Knee Joint Biomechanical Gait Data Classification for Knee Pathology Assessment: A Literature Review

Area of Science:

• Biomechanics
• Gait Analysis
• Medical Diagnostics

Background:

• Knee joint biomechanics is fundamental to understanding gait patterns.
• Biomechanical gait pattern recognition serves as a valuable diagnostic tool for knee conditions.

Purpose of the Study:

• To review current literature on knee joint biomechanical gait data analysis for knee pathology classification.
• To present prerequisite knee joint biomechanics and gait pattern recognition as a diagnostic tool.
• To discuss current research findings and future directions in the field.

Main Methods:

• Literature search conducted in PubMed, IEEE Xplore, Science Direct, and Google Scholar.
• Inclusion criteria focused on English or French articles concerning knee joint biomechanical gait data classification.
• Relevant information on pathologies, participant attributes, data acquisition, feature extraction, classification algorithms, and validation was recorded.

Main Results:

• Thirty-one studies met the inclusion criteria for the review.

Conclusions:

• The importance of medical applications in knee joint biomechanical gait data classification is growing.
• Advancements in data acquisition technology are driving research interest and progress.
• Biomechanical gait data during locomotion contain essential information for early knee joint condition diagnosis.