Literature DB >> 24254254

Drilling electrode for real-time measurement of electrical impedance in bone tissues.

Yu Dai1, Yuan Xue, Jianxun Zhang.   

Abstract

In order to prevent possible damages to soft tissues, reliable monitoring methods are required to provide valuable information on the condition of the bone being cut. This paper describes the design of an electrical impedance sensing drill developed to estimate the relative position between the drill and the bone being drilled. The two-electrode method is applied to continuously measure the electrical impedance during a drill feeding movement: two copper wire brushes are used to conduct electricity in the rotating drill and then the drill is one electrode; a needle is inserted into the soft tissues adjacent to the bone being drilled and acts as another electrode. Considering that the recorded electrical impedance is correlated with the insertion depth of the drill, we theoretically calculate the electrode-tissue contact impedance and prove that the rate of impedance change varies considerably when the drill bit crosses the boundary between two different bone tissues. Therefore, the rate of impedance change is used to determine whether the tip of the drill is located in one of cortical bone, cancellous bone, and cortical bone near a boundary with soft tissue. In vitro experiments in porcine thoracic spines were performed to demonstrate the feasibility of the impedance sensing drill. The experimental results indicate that the drill, used with the proposed data-processing method, can provide accurate and reliable breakthrough detection in the bone-drilling process.

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Year:  2013        PMID: 24254254     DOI: 10.1007/s10439-013-0938-8

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


  2 in total

Review 1.  Advances in tissue state recognition in spinal surgery: a review.

Authors:  Hao Qu; Yu Zhao
Journal:  Front Med       Date:  2021-05-15       Impact factor: 4.592

2.  Tissue Recognition Based on Electrical Impedance Classified by Support Vector Machine in Spinal Operation Area.

Authors:  Bingrong Chen; Yongwang Shi; Jiahao Li; Jiliang Zhai; Liang Liu; Wenyong Liu; Lei Hu; Yu Zhao
Journal:  Orthop Surg       Date:  2022-08-01       Impact factor: 2.279

  2 in total

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