Publications by authors named "Zhuoqi Cheng"

Article Synopsis
  • Lumbar punctures, while essential for diagnostics and therapies, can be risky due to variations in soft tissue, especially in older and obese patients; a new robot-assisted system aims to improve precision by automatically targeting the right tissue layer using tissue recognition techniques.!* -
  • The robotic system uses a probe with concentric electrodes to measure bio-impedance signals, which are analyzed by a master computer using a Bayesian neural network to classify different soft tissues and guide the robotic movement accordingly.!* -
  • Testing on ex vivo tissue phantoms shows that this technology may enhance the safety and accuracy of lumbar punctures, and it could also be adapted for other procedures like discography and epidural steroid injections, provided tissue recognition can
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The early detection of head and neck squamous cell carcinoma (HNSCC) is essential to improve patient prognosis and enable organ and function preservation treatments. The objective of this study is to assess the feasibility of using electrical bioimpedance (EBI) sensing technology to detect HNSCC tissue. A prospective study was carried out analyzing tissue from 46 patients undergoing surgery for HNSCC.

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Article Synopsis
  • The study explores how static and dynamic stresses affect the electrical properties of soft tissues, highlighting their sensitivity to applied forces.
  • An experimental platform is created to measure both force and electrical properties of soft tissues under various compression methods, including constant force and speed.
  • The research introduces a piezoresistive model to understand the mechanical-electrical behavior of soft tissues, using Finite Element Modeling (FEM) to analyze static piezoresistivity and validate the model through experiments.
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Tissue recognition is a critical process during a Robot-assisted minimally invasive surgery (RMIS) and it relies on the involvement of advanced sensing technology.In this paper, the concept of Robot Assisted Electrical Impedance Sensing (RAEIS) is utilized and further developed aiming to sense the electrical bioimpedance of target tissue directly based on the existing robotic instruments and control strategy. Specifically, we present a new sensing configuration called pseudo-tetrapolar method.

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Robots can protect healthcare workers from being infected by the COVID-19 and play a role in throat swab sampling operation. A critical requirement in this process is to maintain a constant force on the tissue for ensuring a safe and good sampling. In this study, we present the design of a disposable mechanism with two non-linear springs to achieve a 0.

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The electrical impedance tomography (EIT) technology is an important medical imaging approach to show the electrical characteristics and the homogeneity of a tissue region noninvasively. Recently, this technology has been introduced to the Robot Assisted Minimally Invasive Surgery (RAMIS) for assisting the detection of surgical margin with relevant clinical benefits. Nevertheless, most EIT technologies are based on a fixed multiple-electrodes probe which limits the sensing flexibility and capability significantly.

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With the evolving demands of surgical intervention, there is a strong need for smaller and functionally augmented instruments to improve surgical outcomes, operational convenience, and diagnostic safety. Owing to the narrow and complicated anatomy, the probe head of the medical instrument is required to possess both good maneuverability and compact size. In addition, the development of medical instrument is moving toward patient-specialized, of which the articulation positions can be customized to reach the target position.

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In Robot Assisted Minimally Invasive Surgery, discriminating critical subsurface structures is essential to make the surgical procedure safer and more efficient. In this paper, a novel robot assisted electrical bio-impedance scanning (RAEIS) system is developed and validated using a series of experiments. The proposed system constructs a tri-polar sensing configuration for tissue homogeneity inspection.

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Article Synopsis
  • Surgeons often face challenges in identifying abnormal tissues and determining resection margins during minimally invasive surgeries.
  • This study introduces a drop-in sensor probe that uses electrical bioimpedance technology, allowing surgeons to easily inspect suspicious tissue areas using laparoscopic forceps.
  • Experiments conducted on porcine liver tissue demonstrate the probe's effectiveness, achieving tissue classification accuracies of 80% and 100% with impedance measurements taken across various frequencies.
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Article Synopsis
  • SmartProbe is a new electrical bioimpedance sensing system that uses concentric needle electrodes for real-time cancer detection in living tissues.
  • The study introduces a statistical learning-based calibration method to improve measurement accuracy, achieving less than 6% relative error when assessing the relationship between impedance and material conductivity.
  • Experimental results show the system can effectively differentiate between cancerous and healthy tissues in various human samples, indicating its potential for broader applications in cancer diagnostics.
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The integration of intra-operative sensors into surgical robots is a hot research topic since this can significantly facilitate complex surgical procedures by enhancing surgical awareness with real-time tissue information. However, currently available intra-operative sensing technologies are mainly based on image processing and force feedback, which normally require heavy computation or complicated hardware modifications of existing surgical tools. This paper presents the design and integration of electrical bio-impedance sensing into a commercial surgical robot tool, leading to the creation of a novel smart instrument that allows the identification of tissues by simply touching them.

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Peripheral intravenous catheterization (PIVC) is frequently required for various medical treatments. Over 1 billion PIVC operations are performed per year in the United States alone. However, this operation is characterized by a very low success rate, especially amongst pediatric patients.

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Intravenous catheterization is frequently required for numerous medical treatments. However, this process is characterized by a high failure rate, especially when performed on difficult patients such as newborns and infants. Very young patients have small veins, and that increases the chances of accidentally puncturing the catheterization needle directly through them.

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Robot-assisted needle-based surgeries are sought to improve many operations, from brain surgery to spine and urological procedures. Force feedback from a needle can provide important guidance during needle insertion. This paper presents a new modelling method of needle force during insertion into soft tissue based on finite element simulation.

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