Classification of temporomandibular joint sounds based upon their reduced interference distribution

Area of Science:

• Biomedical Engineering
• Oral and Maxillofacial Surgery
• Acoustics

Background:

• Temporomandibular joint (TMJ) sounds are common in orthodontic patients.
• Traditional methods like auscultation and patient interviews have limitations in characterizing TMJ sounds.
• Objective and detailed classification of TMJ sounds is needed for accurate diagnosis and treatment.

Purpose of the Study:

• To evaluate the effectiveness of a novel time-frequency analysis method, the reduced interference distribution (RID), for classifying TMJ sounds.
• To compare the diagnostic capabilities of RID analysis with traditional auscultation and interview methods.
• To explore the potential of RID-based classification for differentiating various TMJ sound pathologies.

Main Methods:

• Recorded temporomandibular joint (TMJ) sounds in 98 orthodontic retention patients.
• Utilized interview, auscultation, and electronic recording for sound data acquisition.
• Applied a new time-frequency analysis technique, the reduced interference distribution (RID), to classify electronic sound recordings into five subclasses (RID types 1-5).

Main Results:

• Auscultation detected TMJ sounds in 41% and interviews in 32% of subjects, with higher prevalence in females.
• RID analysis classified sounds into five types based on energy peak characteristics.
• RID types 4-5, associated with crepitation, showed multiple energy peaks within 20-300 ms.
• RID type 1, linked to clicking, was more frequent in females (< 600 Hz dominant peak).
• RID types 2 and 3 showed similar gender distribution across different frequency ranges (600-1200 Hz and > 1200 Hz, respectively).
• RID type 5 (30 Hz to 3000 Hz) was more prevalent in females.

Conclusions:

• The reduced interference distribution (RID) method provides a more detailed classification of temporomandibular joint (TMJ) sounds compared to auscultation.
• RID classification may enable differentiation of TMJ sounds indicative of distinct pathological conditions.
• This advanced analysis technique holds promise for improved diagnosis and understanding of TMJ disorders.