Vibroarthrography (VAG) is an innovative, objective, non-invasive technique for obtaining
diagnostic information concerning the articular cartilage of a joint. Knee VAG signals
can be detected using a contact sensor over the skin surface of the knee joint during
knee movement such as flexion and/or extension. These measured signals, however, contain
significant interference caused by muscle contraction that is required for knee movement.
Quality improvement of VAG signals is an important subject, and crucial in computer-aided
diagnosis of cartilage pathology. While simple frequency domain high-pass (or band-pass)
filtering could be used for minimizing muscle contraction interference (MCI), it could
eliminate possible overlapping spectral components of the VAG signals. In this work,
an adaptive MCI cancellation technique is presented as an alternative technique for
filtering VAG signals. Methods of measuring the VAG and reference signals (MCI) are
described, with details on MCI identification, characterization, and step size optimization
for the adaptive filter. The performance of the method is evaluated by simulated signals
as well as signals obtained from human subjects under isotonic contraction.