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Assist. Lecturer

Mohammed Tawfeeq Yahya alnshah

Research Interests

veterinary science

Gender MALE
Place of Work Mosul Medical Technical Institute
Position Lecturer
Qualification Master
Speciality Internal and preventive medicine veterinary
Email Mohammad.tawfeek@ntu.edu.iq
Phone 07704419713
Address Mosul- Hay al-sediq, Mosul, Ninavah, Iraq

working experience

Academic Qualification

Master's degree in veterinary internal and preventive medicine
Nov 9, 2020 - Dec 12, 2022

veterinary internal and preventive medicine

Publications

Using of Oximeter and Sound Analysis for Detection of Lung Lesions in Buffalo Calves
Nov 10, 2022

Journal NTU Journal of Agriculture and Veterinary Science

publisher Mohammed Tawfeeg Al-Noaemy

DOI http://dx.doi.org/10.56286/ntujavs.v2i2.390

Issue 2788- A9904

Volume 2

Auscultation of the lung is the first line for the diagnosis of lung lesions. Analysis of the auscultated sounds is promising in the diagnosis confirmation. The aim of this study is to evaluate the use of sound analysis and oximeter for detection of the lung lesions in buffalo calves. The study included 100 calves showing respiratory symptoms and 30 clinically healthy calves serving as a control group which aged between (2-6) months from different areas in Mosul City. A pulse oximeter was used to measure the percentage of oxygen blood saturation, then measuring sound frequencies based on multi-resolution sound wave analysis by using digital program (WavePad). Affected calves showed coughing (100%), lacrimation (88%), nasal discharge (86%) and fever (58%). The sound analysis indicated that the natural sound frequency was (221) Hz, gradually increasing to (390.5) Hz in case of pneumonia. It then became (428) Hz in calves with wheezing sound. Diminished breathing sound had a frequency of 426) Hz synchronous with pauses that lasted (0.4) seconds after each complete inhalation and exhalation cycle. An oximeter reading had a positive correlation with each nasal discharge and eye lacrimation, while it had a negative correlation with both coughing and body temperature. The study concluded that sound wave analysis and oximeter were highly accurate in diagnosing the severity of the lung lesion compared to the detection of the clinical signs.

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