Dyadic wavelet analysis and detection of sinusitis using near infrared sensor


  • S. Kamatchi Sathyabama University, Shollinganallur, Chennai http://orcid.org/0000-0001-8781-5517
  • M. Sundararajan Bharath Institute of Higher Education and Technology, Agaram Road, Selaiyur, Chennai




Sinusitis, Dyadic wavelet transform, Near infrared sensor, Regression analysis, Plain radiography, NIR-LED sensor, NIR sensing


Background: Sinusitis is a chronic infection or inflammation which affects the paranasal sinus cavities and the associated nasal cavities. As the symptoms of sinusitis greatly resemble upper respiratory infections, diagnosing sinusitis clinically is a major issue. Though imaging techniques serves as a standard in confirming the diagnosis of chronic sinusitis, the availability at the primary care settings, affordability and diagnosing acute cases calls upon an alternative technique in practice. Recent researches confirming the diagnosis of sinusitis using Near-infrared imaging gives us hope in taking up the research using optical sensing. The objective of the study was to successfully diagnose sinusitis using NIR-LED optical sensor and to signal process the data obtained from the patients using Dyadic Wavelet Transform (DyWT) to confirm and to validate diagnosis using regression analysis. The study also correlates the plain radiographic findings with the NIR device sensing to make the device feasible.

Methods: This was a one year pilot study (June 2014–May 2015) conducted with forty patients suspected of sinusitis and with clinical history along with ten healthy individuals as controls.  

Results: Patients age ranged from 18-65 years were included in the study. Results from NIR sensing device well correlate with the radiographic examination of the registered candidates. The regression result perfectly matches with the dyadic wavelet results of the patients, confirming the diagnosing of sinusitis using near- infrared sensor. Radiographic examination well correlates with the results from the NIR diagnostic device providing a valuable evidence of the hardware.

Conclusions: NIR-LED sensor device can provide qualitative evidence in differentiating the mild and severe patients based on air-fluid level present in the sinus. The results strongly recommend that NIR sensing device can be a best alternative in case of frequently sinus affected patients and for the unaffordable patients without the risk of radiation.

Author Biography

S. Kamatchi, Sathyabama University, Shollinganallur, Chennai

Research scholar, ETCE


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Original Research Articles