Real-time haptic characterisation of Hunt-Crossley model based on radial basis function neural network for contact environment

Dynamic soft tissue characterisation is an important element in robotic minimally invasive surgery. This paper presents a novel method by combining neural network with recursive least square (RLS) estimation for dynamic soft tissue characterisation based on the nonlinear Hunt-Crossley (HC) model. It develops a radial basis function neural network (RBFNN) to compensate for the error caused by natural logarithmic factorisation (NLF) of the HC model for dynamic RLS estimation of soft tissue properties. The RBFNN weights are estimated according to the maximum likelihood principle to evaluate the probability distribution of the neural network modelling residual. Further, by using the linearisation error modelled by RBFNN to compensate for the linearised HC model, an RBFNN-based RLS algorithm is developed for dynamic soft tissue characterisation. Simulation and experimental results demonstrate that the proposed method can effectively model the natural logarithmic linearisation error, leading to improved accuracy for RLS estimation of the HC model parameters.

Curving expectations: The minimal impact of structural curvature in biological puncture mechanics

Living organisms have evolved various biological puncture tools, such as fangs, stingers, and claws, for prey capture, defense, and other critical biological functions. These tools exhibit diverse morphologies, including a wide range of structural curvatures, from straight cactus spines to crescent-shaped talons found in raptors. While the influence of such curvature on the strength of the tool has been explored, its biomechanical role in puncture performance remains untested. Here, we investigate the effect of curvature on puncture mechanics by integrating experiments with finite element simulations. Our findings reveal that within a wide biologically relevant range, structural curvature has a minimal impact on key metrics of damage initiation or the energies required for deep penetration in isotropic and homogeneous target materials. This unexpected result improves our understanding of the biomechanical pressures driving the morphological diversity of curved puncture tools and provides fundamental insights into the crucial roles of curvature in the biomechanical functions of living puncture systems.

Hip-Knee Motion-Lagged Coordination Mapping Enables Speed Adaptive Walking for Powered Knee Prosthesis

The commonly used finite-state-machine (FSM) impedance control for powered prostheses deploys diverse control parameters according to different gait phases, resulting in dozens of parameter adjustments and possible gait phase misrecognition. In contrast, this study presents a straightforward, continuous, and speed-adaptive control approach based on hip-knee motion-lagged coordination mapping (MLCM). The mapping, featured by the motion lag, can effectively generate the prosthetic knee's goal gait within a second-order polynomial. It is also verified from extensive gait analysis that the motion lag and polynomial coefficients evolve linearly with respect to walking speed and gait period, promising a simple real-time deployment for prosthesis control. Experimental validation with two non-disabled subjects and two transfemoral amputees wearing a prosthesis demonstrates the MLCM controller's ability to reduce the hip compensatory behavior, generate biomimetic knee kinematics, stance phase time, stride length, and hip-knee motion coordination across various speeds. Furthermore, compared to the benchmark FSM impedance controller, the MLCM controller reduces the number of control parameters from 17 to 7 and avoids misrecognition during gait phase transitions.

A method for predicting needle insertion deflection in soft tissue based on cutting force identification

The deflection modeling during the insertion of bevel-tipped flexible needles into soft tissues is crucial for robot-assisted flexible needle insertion into specific target locations within the human body during percutaneous biopsy surgery. This paper proposes a mechanical model based on cutting force identification to predict the deflection of flexible needles in soft tissues. Unlike other models, this method does not require measuring Young's modulus (E ) and Poisson's ratio (ν ) of tissues, which require complex hardware to obtain. In the model, the needle puncture process is discretized into a series of uniform-depth puncture steps. The needle is simplified as a cantilever beam supported by a series of virtual springs, and the influence of tissue stiffness on needle deformation is represented by the spring stiffness coefficient of the virtual spring. By theoretical modeling and experimental parameter identification of cutting force, the spring stiffness coefficients are obtained, thereby modeling the deflection of the needle. To verify the accuracy of the proposed model, the predicted model results were compared with the deflection of the puncture experiment in polyvinyl alcohol (PVA) gel samples, and the average maximum error range predicted by the model was between 0.606 ± 0.167 mm and 1.005 ± 0.174 mm, which showed that the model can successfully predict the deflection of the needle. This work will contribute to the design of automatic control strategies for needles.

Biomechanical Comparison of Novel Adaptive Swing-Phase Control Mechanical Knee Prostheses with 3R60 and 3R15 in Trans-Femoral Amputees

Background

The knee joint must adapt to the changes in walking speed to stabilize the stance phase and provide fluency in the swing phase.

Objective

This study aimed to report a comparison of the gait patterns of transfemoral amputees using a novel mechanical prosthetic knee that can adapt automatically to different walking speeds with 3R60 and 3R15 knee prostheses.

Material and Methods

In this experimental study, biomechanical data were collected from six unilateral trans-femoral amputees walking with three knee prostheses. Gait data were gathered at slow, normal, and fast walking speeds across a 7-meter walkway using the Vicon motion system.

Results

The results revealed a significant difference in knee angular velocity during the swing phase between prosthetic knees across three walking speeds (P-value=0.002). Prosthetic knee flexion decreased significantly by increasing walking speed for the novel mechanical auto-adaptive prosthetic knee (P-value<0.001). A lower value of hip power during early swing was considered when amputees walked with novel knee prosthesis (P-value<0.00). The intact leg ankle plantar flexion angle or vaulting did not significantly change while walking speed increased in the novel knee prostheses compared to walking with the 3R60 and 3R15 knee prostheses (P-value=0.002 and P-value<0.06, respectively).

Conclusion

Based on the results, a novel mechanical auto-adaptive knee prosthesis has advantages compared to the other conventional designs for unilateral trans-femoral amputees walking at different speeds.

Biomimetic Closed-Loop Control of a Novel Soft Gastric Simulator Toward Emulating Antral Contraction Waves

Soft gastric simulators are in vitro biomimetic modules that can reproduce the antral contraction waves (ACWs). Along with providing information concerning stomach contents, stomach simulators enable experts to evaluate the digestion process of foods and drugs. Traditionally, open-loop control approaches were implemented on stomach simulators to produce ACWs. Constructing a closed-loop control system is essential to improve the simulator's ability to imitate ACWs in additional scenarios and avoid constant tuning. Closed-loop control can enhance stomach simulators in accuracy, responding to various food and drug contents, timing, and unknown disturbances. In this article, a new generation of anatomically realistic soft pneumatic gastric simulators is designed and fabricated. The presented simulator represents the antrum, the lower portion of the stomach where ACWs occur. It is equipped with a real-time feedback system to implement diverse closed-loop controllers on demand. All the details of the physical design, fabrication, and assembly process are discussed. Also, the measures taken for the mechatronics design and sensory system are highlighted in this article. Through several implementation algorithms and techniques, three closed-loop controllers, including model-based and model-free schemes are designed and successfully applied on the presented simulator to imitate ACWs. All the experimental outcomes are carefully analyzed and compared against the biological counterparts. It is demonstrated that the presented simulator can serve as a reliable tool and method to scrutinize digestion and promote novel technologies around the human stomach and the digestion process. This research methodology can also be utilized to develop other biomimetic and bioinspired applications.

The protagonist of contemporary and emerging nanotechnology-based theranostics and therapeutic approaches in reshaping intensive care unit

To maintain a clean and hygienic environment in the intensive care unit (ICU) is crucial for ensuring patient safety, preventing infections, and reducing healthcare-associated complications. With the increasing prevalence of infections and the emergence of viral and bacterial resistance to standard antiseptics, there is a pressing need for innovative antiseptic solutions. Nanotechnology is increasingly being employed in medicine, particularly focusing on mitigating the activities of various pathogens, including those associated with hospital-acquired infections. This paper explores the current impact of nanotechnology, with a particular focus on bacterial infections and SARS-CoV-2, which significantly strain healthcare systems, and then discusses how nanotechnology can enhance existing treatment methodologies. We highlight the effectiveness of the nanotechnology-based bactericide Bio-Kil in reducing bacterial counts in an ICU. The aim is to educate healthcare professionals on the existing role and prospects of nanotechnology in addressing prevalent infectious diseases.

A Survey of Autonomous Vehicle Behaviors: Trajectory Planning Algorithms, Sensed Collision Risks, and User Expectations

Autonomous vehicles are rapidly advancing and have the potential to revolutionize transportation in the future. This paper primarily focuses on vehicle motion trajectory planning algorithms, examining the methods for estimating collision risks based on sensed environmental information and approaches for achieving user-aligned trajectory planning results. It investigates the different categories of planning algorithms within the scope of local trajectory planning applications for autonomous driving, discussing and differentiating their properties in detail through a review of the recent studies. The risk estimation methods are classified and introduced based on their descriptions of the sensed collision risks in traffic environments and their integration with trajectory planning algorithms. Additionally, various user experience-oriented methods, which utilize human data to enhance the trajectory planning performance and generate human-like trajectories, are explored. The paper provides comparative analyses of these algorithms and methods from different perspectives, revealing the interconnections between these topics. The current challenges and future prospects of the trajectory planning tasks in autonomous vehicles are also discussed.

A comprehensive review on modeling aspects of infusion-based drug delivery in the brain

Brain disorders represent an ever-increasing health challenge worldwide. While conventional drug therapies are less effective due to the presence of the blood-brain barrier, infusion-based methods of drug delivery to the brain represent a promising option. Since these methods are mechanically controlled and involve multiple physical phases ranging from the neural and molecular scales to the brain scale, highly efficient and precise delivery procedures can significantly benefit from a comprehensive understanding of drug-brain and device-brain interactions. Behind these interactions are principles of biophysics and biomechanics that can be described and captured using mathematical models. Although biomechanics and biophysics have received considerable attention, a comprehensive mechanistic model for modeling infusion-based drug delivery in the brain has yet to be developed. Therefore, this article reviews the state-of-the-art mechanistic studies that can support the development of next-generation models for infusion-based brain drug delivery from the perspective of fluid mechanics, solid mechanics, and mathematical modeling. The supporting techniques and database are also summarized to provide further insights. Finally, the challenges are highlighted and perspectives on future research directions are provided. STATEMENT OF SIGNIFICANCE: Despite the immense potential of infusion-based drug delivery methods for bypassing the blood-brain barrier and efficiently delivering drugs to the brain, achieving optimal drug distribution remains a significant challenge. This is primarily due to our limited understanding of the complex interactions between drugs and the brain that are governed by principles of biophysics and biomechanics, and can be described using mathematical models. This article provides a comprehensive review of state-of-the-art mechanistic studies that can help to unravel the mechanism of drug transport in the brain across the scales, which underpins the development of next-generation models for infusion-based brain drug delivery. More broadly, this review will serve as a starting point for developing more effective treatments for brain diseases and mechanistic models that can be used to study other soft tissue and biomaterials.

Multifunctional Hydrogel with 3D Printability, Fluorescence, Biodegradability, and Biocompatibility for Biomedical Microrobots

As micron-sized objects, mobile microrobots have shown significant potential for future biomedical applications, such as targeted drug delivery and minimally invasive surgery. However, to make these microrobots viable for clinical applications, several crucial aspects should be implemented, including customizability, motion-controllability, imageability, biodegradability, and biocompatibility. Developing materials to meet these requirements is of utmost importance. Here, a gelatin methacryloyl (GelMA) and (2-(4-vinylphenyl)ethene-1,1,2-triyl)tribenzene (TPEMA)-based multifunctional hydrogel with 3D printability, fluorescence imageability, biodegradability, and biocompatibility is demonstrated. By using 3D direct laser writing method, the hydrogel exhibits its versatility in the customization and fabrication of 3D microstructures. Spherical hydrogel microrobots were fabricated and decorated with magnetic nanoparticles on their surface to render them magnetically responsive, and have demonstrated excellent movement performance and motion controllability. The hydrogel microstructures also represented excellent drug loading/release capacity and degradability by using collagenase, along with stable fluorescence properties. Moreover, cytotoxicity assays showed that the hydrogel was non-toxic, as well as able to support cell attachment and growth, indicating excellent biocompatibility of the hydrogel. The developed multifunctional hydrogel exhibits great potential for biomedical microrobots that are integrated with customizability, 3D printability, motion controllability, drug delivery capacity, fluorescence imageability, degradability, and biocompatibility, thus being able to realize the real in vivo biomedical applications of microrobots.

Advances in bacteria-based drug delivery systems for anti-tumor therapy

In recent years, bacteria have gained considerable attention as a promising drug carrier that is critical in improving the effectiveness and reducing the side effects of anti-tumor drugs. Drug carriers can be utilised in various forms, including magnetotactic bacteria, bacterial biohybrids, minicells, bacterial ghosts and bacterial spores. Additionally, functionalised and engineered bacteria obtained through gene engineering and surface modification could provide enhanced capabilities for drug delivery. This review summarises the current studies on bacteria-based drug delivery systems for anti-tumor therapy and discusses the prospects and challenges of bacteria as drug carriers. Furthermore, our findings aim to provide new directions and guidance for the research on bacteria-based drug systems.

Immune Cell-Based Microrobots for Remote Magnetic Actuation, Antitumor Activity, and Medical Imaging

Translating medical microrobots into clinics requires tracking, localization, and performing assigned medical tasks at target locations, which can only happen when appropriate design, actuation mechanisms, and medical imaging systems are integrated into a single microrobot. Despite this, these parameters are not fully considered when designing macrophage-based microrobots. This study presents living macrophage-based microrobots that combine macrophages with magnetic Janus particles coated with FePt nanofilm for magnetic steering and medical imaging and bacterial lipopolysaccharides for stimulating macrophages in a tumor-killing state. The macrophage-based microrobots combine wireless magnetic actuation, tracking with medical imaging techniques, and antitumor abilities. These microrobots are imaged under magnetic resonance imaging and optoacoustic imaging in soft-tissue-mimicking phantoms and ex vivo conditions. Magnetic actuation and real-time imaging of microrobots are demonstrated under static and physiologically relevant flow conditions using optoacoustic imaging. Further, macrophage-based microrobots are magnetically steered toward urinary bladder tumor spheroids and imaged with a handheld optoacoustic device, where the microrobots significantly reduce the viability of tumor spheroids. The proposed approach demonstrates the proof-of-concept feasibility of integrating macrophage-based microrobots into clinic imaging modalities for cancer targeting and intervention, and can also be implemented for various other medical applications.

Improving Workers' Musculoskeletal Health During Human-Robot Collaboration Through Reinforcement Learning

OBJECTIVE

This study aims to improve workers' postures and thus reduce the risk of musculoskeletal disorders in human-robot collaboration by developing a novel model-free reinforcement learning method.

BACKGROUND

Human-robot collaboration has been a flourishing work configuration in recent years. Yet, it could lead to work-related musculoskeletal disorders if the collaborative tasks result in awkward postures for workers.

METHODS

The proposed approach follows two steps: first, a 3D human skeleton reconstruction method was adopted to calculate workers' continuous awkward posture (CAP) score; second, an online gradient-based reinforcement learning algorithm was designed to dynamically improve workers' CAP score by adjusting the positions and orientations of the robot end effector.

RESULTS

In an empirical experiment, the proposed approach can significantly improve the CAP scores of the participants during a human-robot collaboration task when compared with the scenarios where robot and participants worked together at a fixed position or at the individual elbow height. The questionnaire outcomes also showed that the working posture resulted from the proposed approach was preferred by the participants.

CONCLUSION

The proposed model-free reinforcement learning method can learn the optimal worker postures without the need for specific biomechanical models. The data-driven nature of this method can make it adaptive to provide personalized optimal work posture.

APPLICATION

The proposed method can be applied to improve the occupational safety in robot-implemented factories. Specifically, the personalized robot working positions and orientations can proactively reduce exposure to awkward postures that increase the risk of musculoskeletal disorders. The algorithm can also reactively protect workers by reducing the workload in specific joints.

Design and Control of the Magnetically Actuated Micro/Nanorobot Swarm toward Biomedical Applications

Recently, magnetically actuated micro/nanorobots hold extensive promises in biomedical applications due to their advantages of noninvasiveness, fuel-free operation, and programmable nature. While effectively promised in various fields such as targeted delivery, most past investigations are mainly displayed in magnetic control of individual micro/nanorobots. Facing practical medical use, the micro/nanorobots are required for the development of swarm control in a closed-loop control manner. This review outlines the recent developments in magnetic micro/nanorobot swarms, including their actuating fundamentals, designs, controls, and biomedical applications. The fundamental principles and interactions involved in the formation of magnetic micro/nanorobot swarms are discussed first. The recent advances in the design of artificial and biohybrid micro/nanorobot swarms, along with the control devices and methods used for swarm manipulation, are presented. Furthermore, biomedical applications that have the potential to achieve clinical application are introduced, such as imaging-guided therapy, targeted delivery, embolization, and biofilm eradication. By addressing the potential challenges discussed toward the end of this review, magnetic micro/nanorobot swarms hold promise for clinical treatments in the future.

A Survey of Needle Steering Approaches in Minimally Invasive Surgery

In virtue of a curved insertion path inside tissues, needle steering techniques have revealed the potential with the assistance of medical robots and images. The superiority of this technique has been preliminarily verified with several maneuvers: target realignment, obstacle circumvention, and multi-target access. However, the momentum of needle steering approaches in the past decade leads to an open question-"How to choose an applicable needle steering approach for a specific clinical application?" This survey discusses this question in terms of design choices and clinical considerations, respectively. In view of design choices, this survey proposes a hierarchical taxonomy of current needle steering approaches. Needle steering approaches of different manipulations and designs are classified to systematically review the design choices and their influences on clinical treatments. In view of clinical consideration, this survey discusses the steerability and acceptability of the current needle steering approaches. On this basis, the pros and cons of the current needle steering approaches are weighed and their suitable applications are summarized. At last, this survey concluded with an outlook of the needle steering techniques, including the potential clinical applications and future developments in mechanical design.

Development of a continuum manipulator with variable bending length and piecewise stiffness for transoral laryngeal surgery

PURPOSE

Continuum manipulators (CMs) show great potential in transoral laryngeal surgery due to their flexibility. However, CMs for transoral surgery face several issues: large size, which reduces practicality; intersegment coupling, which causes undesired deflection; and a lack of versatility that limits their applicability across different patient groups.

METHODS

This work combines a rod-driven proximal segment and a cable-driven distal segment to achieve piecewise stiffness, alleviating the issue of intersegment coupling. A rigid constraint tube is integrated into the proximal segment to diversify its bending behavior. Preliminary experiments are conducted to validate the design concept.

RESULTS

The proposed CM has an overall diameter of only 6.5 mm. The proximal segment can achieve a 90° bending with various curvatures. At the working configuration, the coupling error between the proximal segment and the distal segment is less than 1 mm. The effectiveness of the proposed CM is successfully validated using a human model.

CONCLUSION

The proposed continuum manipulator possesses the desirable characteristics of small size, low coupling, and high versatility, indicating its great potentialities for the diagnosis and treatment of laryngeal lesion.

Experimental Study of the Implantation Process for Array Electrodes into Highly Transparent Agarose Gel

Brain-computer interface (BCI) technology is currently a cutting-edge exploratory problem in the field of human-computer interaction. However, in experiments involving the implantation of electrodes into brain tissue, particularly high-speed or array implants, existing technologies find it challenging to observe the damage in real time. Considering the difficulties in obtaining biological brain tissue and the challenges associated with real-time observation of damage during the implantation process, we have prepared a transparent agarose gel that closely mimics the mechanical properties of biological brain tissue for use in electrode implantation experiments. Subsequently, we developed an experimental setup for synchronized observation of the electrode implantation process, utilizing the Digital Gradient Sensing (DGS) method. In the single electrode implantation experiments, with the increase in implantation speed, the implantation load increases progressively, and the tissue damage region around the electrode tip gradually diminishes. In the array electrode implantation experiments, compared to a single electrode, the degree of tissue indentation is more severe due to the coupling effect between adjacent electrodes. As the array spacing increases, the coupling effect gradually diminishes. The experimental results indicate that appropriately increasing the velocity and array spacing of the electrodes can enhance the likelihood of successful implantation. The research findings of this article provide valuable guidance for the damage assessment and selection of implantation parameters during the process of electrode implantation into real brain tissue.

The Effect of Asset Degradation on Trust in Swarms: A Reexamination of System-Wide Trust in Human-Swarm Interaction

OBJECTIVE

The effects of asset degradation on trust in human-swarm interaction were investigated through the lens of system-wide trust theory.

BACKGROUND

Researchers have begun investigating contextual features that shape human interactions with robotic swarms-systems comprising assets that coordinate behavior based on their nearest neighbors. Recent work has begun investigating how human trust toward swarms is affected by asset degradation through the lens of system-wide trust theory, but these studies have been marked by several limitations.

METHOD

In an online study, the current work manipulated asset degradation and measured trust-relevant criteria in a within-subjects design and addressed the limitations of past work.

RESULTS

Controlling for swarm performance (i.e., target acquisition), asset degradation and trust (i.e., reliance intentions) in swarms were negatively related. In addition, as degradation increased, perceptions of swarm cohesion, obstacle avoidance, target acquisition, and terrain exploration efficiency decreased, the latter two of which (coupled with the reliance intentions criterion) support the tenets of system-wide trust theory as well as replicate and extend past work on the effects of asset degradation on trust in swarms.

CONCLUSION

Human-swarm interaction is a context in which system-wide trust is relevant, and future work ought to investigate how to calibrate human trust toward swarm systems.

APPLICATIONS

Based on these findings, design professionals should prioritize ways to depict swarm performance and system health such that humans do not abandon trust in systems that are still functional yet not over-trust those systems which are indeed performing poorly.

A Review of Recent Advancements in Sensor-Integrated Medical Tools

A medical tool is a general instrument intended for use in the prevention, diagnosis, and treatment of diseases in humans or other animals. Nowadays, sensors are widely employed in medical tools to analyze or quantify disease-related parameters for the diagnosis and monitoring of patients' diseases. Recent explosive advancements in sensor technologies have extended the integration and application of sensors in medical tools by providing more versatile in vivo sensing capabilities. These unique sensing capabilities, especially for medical tools for surgery or medical treatment, are getting more attention owing to the rapid growth of minimally invasive surgery. In this review, recent advancements in sensor-integrated medical tools are presented, and their necessity, use, and examples are comprehensively introduced. Specifically, medical tools often utilized for medical surgery or treatment, for example, medical needles, catheters, robotic surgery, sutures, endoscopes, and tubes, are covered, and in-depth discussions about the working mechanism used for each sensor-integrated medical tool are provided.

A comprehensive dataset on biomechanics and motor control during human walking with discrete mechanical perturbations

Background

Humans have a remarkable capability to maintain balance while walking. There is, however, a lack of publicly available research data on reactive responses to destabilizing perturbations during gait.

Methods

Here, we share a comprehensive dataset collected from 10 participants who experienced random perturbations while walking on an instrumented treadmill. Each participant performed six 5-min walking trials at a rate of 1.2 m/s, during which rapid belt speed perturbations could occur during the participant's stance phase. Each gait cycle had a 17% probability of being perturbed. The perturbations consisted of an increase of belt speed by 0.75 m/s, delivered with equal probability at 10%, 20%, 30%, 40%, 50%, 60%, 70%, or 80% of the stance phase. Data were recorded using motion capture with 25 markers, eight inertial measurement units (IMUs), and electromyography (EMG) from the tibialis anterior (TA), soleus (SOL), lateral gastrocnemius (LG), rectus femoris (RF), vastus lateralis (VL), vastus medialis (VM), biceps femoris (BF), and gluteus maximus (GM). The full protocol is described in detail.

Results

We provide marker trajectories, force plate data, EMG data, and belt speed information for all trials and participants. IMU data is provided for most participants. This data can be useful for identifying neural feedback control in human gait, biologically inspired control systems for robots, and the development of clinical applications.

Concurrent Optimizations of Efficacy and Blood-Brain Barrier Permeability in New Macrocyclic LRRK2 Inhibitors for Potential Parkinson's Disease Therapeutics

The elevated activity of leucine-rich repeat kinase 2 (LRRK2) is implicated in the pathogenesis of Parkinson's disease (PD). The quest for effective LRRK2 inhibitors has been impeded by the formidable challenge of crossing the blood-brain barrier (BBB). We leveraged structure-based de novo design and developed robust three-dimensional quantitative structure-activity relationship (3D-QSAR) models to predict BBB permeability, enhancing the likelihood of the inhibitor's brain accessibility. Our strategy involved the synthesis of macrocyclic molecules by linking the two terminal nitrogen atoms of HG-10-102-01 with an alkyl chain ranging from 2 to 4 units, laying the groundwork for innovative LRRK2 inhibitor designs. Through meticulous computational and synthetic optimization of both biochemical efficacy and BBB permeability, 9 out of 14 synthesized candidates demonstrated potent low-nanomolar inhibition and significant BBB penetration. Further assessments of in vitro and in vivo effectiveness, coupled with pharmacological profiling, highlighted 8 as the promising new lead compound for PD therapeutics.

Model-based trajectory tracking of a compliant continuum robot

Introduction: Compliant mechanisms, especially continuum robots, are becoming integral to advancements in minimally invasive surgery due to their ability to autonomously navigate natural pathways, significantly reducing collision severity. A major challenge lies in developing an effective control strategy to accurately reflect their behavior for enhanced operational precision. Methods: This study examines the trajectory tracking capabilities of a tendon-driven continuum robot at its tip. We introduce a novel feedforward control methodology that leverages a mathematical model based on Cosserat rod theory. To mitigate the computational challenges inherent in such models, we implement an implicit time discretization strategy. This approach simplifies the governing equations into space-domain ordinary differential equations, facilitating real-time computational efficiency. The control strategy is devised to enable the robot tip to follow a dynamically prescribed trajectory in two dimensions. Results: The efficacy of the proposed control method was validated through experimental tests on six different demand trajectories, with a motion capture system employed to assess positional accuracy. The findings indicate that the robot can track trajectories with an accuracy within 9.5%, showcasing consistent repeatability across different runs. Discussion: The results from this study mark a significant step towards establishing an efficient and precise control methodology for compliant continuum robots. The demonstrated accuracy and repeatability of the control approach significantly enhance the potential of these robots in minimally invasive surgical applications, paving the way for further research and development in this field.

Swing-phase detection of locomotive mode transitions for smooth multi-functional robotic lower-limb prosthesis control

Robotic lower-limb prostheses, with their actively powered joints, may significantly improve amputee users' mobility and enable them to obtain healthy-like gait in various modes of locomotion in daily life. However, timely recognition of the amputee users' locomotive mode and mode transition still remains a major challenge in robotic lower-limb prosthesis control. In the paper, the authors present a new multi-dimensional dynamic time warping (mDTW)-based intent recognizer to provide high-accuracy recognition of the locomotion mode/mode transition sufficiently early in the swing phase, such that the prosthesis' joint-level motion controller can operate in the correct locomotive mode and assist the user to complete the desired (and often power-demanding) motion in the stance phase. To support the intent recognizer development, the authors conducted a multi-modal gait data collection study to obtain the related sensor signal data in various modes of locomotion. The collected data were then segmented into individual cycles, generating the templates used in the mDTW classifier. Considering the large number of sensor signals available, we conducted feature selection to identify the most useful sensor signals as the input to the mDTW classifier. We also augmented the standard mDTW algorithm with a voting mechanism to make full use of the data generated from the multiple subjects. To validate the proposed intent recognizer, we characterized its performance using the data cumulated at different percentages of progression into the gait cycle (starting from the beginning of the swing phase). It was shown that the mDTW classifier was able to recognize three locomotive mode/mode transitions (walking, walking to stair climbing, and walking to stair descending) with 99.08% accuracy at 30% progression into the gait cycle, well before the stance phase starts. With its high performance, low computational load, and easy personalization (through individual template generation), the proposed mDTW intent recognizer may become a highly useful building block of a prosthesis control system to facilitate the robotic prostheses' real-world use among lower-limb amputees.

Design of composite puncture blood collection system and research on puncture force

Venous blood collection testing is one of the most commonly used medical diagnostic methods. Compared with conventional venous blood collection, robotic collection can reduce needle-stick injuries, medical staff workload, and infection risk; allow doctor-patient isolation; and improve collection reliability. Existing venous blood collection robots use rigid puncture needles, which can easily puncture the lower wall of blood vessels, causing vessel damage and collection failure. This paper proposes a bionic blood collection strategy based on a composite puncture needle that mimics the structure and function of mosquito mouthparts. A bionic composite puncture needle insertion system with puncture-force sensing was designed, and venipuncture forces were simulated and mathematically modelled. A prototype insertion system was built and used in an experiment, which demonstrated effective composite puncture blood collection and explored the factors influencing puncture force. Puncture force decreases with increased puncture speed and angle and with a decreased needle diameter. This provides a basis for optimising the parameters of blood collection robots.

Effect of Magnetic Resonance Imaging on the Motion Accuracy of Magnetic Resonance Imaging-compatible Focused Ultrasound Robotic System

Purpose

The current study provides insights into the challenges of safely operating a magnetic resonance imaging (MRI)-guided focused ultrasound (MRgFUS) robotic system in a high-field MRI scanner in terms of robotic motion accuracy.

Materials and Methods

Grid sonications were carried out in phantoms and excised porcine tissue in a 3T MRI scanner using an existing MRgFUS robotic system. Fast low-angle shot-based magnetic resonance thermometry was employed for the intraprocedural monitoring of thermal distribution.

Results

Strong shifting of the heated spots from the intended points was observed owing to electromagnetic interference (EMI)-induced malfunctions in system's operation. Increasing the slice thickness of the thermometry sequence to at least 8 mm was proven an efficient method for preserving the robotic motion accuracy.

Conclusions

These findings raise awareness about EMI effects on the motion accuracy of MRgFUS robotic devices and how they can be mitigated by employing suitable thermometry parameters.

Geometric stochastic ray propagation using the special Euclidean group

This paper describes a stochastic model of ray trajectory propagation through a medium-such as the ocean-which has an uncertain sound speed profile. We frame ray propagation as a geometric fractal Brownian motion process on the special Euclidean group of dimension two, SE(2). The framing includes diffusion parameters to describe how the stochastic rays deviate from the expected rays, and these diffusion parameters are a function of the uncertainty in the sound speed profile. We demonstrate this framing for the classical Munk profile and a double-ducted profile in the Beaufort.

Motor neurons generate pose-targeted movements via proprioceptive sculpting

Motor neurons are the final common pathway1 through which the brain controls movement of the body, forming the basic elements from which all movement is composed. Yet how a single motor neuron contributes to control during natural movement remains unclear. Here we anatomically and functionally characterize the individual roles of the motor neurons that control head movement in the fly, Drosophila melanogaster. Counterintuitively, we find that activity in a single motor neuron rotates the head in different directions, depending on the starting posture of the head, such that the head converges towards a pose determined by the identity of the stimulated motor neuron. A feedback model predicts that this convergent behaviour results from motor neuron drive interacting with proprioceptive feedback. We identify and genetically2 suppress a single class of proprioceptive neuron3 that changes the motor neuron-induced convergence as predicted by the feedback model. These data suggest a framework for how the brain controls movements: instead of directly generating movement in a given direction by activating a fixed set of motor neurons, the brain controls movements by adding bias to a continuing proprioceptive-motor loop.

In-Silico Analysis of Optimal Configurations for Rotational Bioinspired Bone Marrow Biopsy Needle Designs: An ANN Approach

Medical needle innovations have utilized rotating motion to enhance tissue-cutting capabilities, reducing cutting force and improving clinical outcomes. This study analyzes the effects of six essential factors on insertion and extraction forces during bone marrow biopsy (BMB) procedures. The study uses Taguchi's L32 orthogonal array and numerically simulates the BMB process using the Lagrangian surface-based method on a three-dimensional (3D) heterogeneous Finite Element (FE) model of the human iliac crest. The study evaluates cutting forces in needle insertion and extraction using uni-directional (360° rotation) and bidirectional (180° clock and anti-clock rotation) bioinspired BMB needles. This work aims to create an AI tool that assists researchers and clinicians in selecting the most suitable and safe design parameters for a bio-inspired barbed biopsy needle. An efficient Graphical User Interface (GUI) has been developed for easy use and seamless interaction with the AI tool. With a remarkable accuracy rate exceeding 98%, the tool's predictions hold significant value in facilitating the development of environmentally conscious biopsy needles. The tool demonstrates significantly higher efficiency compared to Abaqus, rendering it a valuable asset for researchers and clinicians engaged in bio-inspired biopsy needle development.

Adaptive Online Learning and Robust 3-D Shape Servoing of Continuum and Soft Robots in Unstructured Environments

In this article, we present a novel and generic data-driven method to servo-control the 3-D shape of continuum and soft robots based on proprioceptive sensing feedback. Developments of 3-D shape perception and control technologies are crucial for continuum and soft robots to perform tasks autonomously in surgical interventions. However, owing to the nonlinear properties of continuum robots, one main difficulty lies in the modeling of them, especially for soft robots with variable stiffness. To address this problem, we propose a versatile learning-based adaptive shape controller by leveraging proprioception of 3-D configuration from fiber Bragg grating (FBG) sensors, which can online estimate the unknown model of continuum robot against unexpected disturbances and exhibit an adaptive behavior to the unmodeled system without priori data exploration. Based on a new composite adaptation algorithm, the asymptotic convergences of the closed-loop system with learning parameters have been proven by Lyapunov theory. To validate the proposed method, we present a comprehensive experimental study using two continuum and soft robots both integrated with multicore FBGs, including a robotic-assisted colonoscope and multisection extensible soft manipulators. The results demonstrate the feasibility, adaptability, and superiority of our controller in various unstructured environments, as well as phantom experiments.

A mechanics-based model for a tendon-driven active needle navigating inside a multiple-layer tissue

Percutaneous minimally invasive procedures such brachytherapy and biopsy require a flexible active needle for precise movement inside tissue and accurate placement at target positions for higher success rates for diagnosis and treatment, respectively. In a previous work, we presented a tendon-driven active needle to navigate inside tissue. This work presents a new model to predict the deflection of the tendon-driven needle while steering in a multiple-layer soft tissue. A multi-layer phantom tissue with different localized stiffness was developed for needle insertion tests followed by indentation tests to identify its mechanical properties. Using a robot that inserts and actively bends the tendon-driven needle inside the soft tissue while simultaneously tracking the needle through ultrasound imaging, various experiments were conducted for model validation. The proposed model was verified by comparing the simulation results to the empirical data. The results demonstrated the accuracy of the model in predicting the tendon-driven needle deflection in multiple-layer (different stiffness) soft tissue.

Mimicking Motor Proteins: Wall-Guided Self-Navigation of Microwheels

Untethered micro/nanorobots (MNRs) show great promise in biomedicine. However, high-precision targeted in vivo navigation of MNRs into both deep and tiny microtube networks comes with big challenges because the present medical imaging cannot simultaneously meet the requirements of high resolution, high penetration depth, and high real-time performance. Inspired by intracellular motor proteins that transport cargo along cytoskeletal tracks, this study proposed a microtube inwall-guided targeted self-navigation strategy of magnetic microwheels (μ-wheels) that relies only on interactions with a microtube inwall, compared to conventional techniques that rely on real-time imaging and tracking of MNRs. By presetting the direction of the rotating magnetic field, the μ-wheel realized targeted navigation along the inwall. The propulsion principles behind it are elaborated. The targeted self-navigation of the μ-wheels in three-dimensional microtube networks, a spiral microtube, and an intrahepatic bile duct of a pig was conducted. Lastly, based on the strategy, a practical tumor early detection method was proposed and verified by means of magnetic resonance imaging. The microtube inwall-guided targeted self-navigation strategy reduces the dependence of in vivo targeted navigation of MNRs on the real-time performance of medical imaging technology and greatly contributes to the development of MNRs in biomedical applications.

Expanding FTMap for Fragment-Based Identification of Pharmacophore Regions in Ligand Binding Sites

The knowledge of ligand binding hot spots and of the important interactions within such hot spots is crucial for the design of lead compounds in the early stages of structure-based drug discovery. The computational solvent mapping server FTMap can reliably identify binding hot spots as consensus clusters, free energy minima that bind a variety of organic probe molecules. However, in its current implementation, FTMap provides limited information on regions within the hot spots that tend to interact with specific pharmacophoric features of potential ligands. E-FTMap is a new server that expands on the original FTMap protocol. E-FTMap uses 119 organic probes, rather than the 16 in the original FTMap, to exhaustively map binding sites, and identifies pharmacophore features as atomic consensus sites where similar chemical groups bind. We validate E-FTMap against a set of 109 experimentally derived structures of fragment-lead pairs, finding that highly ranked pharmacophore features overlap with the corresponding atoms in both fragments and lead compounds. Additionally, comparisons of mapping results to ensembles of bound ligands reveal that pharmacophores generated with E-FTMap tend to sample highly conserved protein-ligand interactions. E-FTMap is available as a web server at https://eftmap.bu.edu.

Exploring the Evolution of Robotic Surgery in Obstetrics and Gynecology: Past, Present, and Future Perspectives

Robotic surgery has emerged as a transformative technology in obstetrics and gynecology, offering enhanced precision and minimally invasive techniques for various procedures. This paper explores the evolution of robotic surgery in obstetrics and gynecology, examining its historical development, current applications, and prospects. Through a comprehensive review of the literature and case studies, we highlight the benefits of robotic surgery, including reduced trauma, improved patient outcomes, and increased surgeon capabilities. However, cost, training requirements, and regulatory concerns hinder widespread adoption. Continuing technological innovation is expected to enhance the efficacy and applicability of robotic-assisted procedures. Collaboration between healthcare professionals, researchers, and industry stakeholders is essential to address these challenges and ensure optimal patient care. By embracing the opportunities presented by robotic surgery while addressing associated challenges, practitioners and researchers can contribute to the continued advancement of this transformative technology in obstetrics and gynecology.

Between Meanings and Senses-Making Spaces: Agency and Ownership Emergence Formalization from Cultural-Historical Activity Theory Position, for an AI-Friendly Model

Sense of agency and sense of ownership are considered crucial in autonomous systems. However, drawbacks still exist regarding how to represent their causal origin and internal structure, either in formalized psychological models or in artificial systems. This paper considers that these drawbacks are based on the ontological and epistemological duality in mainstream psychology and AI. By shedding light on the cultural-historical activity theory (CHAT) and dialectical logic, and by building on and extending related work, this paper attempts to investigate how the noted duality affects investigating the self and "I". And by differentiating between the space of meanings and the sense-making space, the paper introduces CHAT's position of the causal emergence of agency and ownership by stressing the twofold transition theory being central to CHAT. Furthermore, a qualitative formalized model is introduced to represent the emergence of agency and ownership through the emergence of the contradictions-based meaning with potential employment in AI.

Scalable musculoskeletal model for dynamic simulations of upper body movement

A musculoskeletal (MSK) model is a valuable tool for assessing complex biomechanical problems, estimating joint torques during motion, optimizing motion in sports, and designing exoskeletons and prostheses. This study proposes an open-source upper body MSK model that supports biomechanical analysis of human motion. The MSK model of the upper body consists of 8 body segments (torso, head, left/right upper arm, left/right forearm, and left/right hand). The model has 20 degrees of freedom (DoFs) and 40 muscle torque generators (MTGs), which are constructed using experimental data. The model is adjustable for different anthropometric measurements and subject body characteristics: sex, age, body mass, height, dominant side, and physical activity. Joint limits are modeled using experimental dynamometer data within the proposed multi-DoF MTG model. The model equations are verified by simulating the joint range of motion (ROM) and torque; all simulation results have a good agreement with previously published research.

Robotic system for nasopharyngeal swab sampling based on remote center of motion mechanism

PURPOSE

In this study, a robotic system is proposed for nasopharyngeal (NP) swab sampling with high safety and efficiency. Most existing swab-sampling robots have more than six degrees of freedom (DOFs). However, not all six DOFs are necessarily required for NP swab sampling. A high number of DOFs can cause safety problems, such as collisions between the robot and patient.

METHOD

We developed a new type of robot with four DOFs for NP swab sampling that consists of a two DOFs remote center of motion (RCM) mechanism, a two DOFs insertion mechanism, and a nostril support unit. With the nostril support unit, the robot no longer needs to adjust the insertion position of the swab. The proposed robot enables the insertion orientation and depth to be adjusted according to different postures or facial shapes of the subject. For intuitive and precise remote control of the robot, a dedicated master device for the RCM and a visual feedback system were developed.

RESULT

The effectiveness of the robotic system was demonstrated by repeatability, RCM accuracy, tracking accuracy, and in vitro phantom experiments. The average tracking error between the master device and the robot was less than 2 mm. The contact force exerted on the swab prior to reaching the nasopharynx was less than 0.04 N, irrespective of the phantom's pose.

CONCLUSION

This study confirmed that the RCM-based robotic system is effective and safe for NP swab sampling while using minimal DOFs.

Tracking and navigation of a microswarm under laser speckle contrast imaging for targeted delivery

Micro/nanorobotic swarms consisting of numerous tiny building blocks show great potential in biomedical applications because of their collective active delivery ability, enhanced imaging contrast, and environment-adaptive capability. However, in vivo real-time imaging and tracking of micro/nanorobotic swarms remain a challenge, considering the limited imaging size and spatial-temporal resolution of current imaging modalities. Here, we propose a strategy that enables real-time tracking and navigation of a microswarm in stagnant and flowing blood environments by using laser speckle contrast imaging (LSCI), featuring full-field imaging, high temporal-spatial resolution, and noninvasiveness. The change in dynamic convection induced by the microswarm can be quantitatively investigated by analyzing the perfusion unit (PU) distribution, offering an alternative approach to investigate the swarm behavior and its interaction with various blood environments. Both the microswarm and surrounding environment were monitored and imaged by LSCI in real time, and the images were further analyzed for simultaneous swarm tracking and navigation in the complex vascular system. Moreover, our strategy realized real-time tracking and delivery of a microswarm in vivo, showing promising potential for LSCI-guided active delivery of microswarm in the vascular system.

A survey on puncture models and path planning algorithms of bevel-tipped flexible needles

Percutaneous needle insertion is a minimally invasive surgery with broad medical application prospects, such as biopsy and brachytherapy. However, the currently adopted rigid needles have limitations, as they cannot bypass obstacles or correct puncture deviations and can only travel along a straight path. Bevel-tip flexible needles are increasingly being adopted to address these issues, owing to their needle body's ease of deformation and bending. Successful puncture of flexible needles relies on accurate models and path planning, ensuring the needle reaches the target while avoiding vital tissues. This review investigates puncture models and path-planning algorithms by reviewing recent literature, focusing on the path-planning part. According to the literature, puncture models can be divided into three types: mechanical, finite element method (FEM), and kinematic models, while path-planning algorithms are categorized and discussed following the division used for mobile robots, which differs from the conventional approach for flexible needles-an innovation in this review. This review systematically summarizes the following categories: graph theory search, sampling-based, intelligent search, local obstacle avoidance, and other algorithms, including their implementation, advantages, and disadvantages, to further explore the potential to overcome obstacles in path planning for minimally invasive puncture needles. Finally, this study proposes future development trends in path-planning algorithms, providing possible directions for subsequent research for bevel-tipped flexible needles. This research aims to provide a resource for researchers to quickly learn about common path-planning algorithms, their backgrounds, and puncture models.

A Model to Predict Deflection of an Active Tendon-Driven Notched Needle Inside Soft Tissue

The last decade has witnessed major progress in the field of minimally invasive and robotic-assisted surgeries. Needle insertion, a minimally invasive technique, has proven its efficacy in procedures such as brachytherapy, ablation, drug delivery, and biopsy. Manual needle steering inside tissue is a challenging task due to complex needle-tissue interactions, needle and tissue movement, lack of actuation and control, as well as poor sensing and visualization. Recently, active tendon-driven notched needles, and robotic manipulation systems have been proposed to assist surgeons to guide the needles in desired trajectories toward target positions. This work introduces a new deflection model for the active tendon-driven notched needle steering inside soft tissue for intention to use in model-based robotic control. The model is developed to predict needle deflection in a single-layer tissue. To validate the proposed deflection model, five sets of needle insertion experiments with a bevel-tipped active needle into single-layer phantom tissues were performed. A real-time robot-assisted ultrasound tracking method was used to track the needle tip during needle insertion. It was shown that the model predicts needle deflection with an average error of 0.58 ± 0.14 mm for the bevel-tipped active needle insertion into a single-layer phantom tissue.

Renin and renin blockade have no role in complement activity

Renin, an aspartate protease, regulates the renin-angiotensin system by cleaving its only known substrate angiotensinogen to angiotensin. Recent studies have suggested that renin may also cleave complement component C3 to activate complement or contribute to its dysregulation. Typically, C3 is cleaved by C3 convertase, a serine protease that uses the hydroxyl group of a serine residue as a nucleophile. Here, we provide seven lines of evidence to show that renin does not cleave C3. First, there is no association between renin plasma levels and C3 levels in patients with C3 Glomerulopathies (C3G) and atypical Hemolytic Uremic Syndrome (aHUS), implying that serum C3 consumption is not increased in the presence of high renin. Second, in vitro tests of C3 conversion to C3b do not detect differences when sera from patients with high renin levels are compared to sera from patients with normal/low renin levels. Third, aliskiren, a renin inhibitor, does not block abnormal complement activity introduced by nephritic factors in the fluid phase. Fourth, aliskiren does not block dysregulated complement activity on cell surfaces. Fifth, recombinant renin from different sources does not cleave C3 even after 24 hours of incubation at 37 °C. Sixth, direct spiking of recombinant renin into sera samples of patients with C3G and aHUS does not enhance complement activity in either the fluid phase or on cell surfaces. And seventh, molecular modeling and docking place C3 in the active site of renin in a position that is not consistent with a productive ground state complex for catalytic hydrolysis. Thus, our study does not support a role for renin in the activation of complement.

Design, Characterization, and Preliminary Assessment of a Two-Degree-of-Freedom Powered Ankle-Foot Prosthesis

Powered ankle prostheses have been proven to improve the walking economy of people with transtibial amputation. All commercial powered ankle prostheses that are currently available can only perform one-degree-of-freedom motion in a limited range. However, studies have shown that the frontal plane motion during ambulation is associated with balancing. In addition, as more advanced neural interfaces have become available for people with amputation, it is possible to fully recover ankle function by combining neural signals and a robotic ankle. Accordingly, there is a need for a powered ankle prosthesis that can have active control on not only plantarflexion and dorsiflexion but also eversion and inversion. We designed, built, and evaluated a two-degree-of-freedom (2-DoF) powered ankle-foot prosthesis that is untethered and can support level-ground walking. Benchtop tests were conducted to characterize the dynamics of the system. Walking trials were performed with a 77 kg subject that has unilateral transtibial amputation to evaluate system performance under realistic conditions. Benchtop tests demonstrated a step response rise time of less than 50 milliseconds for a torque of 40 N·m on each actuator. The closed-loop torque bandwidth of the actuator is 9.74 Hz. Walking trials demonstrated torque tracking errors (root mean square) of less than 7 N·m. These results suggested that the device can perform adequate torque control and support level-ground walking. This prosthesis can serve as a platform for studying biomechanics related to balance and has the possibility of further recovering the biological function of the ankle-subtalar-foot complex beyond the existing powered ankles.

Effects of a Powered Ankle-Foot Prosthesis and Physical Therapy on Function for Individuals With Transfemoral Limb Loss: Rationale, Design, and Protocol for a Multisite Clinical Trial

BACKGROUND

Powered ankle-foot prosthetic devices can generate net positive mechanical work during gait, which mimics the physiological ankle. However, gait deviations can persist in individuals with transfemoral limb loss because of habit or lack of rehabilitation. Prosthetic research efforts favor the design or evaluation of prosthetic componentry and rarely incorporate any type of rehabilitation, despite evidence suggesting that it is critical for minimizing gait imbalances. Given the accelerated rate of innovation in prosthetics, there is a fundamental knowledge gap concerning how individuals with transfemoral limb loss should learn to correctly use powered ankle-foot devices for maximum functional benefit. Because of the recent advances in prosthetic technology, there is also a critical unmet need to develop guidelines for the prescription of advanced prosthetic devices that incorporate both physical and psychological components to identify appropriate candidates for advanced technology.

OBJECTIVE

The primary goal of this investigation is to examine the roles of advanced prosthetic technology and a device-specific rehabilitative intervention on gait biomechanics, functional efficacy, and pain in individuals with transfemoral limb loss. The secondary goal is to develop preliminary rehabilitation guidelines for advanced lower limb prosthetic devices to minimize gait imbalances and maximize function and to establish preliminary guidelines for powered ankle-foot prosthetic prescription.

METHODS

This prospective, multisite study will enroll 30 individuals with unilateral transfemoral limb loss. At baseline, participants will undergo a full gait analysis and assessment of function, neurocognition, cognitive load, subjective preferences, and pain using their current passive prosthesis. The participants will then be fitted with a powered ankle-foot device and randomized into 2 equal groups: a powered device with a device-specific rehabilitation intervention (group A) or a powered device with the current standard of practice (group B). Group A will undergo 4 weeks of device-specific rehabilitation. Group B will receive the current standard of practice, which includes basic device education but no further device-specific rehabilitation. Data collection procedures will then be repeated after 4 weeks and 8 weeks of powered ankle use.

RESULTS

This study was funded in September 2017. Enrollment began in September 2018. Data collection will conclude by March 2024. The initial dissemination of results is expected in August 2024.

CONCLUSIONS

The projected trends indicate that the number of individuals with limb loss will dramatically increase in the United States. The absence of effective, evidence-based interventions may make individuals with transfemoral limb loss more susceptible to increased secondary physical conditions and degenerative changes. With this expected growth, considerable resources will be required for prosthetic and rehabilitation services. Identifying potential mechanisms for correcting gait asymmetries, either through advanced prosthetic technology or rehabilitative interventions, can provide a benchmark for understanding the optimal treatment strategies for individuals with transfemoral limb loss.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03625921; https://clinicaltrials.gov/study/NCT03625921.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/53412.

Machine Learning-Assisted Computational Screening of Adhesive Molecules Derived from Dihydroxyphenyl Alanine

Marine mussels adhere to virtually any surface via 3,4-dihydroxyphenyl-L-alanines (L-DOPA), an amino acid largely contained in their foot proteins. The biofriendly, water-repellent, and strong adhesion of L-DOPA are unparalleled by any synthetic adhesive. Inspired by this, we computationally designed diverse derivatives of DOPA and studied their potential as adhesives or coating materials. We used first-principles calculations to investigate the adsorption of the DOPA derivatives on graphite. The presence of an electron-withdrawing group, such as nitrogen dioxide, strengthens the adsorption by increasing the π-π interaction between DOPA and graphite. To quantify the distribution of electron charge and to gain insights into the charge distribution at interfaces, we performed Bader charge analysis and examined charge density difference plots. We developed a quantitative structure-property relationship (QSPR) model using an artificial neural network (ANN) to predict the adsorption energy. Using the three-dimensional and quantum mechanical electrostatic potential of a molecule as a descriptor, the present quantum NN model shows promising performance as a predictive QSPR model.

Model-free control for autonomous prevention of adverse events in robotics

Introduction: Preventive control is a critical feature in autonomous technology to ensure safe system operations. One application where safety is most important is robot-assisted needle interventions. During incisions into a tissue, adverse events such as mechanical buckling of the needle shaft and tissue displacements can occur on encounter with stiff membranes causing potential damage to the organ. Methods: To prevent these events before they occur, we propose a new control subroutine that autonomously chooses a) a reactive mechanism to stop the insertion procedure when a needle buckling or a severe tissue displacement event is predicted and b) an adaptive mechanism to continue the insertion procedure through needle steering control when a mild tissue displacement is detected. The subroutine is developed using a model-free control technique due to the nonlinearities of the unknown needle-tissue dynamics. First, an improved version of the model-free adaptive control (IMFAC) is developed by computing a fast time-varying partial pseudo derivative analytically from the dynamic linearization equation to enhance output convergence and robustness against external disturbances. Results and Discussion: Comparing IMFAC and MFAC algorithms on simulated nonlinear systems in MATLAB, IMFAC shows 20% faster output convergence against arbitrary disturbances. Next, IMFAC is integrated with event prediction algorithms from prior work to prevent adverse events during needle insertions in real time. Needle insertions in gelatin tissues with known environments show successful prevention of needle buckling and tissue displacement events. Needle insertions in biological tissues with unknown environments are performed using live fluoroscopic imaging as ground truth to verify timely prevention of adverse events. Finally, statistical ANOVA analysis on all insertion data shows the robustness of the prevention algorithm to various needles and tissue environments. Overall, the success rate of preventing adverse events in needle insertions through adaptive and reactive control was 95%, which is important toward achieving safety in robotic needle interventions.

Diffuse domain approach for flexible needle insertion and relaxation

Needle insertion simulations play an important role in medical training and surgical planning. Most simulations require boundary conforming meshes, while the diffuse domain approach, currently limited to stiff needles, eliminates the need for meshing geometries. In this article the diffuse domain approach for needle insertion simulations is first extended to the use of flexible needles with bevel needle tips, which are represented by an Euler-Bernoulli beam. The model parameters are tuned and the model is evaluated on a real-world phantom experiment. Second, a new method for the relaxation of the needle-tissue system after the user releases the needle is introduced. The equilibrium state of the system is determined by minimizing the potential energy. The convergence rate of the coupled Laplace equations for solving the Euler-Bernoulli beam is 1.92 ± 0.14 for decreasing cell size. The diffuse penalty method for the application of Dirichlet boundary conditions results in a convergence rate of 0.73 ± 0.21 for decreasing phase field width. The simulated needle deviates on average by 0.29 mm compared to the phantom experiment. The error of the tissue deformation is below 1 mm for 97.5% of the attached markers. Two additional experiments demonstrate the feasibility of the relaxation process. The simulation method presented here is a valuable tool for patient-specific medical simulations using flexible needles without the need for boundary conforming meshing. To the best of the authors' knowledge this is the first work to introduce a relaxation model, which is a major step for simulating accurate needle-tissue positioning during realistic medical interventions.

A review on tissue-needle interaction and path planning models for bevel tip type flexible needle minimal intervention

A flexible needle has emerged as a crucial clinical technique in contemporary medical practices, particularly for minimally invasive interventions. Its applicability spans diverse surgical domains such as brachytherapy, cardiovascular surgery, neurosurgery and others. Notably, flexible needles find utility in biopsies requiring deep skin penetration to access infected areas. Despite its minimally invasive advantages, the precise guidance of the needle to its intended target, while avoiding damage to bones, blood vessels, organs and tissues, remains a significant challenge for researchers. Consequently, extensive research has been dedicated to enhancing the steering and accuracy of flexible needles. Here, we aim to elucidate the recent advancements, trends and perspectives in flexible needle steering models and path planning over the last 15 years. The discussed models encompass various types, including symmetric-tip needles, curved-tip needles, tendon-actuated needles, programmable needles and the innovative fracture-directed waterjet needles. Moreover, the paper offers a comprehensive analysis, comparing the trajectories followed by these needle models to attain the desired target with minimal tissue damage. By delving into these aspects, the paper contributes to a deeper understanding of the current landscape of flexible needle technology and guides future research directions in this dynamic field.

Human Robot Collaboration for Enhancing Work Activities

OBJECTIVE

Trade-offs between productivity, physical workload (PWL), and mental workload (MWL) were studied when integrating collaborative robots (cobots) into existing manual work by optimizing the allocation of tasks.

BACKGROUND

As cobots become more widely introduced in the workplace and their capabilities greatly improved, there is a need to consider how they can best help their human partners.

METHODS

A theoretical data-driven analysis was conducted using the O*NET Content Model to evaluate 16 selected jobs for associated work context, skills, and constraints. Associated work activities were ranked by potential for substitution by a cobot. PWL and MWL were estimated using variables from the O*Net database that represent variables for the Strain Index and NASA-TLX. An algorithm was developed to optimize work activity assignment to cobots and human workers according to their most suited abilities.

RESULTS

Human workload for some jobs decreased while workload for some jobs increased after cobots were reassigned tasks, and residual human capacity was used to perform job activities designated the most important to increase productivity. The human workload for other jobs remained unchanged.

CONCLUSIONS

The changes in human workload from the introduction of cobots may not always be beneficial for the human worker unless trade-offs are considered.Application: The framework of this study may be applied to existing jobs to identify the relationship between productivity and worker tolerances that integrate cobots into specific tasks.

Architectural design and development of an upper-limb rehabilitation device: a modular synthesis approach

PURPOSE

Enormous assistance is required during rehabilitation activities, which might result in a variety of complications if performed manually. To solve this issue, several solutions in the form of assistive devices have been presented recently. Another issue highlighted is the lack of kinematic compatibility in low degrees-of-freedom (dof) systems. The proposed approach of developing a human-motion-oriented rehabilitation device deals with the problem through hybrid architectures. A novel modular synthesis approach is used for the purpose to induce generality in the design process.

MATERIALS AND METHODS

Using a modular strategy, three planar hybrid configurations are generated for two-dof mechanisms for supporting flexion/extension motion. Three such architectures are optimally synthesised and kinematically analysed over the entire workspace. A Genetic Algorithm (GA) is used to synthesise the architecture parameters optimally. Moreover, the outcomes are evaluated against a set of seven poses and posture locations of the wrist to choose the most suitable configuration among the others. Subsequently, kinematic compatibility is analysed for the coupled system - formed by the selected architecture and the human arm - while wearing the proposed mechanism.

RESULTS

According to the findings of optimal synthesis, workspace and singularity analysis, configuration-III is capable of achieving the optimal postures for all task space locations (TSLs). Further, the work modifies the design by attaching additional three revolute passive joints for correcting misalignment concerns using coupled mobility analysis.

CONCLUSION

The modular strategy for hybrid architectures and the subsequent mobility analysis provides an algorithmic framework for synthesising a task-based rehabilitation device.IMPLICATIONS OF REHABILITATIONManual physiotherapy is reported as repeated task, expensive and time-consuming, and considered stressful for the therapist or assistants to provide one-on-one physiotherapy to each patient in the traditional method. Robotic rehabilitation is, therefore, a viable option.In the several reported works on robotic rehabilitation exoskeletons, misalignment of the exoskeleton and the human motion is considered an open challenge. Normally, it is being managed through large number of degrees of freedom, which is certainly expensive and complex in control. The proposed approach of developing a human-motion-oriented rehabilitation device deals with the problem through hybrid architectures and modular strategy to develop them.While focusing upon the emulation of natural human motion trajectory, the compatibility of orthotic joint and human joint motion needs attention. As biological joint possesses complex kinematic characteristics, closed-loops are used in the design.Overall, a complete framework of a cost effective low-dof rehabilitation device is proposed and detailed through coupled analysis.

Robotics in Screening, Diagnosis and Treatment of Breast Cancer: A Perspective View

This perspective article aims to summarize and provide an outlook for developments around the use of robotics in the screening, diagnosis and treatment of breast cancer. We searched existing literature on the design and development of new systems and the current use of pre-existing surgical robotic systems. Robotic interventions for breast palpation and biopsy under ultrasound and MRI guidance are being developed and tested on simulated breast phantoms. Results are comparable to those achieved by clinicians; however, there are yet to be any human trials. Existing robotic surgical systems have been evaluated in human trials to perform nipple-sparing mastectomy and harvesting of autologous tissue for breast reconstruction. Results are comparable to traditional NSM and demonstrate positive short-term outcomes for patients. Robotic devices could revolutionize the clinical workflow around breast cancer through less invasive surgery, greater accuracy in biopsies and microsurgery and a potential reduction in clinicians' workload. However, more research into the practical deployment of these devices and concrete scientific evidence of better patient outcomes is needed.