Development and evaluation of a robotic system for lumbar puncture and epidural steroid injection.

Introduction: Lumbar puncture is an important medical procedure for various diagnostics and therapies, but it can be hazardous due to individual variances in subcutaneous soft tissue, especially in the elderly and obese. Our research describes a novel robot-assisted puncture system that automatically controls and maintains the probe at the target tissue layer through a process of tissue recognition. Methods: The system comprises a robotic system and a master computer. The robotic system is constructed based on a probe consisting of a pair of concentric electrodes. From the probe, impedance spectroscopy measures bio-impedance signals and transforms them into spectra that are communicated to the master computer. The master computer uses a Bayesian neural network to classify the bio-impedance spectra as corresponding to different soft tissues. By feeding the bio-impedance spectra of unknown tissues into the Bayesian neural network, we can determine their categories. Based on the recognition results, the master computer controls the motion of the robotic system. Results: The proposed system is demonstrated on a realistic phantom made of ex vivo tissues to simulate the spinal environment. The findings indicate that the technology has the potential to increase the precision and security of lumbar punctures and associated procedures. Discussion: In addition to lumbar puncture, the robotic system is suitable for related puncture operations such as discography, radiofrequency ablation, facet joint injection, and epidural steroid injection, as long as the required tissue recognition features are available. These operations can only be carried out once the puncture needle and additional instruments reach the target tissue layer, despite their ensuing processes being distinct.

Electric Bioimpedance Sensing for the Detection of Head and Neck Squamous Cell Carcinoma.

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. The goal was the correct identification of pathologic tissue using a novel needle-based EBI sensing device and AI-based classifiers. Considering the data from the overall patient cohort, the system achieved accuracies between 0.67 and 0.93 when tested on tissues from the mucosa, skin, muscle, lymph node, and cartilage. Furthermore, when considering a patient-specific setting, the accuracy range increased to values between 0.82 and 0.95. This indicates that more reliable results may be achieved when considering a tissue-specific and patient-specific tissue assessment approach. Overall, this study shows that EBI sensing may be a reliable technology to distinguish pathologic from healthy tissue in the head and neck region. This observation supports the continuation of this research on the clinical use of EBI-based devices for early detection and margin assessment of HNSCC.

Piezoresistivity modeling of soft tissue electrical-mechanical properties: A validation study.

In general, the electrical property of soft tissues is sensitive to the force applied to their surface. To further study the relationship between the force and the electrical property of soft tissues, this paper attempts to investigate the effect of static and higher-order stresses on electrical properties. Overall, a practical experimental platform is designed to acquire the force information and the electrical property of soft tissues during a contact procedure, which is featured different compression stimuli, such as constant pressing force, constant pressing speed, and step-force compression, etc. Furthermore, the piezoresistive characteristic is innovatively introduced to model the mechanical-electrical properties of soft tissue. Finite Element Modeling (FEM) is adopted to fit the static piezoresistivity of the soft tissue. Finally, experimental studies were performed to demonstrate the effect of stress on the electrical properties and the feasibility of the proposed piezoresistive model to describe soft tissues' mechanical and electrical properties.

Monopolar, bipolar, tripolar, and tetrapolar configurations in robot assisted electrical impedance sensing.

Objective.Tissue recognition is a critical process during a Robot-assisted minimally invasive surgery (RMIS) and it relies on the involvement of advanced sensing technology.Approach.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. With the help of robotic control, we can achieve a similar configuration as traditional tetrapolar, and with better accuracy.Main results.Five configurations including monopolar, bipolar, tripolar, tetrapolar and pseudo-tetrapolar are analyzed and compared through simulation experiments. Advantages and disadvantages of each configuration are thus discussed.Significance.This study investigates the measurement of tissue electrical property directly based on the existing robotic surgical instruments. Specifically, different sensing configurations can be realized through different connection and control strategies, making them suitable for different application scenarios.

An Electrical Bioimpedance Scanning System for Subsurface Tissue Detection in Robot Assisted Minimally Invasive Surgery.

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. Specifically, two robotic forceps are used as electrodes for applying electric current and measuring reciprocal voltages relative to a ground electrode which is placed distal from the measuring site. Compared to existing electrical bioimpedance sensing technology, the proposed system is able to use miniaturized electrodes to measure a site flexibly with enhanced subsurfacial detection capability. This paper presents the concept, the modeling of the sensing method, the hardware design, and the system calibration. Subsequently, a series of experiments are conducted for system evaluation including finite element simulation, saline solution bath experiments and experiments based on ex vivo animal tissues. The experimental results demonstrate that the proposed system can measure the resistivity of the material with high accuracy, and detect a subsurface non-homogeneous object with 100% success rate. The proposed parameters estimation algorithm is able to approximate the resistivity and the depth of the subsurface object effectively with one fast scanning.

Smart handheld device with flexible wrist and electrical bioimpedance sensor for tissue inspection.

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. To fulfill these requirements, this study presents the design of a smart handheld device which equips with a low cost, easy control, disposable flexible wrist, and an electrical bioimpedance sensor for medical diagnosis. Prototype of the device is made and tested. The experimental results demonstrate that the proposed device can provide accurate manipulation and effective tissue detection, showing a great potential in various medical applications.

Robot-Assisted Electrical Impedance Scanning system for 2D Electrical Impedance Tomography tissue inspection.

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. In this study, we present a method for acquiring the EIT measurements during a RAMIS procedure using two already existing robotic forceps as electrodes. The robot controls the forceps tips to a series of predefined positions for injecting excitation current and measuring electric potentials. Given the relative positions of electrodes and the measured electric potentials, the spatial distribution of electrical conductivity in a section view can be reconstructed. Realistic experiments are designed and conducted to simulate two tasks: subsurface abnormal tissue detection and surgical margin localization. According to the reconstructed images, the system is demonstrated to display the location of the abnormal tissue and the contrast of the tissues' conductivity with an accuracy suitable for clinical applications.

A disposable force regulation mechanism for throat swab robot.

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 0.6 N constant force within a 20 mm displacement. The nonlinear spring is designed through optimization based on Finite Element Simulation and Genetic Algorithm. Prototype of the mechanism is made and tested. The experimental results show that the mechanism can provide 0.67±0.04 N and 0.57±0.02 N during its compression and return process. The proposed design can be extended to different scales and used in a variety of scenario where safe interacting with human is required.

SmartProbe: a bioimpedance sensing system for head and neck cancer tissue detection.

OBJECTIVES: This study presents SmartProbe, an electrical bioimpedance (EBI) sensing system based on a concentric needle electrode (CNE). The system allows the use of commercial CNEs for accurate EBI measurement, and was specially developed for in-vivo real-time cancer detection. APPROACH: Considering the uncertainties in EBI measurements due to the CNE manufacturing tolerances, we propose a calibration method based on statistical learning. This is done by extracting the correlation between the measured impedance value |Z|, and the material conductivity σ, for a group of reference materials. By utilizing this correlation, the relationship of σ and |Z| can be described as a function and reconstructed using a single measurement on a reference material of known conductivity. MAIN RESULTS: This method simplifies the calibration process, and is verified experimentally. Its effectiveness is demonstrate by results that show less than 6% relative error. An additional experiment is conducted for evaluating the system's capability to detect cancerous tissue. Four types of ex-vivo human tissue from the head and neck region, including mucosa, muscle, cartilage and salivary gland, are characterized using SmartProbe. The measurements include both cancer and surrounding healthy tissue excised from 10 different patients operated on for head and neck cancer. The measured data is then processed using dimension reduction and analyzed for tissue classification. The final results show significant differences between pathologic and healthy tissues in muscle, mucosa and cartilage specimens. SIGNIFICANCE: These results are highly promising and indicate a great potential for SmartProbe to be used in various cancer detection tasks.

Design of a Drop-in EBI Sensor Probe for Abnormal Tissue Detection in Minimally Invasive Surgery.

It is a common challenge for the surgeon to detect pathological tissues and determine the resection margin during a minimally invasive surgery. In this study, we present a drop-in sensor probe based on the electrical bioimpedance spectroscopic technology, which can be grasped by a laparoscopic forceps and controlled by the surgeon to inspect suspicious tissue area conveniently. The probe is designed with an optimized electrode and a suitable shape specifically for Minimally Invasive Surgery (MIS). Subsequently, a series of ex vivo experiments are carried out with porcine liver tissue for feasibility validation. During the experiments, impedance measured at frequencies from 1 kHz to 2 MHz are collected on both normal tissues and water soaked tissue. In addition, classifiers based on discriminant analysis are developed. The result of the experiment indicate that the sensor probe can be used to measure the impedance of the tissue easily and the developed tissue classifier achieved accuracy of 80% and 100% respectively.

Design and Integration of Electrical Bio-impedance Sensing in Surgical Robotic Tools for Tissue Identification and Display.

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. In addition, an advanced user interface is designed to provide guidance during the use of the system and to allow augmented-reality visualization of the tissue identification results. The proposed system imposes minor hardware modifications to an existing surgical tool, but adds the capability to provide a wealth of data about the tissue being manipulated. This has great potential to allow the surgeon (or an autonomous robotic system) to better understand the surgical environment. To evaluate the system, a series of ex-vivo experiments were conducted. The experimental results demonstrate that the proposed sensing system can successfully identify different tissue types with 100% classification accuracy. In addition, the user interface was shown to effectively and intuitively guide the user to measure the electrical impedance of the target tissue, presenting the identification results as augmented-reality markers for simple and immediate recognition.

A New Venous Entry Detection Method Based on Electrical Bio-impedance Sensing.

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. Statistics show that only 53% of first PIVC attempts are successful in pediatric patients. Since their veins are small and readily rupture, multiple attempts are commonly required before successfully inserting the catheter into the vein. This article presents and evaluates a novel venous entry detection method based on measuring the electrical bio-impedance of the contacting tissue at the tip of a concentric electrode needle (CEN). This detection method is then implemented in the design of a clinical device called smart venous entry indicator (SVEI), which lights up a LED to indicate the venous entry when the measured value is within the range of blood. To verify this detection method, two experiments are conducted. In the first experiment, we measured the bio-impedance during the insertion of a CEN into a rat's tail vein with different excitation frequencies. Then three classifiers are tested to discriminate blood from surrounding tissues. The experimental results indicate that with 100 kHz excitation frequency the blood bio-impedance can be identified with accuracy nearly 100%, demonstrating the feasibility and reliability of the proposed method for venous entry detection. The second experiment aims to assess the impact of SVEI on PIVC performance. Ten naive subjects were invited to catheterize a realistic baby arm phantom. The subjects are equally divided into two groups, where one group does PIVC with SVEI and the other group uses an ordinary IV catheter. The results show that subjects using SVEI can achieve much higher success rates (86%) than those performing PIVC in a conventional way (12%). Also, all subjects assisted by SVEI succeeded in their first trials while no one succeed in their first attempt using the conventional unassisted system. These results demonstrate the proposed detection method has great potential to improve pediatric PIVC performance, especially for non-expert clinicians. This supports further investment towards clinical validation of the technology.

A hand-held robotic device for peripheral intravenous catheterization.

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. In this article, we present the design, development and experimental evaluation of a novel hand-held robotic device for improving the process of peripheral intravenous catheterization by facilitating the needle insertion procedure. To our knowledge, this design is the first hand-held robotic device for assisting in the catheterization insertion task. Compared to the other available technologies, it has several unique advantages such as being compact, low-cost and able to reliably detect venipuncture. The system is equipped with an electrical impedance sensor at the tip of the catheterization needle, which provides real-time measurements used to supervise and control the catheter insertion process. This allows the robotic system to precisely position the needle within the lumen of the target vein, leading to enhanced catheterization success rate. Experiments conducted to evaluate the device demonstrated that it is also effective to deskill the task. Naïve subjects achieved an average catheterization success rate of 88% on a 1.5 mm phantom vessel with the robotic device versus 12% with the traditional unassisted system. The results of this work prove the feasibility of a hand-held assistive robotic device for intravenous catheterization and show that such device has the potential to greatly improve the success rate of these difficult operations.