A High-Precision and Miniature Fiber Bragg Grating-Based Force Sensor for Tissue Palpation During Minimally Invasive Surgery

Tissue palpation in endoscopy using EIT and soft actuators

The integration of soft robots in medical procedures has significantly improved diagnostic and therapeutic interventions, addressing safety concerns and enhancing surgeon dexterity. In conjunction with artificial intelligence, these soft robots hold the potential to expedite autonomous interventions, such as tissue palpation for cancer detection. While cameras are prevalent in surgical instruments, situations with obscured views necessitate palpation. This proof-of-concept study investigates the effectiveness of using a soft robot integrated with Electrical Impedance Tomography (EIT) capabilities for tissue palpation in simulated in vivo inspection of the large intestine. The approach involves classifying tissue samples of varying thickness into healthy and cancerous tissues using the shape changes induced on a hydraulically-driven soft continuum robot during palpation. Shape changes of the robot are mapped using EIT, providing arrays of impedance measurements. Following the fabrication of an in-plane bending soft manipulator, the preliminary tissue phantom design is detailed. The phantom, representing the descending colon wall, considers induced stiffness by surrounding tissues based on a mass-spring model. The shape changes of the manipulator, resulting from interactions with tissues of different stiffness, are measured, and EIT measurements are fed into a Long Short-Term Memory (LSTM) classifier. Train and test datasets are collected as temporal sequences of data from a single training phantom and two test phantoms, namely, A and B, possessing distinctive thickness patterns. The collected dataset from phantom B, which differs in stiffness distribution, remains unseen to the network, thus posing challenges to the classifier. The classifier and proposed method achieve an accuracy of 93 % and 88.1 % on phantom A and B, respectively. Classification results are presented through confusion matrices and heat maps, visualising the accuracy of the algorithm and corresponding classified tissues.

An FBG-based optical pressure sensor for the measurement of radial artery pulse pressure

One of the diagnostic tool for clinical evaluation and disease diagnosis is a pulse waveform analysis. High fidelity radial artery pulse waveforms have been investigated in clinical research to compute central aortic pressure, which has been demonstrated to be predictive of cardiovascular diseases. The radial artery must be inspected from several angles in order to obtain the best pulse waveform for estimate and diagnosis. In this study, we present the design and experimental testing of an optical sensor based on Fiber Bragg Gratings (FBG). A 3D printed device along with the FBG is used to measure the radial artery pulses. The proposed sensor is used for the purpose of quantifying the radial artery pulse waveform across major pulse position point. The suggested optical sensing system can measure the pulse signal with good accuracy. The main characteristic parameters of the pulse can then be retrieved from the processed signal for their use in clinical applications. By conducting experiments under the direction of medical experts, the pulse signals are measured. In order to experimentally validate the sensor, we used it to detect the pulse waveforms at Guan position of the wrist's radial artery in accordance with the diagnostic standards. The findings show that combining optical technologies for physiological monitoring and radial artery pulse waveform monitoring using FBG in clinical applications are highly feasible.

A Tension Sensor Array for Cable-Driven Surgical Robots

Tendon-sheath structures are commonly utilized to drive surgical robots due to their compact size, flexibility, and straightforward controllability. However, long-distance cable tension estimation poses a significant challenge due to its frictional characteristics affected by complicated factors. This paper proposes a miniature tension sensor array for an endoscopic cable-driven parallel robot, aiming to integrate sensors into the distal end of long and flexible surgical instruments to sense cable tension and alleviate friction between the tendon and sheath. The sensor array, mounted at the distal end of the robot, boasts the advantages of a small size (16 mm outer diameter) and reduced frictional impact. A force compensation strategy was presented and verified on a platform with a single cable and subsequently implemented on the robot. The robot demonstrated good performance in a series of palpation tests, exhibiting a 0.173 N average error in force estimation and a 0.213 N root-mean-square error. In blind tests, all ten participants were able to differentiate between silicone pads with varying hardness through force feedback provided by a haptic device.

Visualizing tactile feedback: an overview of current technologies with a focus on ultrasound elastography

Tissue elasticity remains an essential biomarker of health and is indicative of irregularities such as tumors or infection. The timely detection of such abnormalities is crucial for the prevention of disease progression and complications that arise from late-stage illnesses. However, at both the bedside and the operating table, there is a distinct lack of tactile feedback for deep-seated tissue. As surgical techniques advance toward remote or minimally invasive options to reduce infection risk and hasten healing time, surgeons lose the ability to manually palpate tissue. Furthermore, palpation of deep structures results in decreased accuracy, with the additional barrier of needing years of experience for adequate confidence of diagnoses. This review delves into the current modalities used to fulfill the clinical need of quantifying physical touch. It covers research efforts involving tactile sensing for remote or minimally invasive surgeries, as well as the potential of ultrasound elastography to further this field with non-invasive real-time imaging of the organ's biomechanical properties. Elastography monitors tissue response to acoustic or mechanical energy and reconstructs an image representative of the elastic profile in the region of interest. This intuitive visualization of tissue elasticity surpasses the tactile information provided by sensors currently used to augment or supplement manual palpation. Focusing on common ultrasound elastography modalities, we evaluate various sensing mechanisms used for measuring tactile information and describe their emerging use in clinical settings where palpation is insufficient or restricted. With the ongoing advancements in ultrasound technology, particularly the emergence of micromachined ultrasound transducers, these devices hold great potential in facilitating early detection of tissue abnormalities and providing an objective measure of patient health.

A Survey on Force Sensing Techniques in Robot-Assisted Minimally Invasive Surgery

Minimally invasive surgery (MIS) is commonly used in some robotic-assisted surgery (RAS) systems. However, many RAS lack the strength and tactile sensation of surgical tools. Therefore, researchers have developed various force sensing techniques in robot-assisted minimally invasive surgery (RMIS). This paper provides a systematic classification and review of force sensing approaches in the field of RMIS, with a particular focus on direct and indirect force sensing. In this survey, the relevant literature on various sensing principles, haptic sensor design standards, and sensing technologies between 2000 and 2022 is reviewed. This survey can also serve as a roadmap for future developments by identifying the shortcomings of the field and discussing the emerging trends in force sensing methods.

Vibro-acoustic sensing of tissue-instrument-interactions allows a differentiation of biological tissue in computerised palpation

BACKGROUND

The shift towards minimally invasive surgery is associated with a significant reduction of tactile information available to the surgeon, with compensation strategies ranging from vision-based techniques to the integration of sensing concepts into surgical instruments. Tactile information is vital for palpation tasks such as the differentiation of tissues or the characterisation of surfaces. This work investigates a new sensing approach to derive palpation-related information from vibration signals originating from instrument-tissue-interactions.

METHODS

We conducted a feasibility study to differentiate three non-animal and three animal tissue specimens based on palpation of the surface. A sensor configuration was mounted at the proximal end of a standard instrument opposite the tissue-interaction point. Vibro-acoustic signals of 1680 palpation events were acquired, and the time-varying spectrum was computed using Continuous-Wavelet-Transformation. For validation, nine spectral energy-related features were calculated for a subsequent classification using linear Support Vector Machine and k-Nearest-Neighbor.

RESULTS

Indicators derived from the vibration signal are highly stable in a set of palpations belonging to the same tissue specimen, regardless of the palpating subject. Differences in the surface texture of the tissue specimens reflect in those indicators and can serve as a basis for differentiation. The classification following a supervised learning approach shows an accuracy of >93.8% for the three-tissue classification tasks and decreases to 78.8% for a combination of all six tissues.

CONCLUSIONS

Simple features derived from the vibro-acoustic signals facilitate the differentiation between biological tissues, showing the potential of the presented approach to provide information related to the interacting tissue. The results encourage further investigation of a yet little-exploited source of information in minimally invasive surgery.

Wearable Microfluidics for Continuous Assay

The development of wearable devices provides approaches for the realization of self-health care. Easily carried wearable devices allow individual health monitoring at any place whenever necessary. There are various interesting monitoring targets, including body motion, organ pressure, and biomarkers. An efficient use of space in one small device is a promising resolution to increase the functions of wearable devices. Through integration of a microfluidic system into wearable devices, embedding complicated structures in one design becomes possible and can enable multifunction analyses within a limited device volume. This article reviews the reported microfluidic wearable devices, introduces applications to different biofluids, discusses characteristics of the design strategies and sensing principles, and highlights the attractive configurations of each device. This review seeks to provide a detailed summary of recent advanced microfluidic wearable devices. The overview of advanced key components is the basis for the development of future microfluidic wearable devices.

Vibro-Acoustic Sensing of Instrument Interactions as a Potential Source of Texture-Related Information in Robotic Palpation

The direct tactile assessment of surface textures during palpation is an essential component of open surgery that is impeded in minimally invasive and robot-assisted surgery. When indirectly palpating with a surgical instrument, the structural vibrations from this interaction contain tactile information that can be extracted and analysed. This study investigates the influence of the parameters contact angle α and velocity v→ on the vibro-acoustic signals from this indirect palpation. A 7-DOF robotic arm, a standard surgical instrument, and a vibration measurement system were used to palpate three different materials with varying α and v→. The signals were processed based on continuous wavelet transformation. They showed material-specific signatures in the time-frequency domain that retained their general characteristic for varying α and v→. Energy-related and statistical features were extracted, and supervised classification was performed, where the testing data comprised only signals acquired with different palpation parameters than for training data. The classifiers support vector machine and k-nearest neighbours provided 99.67% and 96.00% accuracy for the differentiation of the materials. The results indicate the robustness of the features against variations in the palpation parameters. This is a prerequisite for an application in minimally invasive surgery but needs to be confirmed in realistic experiments with biological tissues.

Smart laparoscopic grasper integrated with fiber Bragg grating based tactile sensor for real-time force feedback

Minimally invasive surgery, such as laparoscopic surgery, has developed rapidly due to its small wound, less bleeding and quick recovery. However, a lack of force feedback, which leads to tissue damage, is still unsolved. Many sensors have been used to offer force feedback but still limited by their large size, low security and high complexity. Based on the advantages of small size, high sensitivity and immunity to electromagnetic interferences, we propose a tactile sensor integrated with fiber Bragg gratings (FBGs) at the tip of laparoscopic grasper to offer real-time force feedback in the laparoscopic surgery. The tactile sensor shows a force sensitivity of 0.076 nm/N with a repeatable accuracy of 0.118 N. A bench test is conducted in a laparoscopic training box to verify its feasibility. Test results illustrate that gripping force exerted on the laparoscopic grasper in terms of peak and standard deviation values reduce significantly for the novice subjects with force feedback compared to those without force feedback. The proposed sensor integrated at the tip of the laparoscopic grasper demonstrates a better control of the gripping force among the novice surgeons and indicates that the smart grasper can help surgeons achieve precise gripping force to reduce unnecessary tissue trauma.

Respiratory and heart rate monitoring using an FBG 3D-printed wearable system

This work proposes a 3D-printed sensor based on fiber Bragg grating (FBG) technology for respiratory rate (RR) and heart rate (HR) monitoring. Each sensor is composed of a single FBG fully encapsulated into a 3D-printable Flexible, during the printing process. Sensors with different material thicknesses and infill densities were tested. The sensor with the best metrological properties was selected and preliminary assessed in terms of capability of monitoring RR and HR on three users. Preliminary results proved that the developed sensor can be a valuable easy-to-fabricate solution, with high reproducibility and high strain sensitivity to chest wall deformations due to breathing and heart beating.

A Comprehensive Review on the Optical Micro-Electromechanical Sensors for the Biomedical Application

This study presented an overview of current developments in optical micro-electromechanical systems in biomedical applications. Optical micro-electromechanical system (MEMS) is a particular class of MEMS technology. It combines micro-optics, mechanical elements, and electronics, called the micro-opto electromechanical system (MOEMS). Optical MEMS comprises sensing and influencing optical signals on micron-level by incorporating mechanical, electrical, and optical systems. Optical MEMS devices are widely used in inertial navigation, accelerometers, gyroscope application, and many industrial and biomedical applications. Due to its miniaturised size, insensitivity to electromagnetic interference, affordability, and lightweight characteristic, it can be easily integrated into the human body with a suitable design. This study presented a comprehensive review of 140 research articles published on photonic MEMS in biomedical applications that used the qualitative method to find the recent advancement, challenges, and issues. The paper also identified the critical success factors applied to design the optimum photonic MEMS devices in biomedical applications. With the systematic literature review approach, the results showed that the key design factors could significantly impact design, application, and future scope of work. The literature of this paper suggested that due to the flexibility, accuracy, design factors efficiency of the Fibre Bragg Grating (FBG) sensors, the demand has been increasing for various photonic devices. Except for FBG sensing devices, other sensing systems such as optical ring resonator, Mach-Zehnder interferometer (MZI), and photonic crystals are used, which still show experimental stages in the application of biosensing. Due to the requirement of sophisticated fabrication facilities and integrated systems, it is a tough choice to consider the other photonic system. Miniaturisation of complete FBG device for biomedical applications is the future scope of work. Even though there is a lot of experimental work considered with an FBG sensing system, commercialisation of the final FBG device for a specific application has not been seen noticeable progress in the past.

Force sensing in robot-assisted keyhole endoscopy: A systematic survey

Instrument–tissue interaction forces in minimally invasive surgery (MIS) provide valuable information that can be used to provide haptic perception, monitor tissue trauma, develop training guidelines, and evaluate the skill level of novice and expert surgeons. Force and tactile sensing is lost in many robot-assisted surgery (RAS) systems. Therefore, many researchers have focused on recovering this information through sensing systems and estimation algorithms. This article provides a comprehensive systematic review of the current force sensing research aimed at RAS and, more generally, keyhole endoscopy, in which instruments enter the body through small incisions. Articles published between January 2011 and May 2020 are considered, following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. The literature search resulted in 110 papers on different force estimation algorithms and sensing technologies, sensor design specifications, and fabrication techniques.

Miniaturized optical fiber probe for prostate cancer screening

Tissue elasticity is universally recognized as a diagnostic and prognostic biomarker for prostate cancer. As the first diagnostic test, the digital rectal examination is used since malignancy changes the prostate morphology and affects its mechanical properties. Currently, this examination is performed manually by the physician, with an unsatisfactory positive predictive value of 42%. A more objective and spatially selective technique is expected to provide a better prediction degree and understanding of the disease. To this aim, here we propose a miniaturized probe, based on optical fiber sensor technology, for mechanical characterization of the prostate with sub-millimeter resolution. Specifically, the optical system incorporates a customized Fiber Bragg Grating, judiciously integrated in a metallic cannula and moved by a robotic arm. The probe enables the local measurement of the force upon tissue indentation with a resolution of 0.97 mN. The system has been developed in such a way to be potentially used directly in vivo. Measurements performed on phantom tissues mimicking different stages of the prostatic carcinoma demonstrated the capability of our device to distinguish healthy from diseased zones of the prostate. The study on phantoms has been complemented with preliminary ex vivo experiments on real organs obtained from radical surgeries. Our findings lay the foundation for the development of advanced optical probes that, when integrated inside biopsy needle, are able to perform in vivo direct mechanical measurements with high sensitivity and spatial resolution, opening to new scenarios for early diagnosis and enhanced diagnostic accuracy of prostate cancer.

Sensor Integrated Load-Bearing Structures: Measuring Axis Extension with DIC-Based Transducers

In this paper we present a novel, cost-effective camera-based multi-axis force/torque sensor concept for integration into metallic load-bearing structures. A two-part pattern consisting of a directly incident and mirrored light beam is projected onto the imaging sensor surface. This allows the capturing of 3D displacements, occurring due to structure deformation under load in a single image. The displacement of defined features in size and position can be accurately analyzed and determined through digital image correlation (DIC). Validation on a prototype shows good accuracy of the measurement and a unique identification of all in- and out-of-plane displacement components under multiaxial load. Measurements show a maximum deviation related to the maximum measured values between 2.5% and 4.8% for uniaxial loads (Fx, Fy,Fz,Mz) and between 2.5% and 10.43% for combined bending, torsion and axial load. In the course of the investigations, the measurement inaccuracy was partly attributed to the joint used between the sensor parts and the structure as well as to eccentric load.

Optical Micro/Nanofiber-Enabled Compact Tactile Sensor for Hardness Discrimination

Optical micro/nanofibers (MNFs) can be applied for ultrasensitive tactile sensing with fast response and compact size, which are attractive for restoring tactile information in minimally invasive robotic surgery and tissue palpation. Herein, we present a compact tactile sensor (CTS) with a diameter of 1.5 mm enabled by an optical MNF. The CTS provides continuous readouts for high-fidelity transduction of touch and pressure stimuli into interpretable optical signals, which permit instantaneous sensing of contact and pressure with pressure-sensing sensitivity as high as 0.108 mN^-1 and a resolution of 0.031 mN. Working in pressing mode, the CTS can discriminate the difference in the hardness of two poly(dimethylsiloxane) (PDMS) slats (with shore A of 36 and 40) directly, a hardness resolving ability even beyond the human hands. Benefitting from the fast response feature, the CTS can also be operated in either scanning or tapping mode, making it feasible for hardness identification by analyzing the shape of the response curve. As a proof of concept, the hardness discrimination of a pork liver and an adductor muscle was experimentally demonstrated. Such MNF-enabled compact tactile sensors may pave the way for hardness sensing in tissue palpation, surgical robotics, and object identification.

A tactile sensor using the acoustic reflection principle for assessing the contact force component in laparoscopic tumor localization

PURPOSE

Localization of an early stage gastric tumor is easily performed in conventional open surgery, whereas it is a difficult procedure in minimally invasive surgery (MIS). A tactile sensor could allow precise resection of the tumor in laparoscopic surgery. The safety of medical tools should be ensured in MIS. Moreover, boundary conditions such as a double-ended beam without a supporting rigid base during tissue palpation were hardly considered. Thus, we suppose that it is informative to assess the normal force and shear force for practical tumor detection considering the boundary condition.

METHODS

In this study, a tactile sensor with normal and shear force measurement functions using the acoustic reflection principle was developed for gastric tumor detection in MIS. The developed tactile sensor was tested using an artificial phantom of the stomach without a supporting rigid base to evaluate the force response of the sensor in intraoperative tumor localization.

RESULTS

The developed sensor is safe for human tissue and can be sterilized. The experimental results show that the developed tactile sensor has the capability to measure normal and shear forces. In the gastric tumor detection test, the shear force of the sensor was more stable and highly responsive to the tumor position than the normal force, which is greatly affected by the bending of the tissue during the operation.

CONCLUSIONS

A two-axis tactile sensor using the acoustic reflection principle was assembled for tissue palpation in MIS. The results showed that the developed sensor is suitable for tumor detection, indicating that the shear force information of the developed sensor is more useful in MIS for early stage gastric tumor localization.

A Piezoelectric Tactile Sensor for Tissue Stiffness Detection with Arbitrary Contact Angle

In this paper, a piezoelectric tactile sensor for detecting tissue stiffness in robot-assisted minimally invasive surgery (RMIS) is proposed. It can detect the stiffness not only when the probe is normal to the tissue surface, but also when there is a contact angle between the probe and normal direction. It solves the problem that existing sensors can only detect in the normal direction to ensure accuracy when the degree of freedom (DOF) of surgical instruments is limited. The proposed senor can distinguish samples with different stiffness and recognize lump from normal tissue effectively when the contact angle varies within [0°, 45°]. These are achieved by establishing a new detection model and sensor optimization. It deduces the influence of contact angle on stiffness detection by sensor parameters design and optimization. The detection performance of the sensor is confirmed by simulation and experiment. Five samples with different stiffness (including lump and normal samples with close stiffness) are used. Through blind recognition test in simulation, the recognition rate is 100% when the contact angle is randomly selected within 30°, 94.1% within 45°, which is 38.7% higher than the unoptimized sensor. Through blind classification test and automatic k-means clustering in experiment, the correct rate is 92% when the contact angle is randomly selected within 45°. We can get the proposed sensor can easily recognize samples with different stiffness with high accuracy which has broad application prospects in the medical field.