang C, Huang B, Hu J, Fang S, Huang K, Gao Y, Yu J. Cylindrical Tube Stethoscopes: The Value of Practical Equipment in the Management of Patients with Infectious Diseases. Infection and Drug Resistance 2022;Volume 15:3611 View
  4. Gavrishev A, Gavrisheva N. New Technological Approaches to the Organization of the Work of Medical Personnel Performing Auscultation of Patients with COVID-19. Biomedical Engineering 2022;56(3):211 View
  5. Yeung A, Kulnik S, Parvanov E, Fassl A, Eibensteiner F, Völkl-Kernstock S, Kletecka-Pulker M, Crutzen R, Gutenberg J, Höppchen I, Niebauer J, Smeddinck J, Willschke H, Atanasov A. Research on Digital Technology Use in Cardiology: Bibliometric Analysis. Journal of Medical Internet Research 2022;24(5):e36086 View
  6. Kasim N, Bachner-Hinenzon N, Brikman S, Cheshin O, Adler D, Dori G. A comparison of the power of breathing sounds signals acquired with a smart stethoscope from a cohort of COVID-19 patients at peak disease, and pre-discharge from the hospital. Biomedical Signal Processing and Control 2022;78:103920 View
  7. Lapteva E, Kharevich O, Khatsko V, Voronova N, Chamko M, Bezruchko I, Katibnikova E, Loban E, Mouawie M, Binetskaya H, Aleshkevich S, Karankevich A, Dubinetski V, Vestbo J, Mathioudakis A. Automated lung sound analysis using the LungPass platform: a sensitive and specific tool for identifying lower respiratory tract involvement in COVID-19. European Respiratory Journal 2021;58(6):2101907 View
  8. Chen J, Guo Z, Xu X, Jeon G, Camacho D. Artificial intelligence for heart sound classification: A review. Expert Systems 2024;41(4) View