Design and Evaluation of Laparoscopic Forceps with Accurate Force Feedback

Interaction model between elastic objects for haptic feedback considering collisions of soft tissue

Mantis is a highly scalable system architecture that democratizes haptic devices by enabling designers to create accurate, multiform and accessible force feedback systems. Mantis uses brushless DC motors, custom electronic controllers, and an admittance control scheme to achieve stable high-quality haptic rendering. It enables common desktop form factors but also: large workspaces (multiple arm lengths), multiple arm workspaces, and mobile workspaces. It also uses accessible components and costs significantly less than typical high-fidelity force feedback solutions which are often confined to research labs. We present our design and show that Mantis can reproduce the haptic fidelity of common robotic arms. We demonstrate its multiform ability by implementing five systems: a single desktop-sized device, a single large workspace device, a large workspace system with four points of feedback, a mobile system and a wearable one.

This paper presents the control of a pneumatically actuated master–slave system intended for teleoperated needle insertion in the liver under magnetic resonance imaging (MRI) guidance. It addresses the challenge of achieving accurate needle positioning and force feedback to the operator in the case of pneumatic actuation with significant friction. Using time-delay position control as the basis, we investigate force feedback via impedance control and admittance control. For impedance control, we propose a new adaptive friction compensation algorithm that only requires a single tuning parameter. Experiments on a 1-degree of freedom prototype system using silicone rubber phantoms with distinct densities highlight the differences between impedance control and admittance control, and demonstrate superior performance compared with a traditional impedance control scheme.

Percutaneous medical procedures rely upon clinicians performing precise needle insertion in soft tissue. The utility of haptic simulation systems in training clinicians for these procedures is highly dependent upon the ability to render accurate insertion force feedback. This paper presents a piecewise mathematical model for insertion force that does not require tissue material properties, detailed mechanical approximations, or complex computations. With manipulation of model parameters, a wide variety of insertion tasks and clinical scenarios can be modeled. Through needle insertion experiments and parameter estimation, this model was demonstrated to replicate the insertion forces associated with a variety of needle and tissue types. In 11 of 12 needle and tissue combinations tested, the model replicated the insertion force with an average absolute mean error of less than 0.065 N.

Robot-assisted minimally invasive surgery (MIS) offers several advantages over traditional surgery, including reduced trauma and faster recovery times, leading to its increasingly widespread application. In robot-assisted MIS, the direct contact between surgical instruments and the patient's tissues demands higher precision in movement and enhanced sensing capabilities. This paper focuses on investigating the critical technologies of time delay and gripping force feedback in laparoscopic surgery robot. We propose an actuators-driven surgical robot equipped with gripping force feedback. An experimental system was constructed and control parameters were optimized to achieve ± 180° rotation and 0-60° gripping freedom in primary-secondary control. The experimental measurements indicated that the time delay of the primary-secondary robotic system was maintained at approximately 10ms. To evaluate the gripping force feedback, three different materials-silicone simulated skin, silicone rubber, and ceramic-were used to simulate human tissue, tumors, and bones, respectively. Sensor measurements of the gripping force feedback revealed that the force required to grip ceramic was twice that needed for gripping the silicone rubber and four times that for gripping the silicone simulated skin. The proposed actuators-driven surgical robot system demonstrates precise primary-secondary synchronous control and accurate gripping force feedback, offering significant potential for the further development of advanced surgical systems.

Smooth haptic force feedback is an important task for multirate 6-DOF haptic rendering for both rigid and deformable objects. The update rate of the haptic force may be too low and changed during the simulation as the high computation time is required for complex physical simulation. Therefore, to implement a stable and smooth haptic rendering, we need a method to update the force in a higher regular rate during the physical simulation. We propose a prediction method using interpolation to calculate smooth haptic interaction force in a high update rate. The auto-regressive model is used to predict the force value based on the previous haptic force calculation. In addition, we introduce a spline function to interpolate force values for the haptic force output. We demonstrate that the proposed method can provide smooth and accurate haptic force feedback in a high update rate during a low frequency physical simulation of complex and deformable models. In the experiments, we show the feasibility of the proposed method and compare its accuracy and stability with the linear force prediction algorithm.

Due to the limited force feedback provided by laparoscopic instruments, surgeons may have difficulty in applying the appropriate force on the tissue. The aim of this study was to determine the influence of force feedback and visual feedback on the exerted pinch force. A grasper with a force sensor in the jaws was developed. Subjects with and without laparoscopic experience grasped and pulled pig bowel with a force of 5 N. The applied pinch force was measured during tasks of 1-s and 1-min duration. Visual feedback was provided in half the measurements. Force feedback was adjusted by changing the mechanical efficiency of the forceps from 30% to 90%. The mean pinch force applied was 6.8 N (+/-0.5), whereas the force to prevent slippage was 3.0 N (+/-0.4). Improving the mechanical efficiency had no effect on the pinch force for the 1-s measurements. The amount of excessive pinch force when holding tissue for 1 min was lower at 30% mechanical efficiency compared with 90% (105% vs 131%, p = 0.04). The tissue slipped more often when the subject had no visual feedback (2% vs 8%, p = 0.02). Force feedback and visual feedback play a more limited role than expected in the task of grasping tissue with laparoscopic forceps.

Suboptimal quality of type 2 diabetes care discovered through electronic feedback led to increased nurse–GP cooperation. A qualitative study

Data compression plays a significant role in Body Sensor Networks (BSN). This is true since the sensors in BSNs have limited battery power and memory; sensor data needs to be transmitted regularly, and in lossless manner to provide prompt, accurate feedback. The paper evaluates lossless data compression algorithms including Run Length Encoding (RLE), Lempel Zev Welch (LZW), and Huffman on data from wearable devices and compares them in terms of Compression Ratio, Compression Factor, Savings Percentage and Compression Time. It also evaluates a data deduplication technique used for Low Bandwidth File Systems (LBFS), Two Thresholds Two Divisors (TTTD) algorithm, to determine if it is suitable for BSN data. First, through experiments s we arrive at a set of parameter values that give compression ratio above 50 on BSN data. Next, based on performance evaluation results of TTTD and classical compression algorithms including RLW, LAW, and Huffman, it proposes a technique to combine multiple algorithms in sequence. Upon comparison of the performance, it is found that the new algorithm, TTTD-H, which executes TTTD and Huffman in sequence, significantly improves the compression factor against both TTTD and Huffman. Performance evaluation has been carried out in two sets of BSN data.

Multi-source micro-friction identification for a class of cable-driven robots with passive backbone

IMU- based Determination of Stance Duration During Sprinting

The study utilized 401 data points categorized into upper, middle, and lower levels. The model development process included five stages: 1) data purification and preprocessing, 2) embedding, 3) data segmentation and shape conversion, 4) model training, and 5) model performance evaluation. The research employed BERT, a pre-trained model, to develop the grading model. Performance evaluation of the trained model yielded an accuracy of 0.7377, precision of 0.6514, recall of 0.7377, and an F1 score of 0.6717. These results demonstrate a relatively high level of performance compared to previous studies on scoring Korean written and essay answers by L1 learners. As a result, the feasibility of developing an automatic scoring model using the BERT language model with small-scale data from a specific domain. Also, the model’s performance shows some generalizability, but further exploration is needed for improvement. Limitations of the study include the use of writing samples graded without considering grade levels, limited test data, difficulties in processing unregistered tokens, and the inherent unexplainability of deep learning techniques. Further discussions and considerations on how to more effectively utilize artificial intelligence in Korean language education should continue. Ongoing research on automatic grading is necessary to provide accurate and detailed educational feedback to students. As automatic grading research in the field of Korean language education advances, it is expected that high-quality educational interventions for students will become possible in the future.

Objective: This study sought to assess the impact of a novel electronic audit and feedback (e-A&F) system on patient outcomes. Methods: The e-A&F intervention was implemented in a tertiary hospital and involved near real-time feedback via web-based dashboards. We used a segmented regression analysis of interrupted time series. We modelled the pre-post change in outcomes for the (1) announcement of this priority list, and (2) implementation of the e-A&F intervention to have affected patient outcomes. Results: Across the study period there were 222,792 episodes of inpatient care, of which 13,904 episodes were found to contain one or more HACs, a risk of 6.24%. From the point of the first intervention until the end of the study the overall risk of a HAC reduced from 8.57% to 4.12% - a 51.93% reduction. Of this reduction the proportion attributed to each of these interventions was found to be 29.99% for the announcement of the priority list and 21.93% for the implementation of the e-A&F intervention. Discussion: Our findings lend evidence to a mechanism that the announcement of a measurement framework, at a national level, can lead to local strategies, such as e-A&F, that lead to significant continued improvements over time.

A new class of high-energy batteries, the molten air battery, is presented. These batteries use a molten electrolyte, are quasi-reversible (rechargeable), and have amongst the highest intrinsic battery storage capacities available.In today’s society there exists a need for higher energy capacity, cost effective batteries for a range of electronic, transportation and large-scale power storage devices. The molten air battery overcomes these problems. For example, these batteries address the “range anxiety” of electric vehicles as a result of energy density limitations, and offer increased energy storage capacity for the electric grid.The electron charge transfer chemistry of the molten air battery is demonstrated through three examples. These examples utilize metal, carbon and vanadium diboride as reactive material each containing the respective intrinsic volumetric energy capacities of 10,000 Wh liter-1 for Fe to Fe(III), 19,000 Wh liter-1 for C to CO2 - and 27,000 Wh liter-1 for VB2 to B2O3 + V2O5, compared to 6,200 Wh liter-1 for the lithium air battery.

Purpose: Growing demands placed upon healthcare systems require more health professionals to be trained. Clinical placement education is an integral component of health professional training, however accommodating increasing numbers of student placements is a challenge for health services. Personal digital assistants such as iPads™ may assist in delivery of clinical education, by facilitating transfer of knowledge and skills from clinical educators to health professional students, however such an initiative has not been formally investigated. The present study sought to explore perceptions of clinical educators and allied health students regarding the impact of an iPad™-based feedback delivery system on student reflection and learning. Methods: A pilot study was performed using iPads™ with specialised software to deliver electronic formative feedback to physiotherapy, occupational therapy and speech pathology students during clinical placements. Students and clinical educators completed a questionnaire exploring advantages and disadvantages of the technology. Results: Nine clinical educators and 14 students participated and completed the survey. Clinical educators largely (n=7, 78%) reported the electronic feedback system was easy to use and 67% (n=6) reported it improved the quality of feedback provided to students. Five (56%) clinical educators thought electronic feedback improved student performance. Most students (n=10, 71%) reported electronic feedback facilitated reflection upon performance, and 64% (n=9) reported improved performance as a result. Disadvantages included poor wireless internet access and software inefficiencies (n=7 [78%] clinical educators, n=7 [50%] students), and difficulties using iPads™ in settings requiring infection control (n=2 [22%] clinical educators). Conclusions: Clinical educators and students perceived electronic feedback as a positive adjunct to student learning on clinical placement, however technological and software interface factors need to be considered for implementation in some settings.