Compliant Mechanism Needle Guidance With Smartphone Magnetic Tracking

Precise needle placement is crucial to ensure both safety and efficacy during needle intervention procedures. Traditionally, interventional radiologists conduct cancer biopsies using image guided techniques where images are used to help guide and track needle placement. Such procedures are oftentimes performed freehand and require high-level motor-visual coordination to adequately map needle placement using the medical images. As a result, biopsies are time-consuming, with accuracy heavily dependent on the experience of the operator. In this work, a compliant mechanism-based magnetic tracking device combined with a smartphone has been designed to address the shortcomings of current image-guided needle targeting systems. Smartphones, being ubiquitous, are equipped with sufficient processing power for data analysis, pair well with permanent magnet-based magnetic tracking systems, and do not require an external power supply during operation. In the procedure, the system is placed on the abdomen of the patient. The compliant mechanism can hold the needle such that there is a remote centre of motion (RCM) on the surface of the patient’s skin. This RCM allows for a fixed skin entry point, minimising possible tissue tearing that occurs due to unintended needle translation. In this study, the working principle of the compliant mechanism and the mathematical model for magnetic tracking are introduced. Experimental results show that the device’s average angular tracking errors are 0.96∘( left-to-right), and 0.89∘ (head-to-foot), with standard deviations of 1.09∘ and 0.86∘, respectively. The RCM points are distributed within ranges of 0.52×3.48 mm (left-to-right) and 0.53 × 2.19 mm (head-to-foot).

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Publication Details

Journal
IEEE Transactions on Medical Robotics and Bionics
Published
2025-04-18
DOI
https://doi.org/10.1109/tmrb.2025.3562272
Primary Topic
Augmented Reality Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Compliant Mechanism Needle Guidance With Smartphone Magnetic Tracking

Haipeng Liang, Hongguang Li, Zion Tsz Ho Tse
IEEE Transactions on Medical Robotics and Bionics
Augmented Reality Applications
article

Compliant Mechanism Needle Guidance With Smartphone Magnetic Tracking

Haipeng Liang, Hongguang Li, Zion Tsz Ho Tse
article en

Abstract

Precise needle placement is crucial to ensure both safety and efficacy during needle intervention procedures. Traditionally, interventional radiologists conduct cancer biopsies using image guided techniques where images are used to help guide and track needle placement. Such procedures are oftentimes performed freehand and require high-level motor-visual coordination to adequately map needle placement using the medical images. As a result, biopsies are time-consuming, with accuracy heavily dependent on the experience of the operator. In this work, a compliant mechanism-based magnetic tracking device combined with a smartphone has been designed to address the shortcomings of current image-guided needle targeting systems. Smartphones, being ubiquitous, are equipped with sufficient processing power for data analysis, pair well with permanent magnet-based magnetic tracking systems, and do not require an external power supply during operation. In the procedure, the system is placed on the abdomen of the patient. The compliant mechanism can hold the needle such that there is a remote centre of motion (RCM) on the surface of the patient’s skin. This RCM allows for a fixed skin entry point, minimising possible tissue tearing that occurs due to unintended needle translation. In this study, the working principle of the compliant mechanism and the mathematical model for magnetic tracking are introduced. Experimental results show that the device’s average angular tracking errors are 0.96∘( left-to-right), and 0.89∘ (head-to-foot), with standard deviations of 1.09∘ and 0.86∘, respectively. The RCM points are distributed within ranges of 0.52×3.48 mm (left-to-right) and 0.53 × 2.19 mm (head-to-foot).

IEEE Transactions on Medical Robotics and BionicsVol. 7(4)
Queen Mary University of London (GB)
Cancer Research UK
Affordable and clean energy
Openalex Percentile: Top 94%
Augmented Reality Applications
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