Enhanced frequency analysis on a vibrated tumor with a compression cylinder

Satoshi Miura*, Hidekazu Ishiuchi, Yuta Shintaku, Victor Parque, Ayako Torisaka, Tomoyuki Miyashita

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


Breast cancer diagnosis has been mostly accomplished through imaging. These methods have great advantages in being able to detect the presence and location of breast cancer. However, it is difficult to distinguish between a benign and malignant tumor located in a deep position because both tumor types look similar. In this paper, tissue including the tumor from skin was vibrated using a compression cylinder, to analyze the frequency difference for distinguishing tissue type. Before distinguishing between a benign and malignant tumor, it is necessary to validate that the difference between normal tissue and tumor can be distinguished. The objective of the study is to validate the feasibility to emphasize the frequency differences in a 10.0 mm or greater deep tumors during vibration by pushing a cylinder towards the deep tumor. A phantom model and finite element analysis model were constructed to simulate the breast. In the experiment, air was injected into the phantom and the displacement was measured. The frequency response for distinction of tissue types was analyzed and it was found that the displacement difference rate was over 50% at a frequency of 130 Hz when the cylinder was pushed into the sample as opposed to when not pushed in. Changes in displacement were measured according to the distance between the tumor and vibration point using finite element analysis. When the measurement and vibration points were on the center of the tumor, the difference in the resonance point was at its largest (5.5 Hz). Results show that the position of a tumor could be easily and rapidly detected by vibrations from a cylinder pushed into the diagnostic site.

Original languageEnglish
Article number10
JournalROBOMECH Journal
Issue number1
Publication statusPublished - 2019 Dec 1


  • Breast cancer diagnosis
  • Resonance frequency analysis
  • Vibration analysis

ASJC Scopus subject areas

  • Modelling and Simulation
  • Instrumentation
  • Mechanical Engineering
  • Control and Optimization
  • Artificial Intelligence


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