Literature DB >> 8026851

Adaptive cancellation of muscle contraction interference in vibroarthrographic signals.

Y T Zhang1, R M Rangayyan, C B Frank, G D Bell.   

Abstract

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.

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Year:  1994        PMID: 8026851     DOI: 10.1109/10.284929

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  7 in total

1.  Automatic de-noising of knee-joint vibration signals using adaptive time-frequency representations.

Authors:  S Krishnan; R M Rangayyan
Journal:  Med Biol Eng Comput       Date:  2000-01       Impact factor: 2.602

2.  Knee joint vibroarthrography of asymptomatic subjects during loaded flexion-extension movements.

Authors:  Rasmus Elbæk Andersen; Lars Arendt-Nielsen; Pascal Madeleine
Journal:  Med Biol Eng Comput       Date:  2018-06-21       Impact factor: 2.602

3.  Vibroarthrography for early detection of knee osteoarthritis using normalized frequency features.

Authors:  Nima Befrui; Jens Elsner; Achim Flesser; Jacqueline Huvanandana; Oussama Jarrousse; Tuan Nam Le; Marcus Müller; Walther H W Schulze; Stefan Taing; Simon Weidert
Journal:  Med Biol Eng Comput       Date:  2018-02-01       Impact factor: 2.602

4.  Adaptive filtering, modelling and classification of knee joint vibroarthrographic signals for non-invasive diagnosis of articular cartilage pathology.

Authors:  S Krishnan; R M Rangayyan; G D Bell; C B Frank; K O Ladly
Journal:  Med Biol Eng Comput       Date:  1997-11       Impact factor: 2.602

5.  Screening of knee-joint vibroarthrographic signals using statistical parameters and radial basis functions.

Authors:  Rangaraj M Rangayyan; Y F Wu
Journal:  Med Biol Eng Comput       Date:  2007-10-25       Impact factor: 2.602

Review 6.  Engineering Aspects of Incidence, Prevalence, and Management of Osteoarthritis: A Review.

Authors:  Dhirendra Kumar Verma; Poonam Kumari; Subramani Kanagaraj
Journal:  Ann Biomed Eng       Date:  2022-01-21       Impact factor: 3.934

7.  Preliminary study of optimal measurement location on vibroarthrography for classification of patients with knee osteoarthritis.

Authors:  Susumu Ota; Akiko Ando; Yusuke Tozawa; Takuya Nakamura; Shogo Okamoto; Takenobu Sakai; Kazunori Hase
Journal:  J Phys Ther Sci       Date:  2016-10-28
  7 in total

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