Recognition of Finger Flexion Motion from Ultrasound Image: A Feasibility Study

Jun Shi, Jing Yi Guo, Shu Xian Hu, Yongping Zheng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

33 Citations (Scopus)

Abstract

Muscle contraction results in structural and morphologic changes of the related muscle. Therefore, finger flexion can be monitored from measurements of these morphologic changes. We used ultrasound imaging to record muscle activities during finger flexion and extracted features to discriminate different fingers' flexions using a support vector machine (SVM). Registration of ultrasound images before and after finger flexion was performed to generate a deformation field, from which angle features and wavelet-based features were extracted. The SVM was then used to classify the motions of different fingers. The experimental results showed that the overall mean recognition accuracy was 94.05% ± 4.10%, with the highest for the thumb (97%) and the lowest for the ring finger (92%) and the mean F value was 0.94 ± 0.02, indicating high accuracy and reliability of this method. The results suggest that the proposed method has the potential to be used as an alternative method of surface electromyography in differentiating the motions of different fingers.
Original languageEnglish
Pages (from-to)1695-1704
Number of pages10
JournalUltrasound in Medicine and Biology
Volume38
Issue number10
DOIs
Publication statusPublished - 1 Oct 2012

Keywords

  • Deformation field
  • Finger flexion
  • Image registration
  • Muscle
  • Recognition
  • Ultrasound image

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Biophysics
  • Radiology Nuclear Medicine and imaging

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