Robotic Assistance Research Articles

Robotic-assisted total knee arthroplasty reduces soft-tissue releases which improves functional outcomes: A retrospective study

BackgroundThere is increasing use of Robotic-Assisted (RA) and personalized alignment techniques in total knee arthroplasty (TKA). The hypothesis of this study was that RA TKA would result in fewer soft-tissue releases, and that fewer soft-tissue releases would be associated with improved clinical outcomes. MethodsA retrospective review of an internal company registry was conducted for all primary TKAs performed from Jan 1, 2014, through a database extract date of Nov 4, 2022. These were grouped by whether there was an intentional soft-tissue release performed (STR) during the surgery or not (NSTR) and whether RA was utilized. The incidence of STR was compared between RA-TKAs and those performed with manual instrumentation. Knee Society Score (KSS) and Knee Society Function Scores (KSFS) were collected at 6 months, 1 year and 2 years. Kaplan-Meier survivorship was performed. ResultsThe incidence of STR was significantly lower for RA vs. Manual (43.81% Vs 86.62%, p < 0.0001). The TKAs with NSTR had higher KSFS compared to those with STR at 6 months (84.73 Vs. 77.51, p < 0.0001), 1 year (89.87 Vs. 83.54, p < 0.0001) and 2 years (90.09 Vs. 82.65, p < 0.0001). There was no difference in survivorship, or KSS at any time point. However, the NSTR group had improved KSS pain sub score at 2 years. ConclusionThe results of this observational, retrospective analysis found that the incidence of soft-tissue release was lower with RA-TKA. Further, regardless of if RA was used, avoiding releases was associated with improved KSFS and KSS pain scores through 2 years post-operatively.

Does Robotic Assistance Help with Bone Preservation in Total Knee Replacement?

This research paper investigates whether robotic total knee replacement (TKR) reduces bone resection compared to conventional TKR. While TKR is a successful procedure, revision surgery remains a challenge with up to 8.3% of all knee replacement procedures requiring revisions. The study retrospectively analyzed the tibial polyethylene inserts used and bone cuts made in 157 primary TKRs performed by a single surgeon. The results show that 93.3% of robotic TKRs used the base size tibial polyethylene of 9 mm, and the average distal femoral cut was 7.4 mm and the average tibial cut was 6.4 mm, with the minimum being 3 mm. The study suggests that robotic TKR reduces bone resection compared to conventional TKR.

Inverse kinematic total knee arthroplasty using conventional instrumentation restores constitutional coronal alignment.

Restricted inverse kinematic alignment (iKA) is a contemporary alignment strategy for total knee arthroplasty (TKA), commonly performed with robotic assistance. While superior clinical results are reported for kinematic-type alignment strategies, registry data indicate no survivorship benefit for navigation or robotic assistance. This study aimed to determine the efficacy of an instrumented, restricted iKA technique for achieving patient-specific alignment. Seventy-nine patients undergoing 84 TKAs (five bilateral procedures) using an iKA technique were included for preoperative and postoperative lower limb alignment analysis. The mean age was 66.5 (range: 43-82) with 33 male and 51 female patients. Artificial intelligence was employed for radiographic measurements. Alignment profiles were classified using the Coronal Plane Alignment of the Knee (CPAK) system. Preoperative and postoperative alignment profiles were compared with subanalyses for preoperative valgus, neutral and varus profiles. The mean joint-line convergence angle (JLCA) reduced from 2.5° to -0.1° postoperatively. The mean lateral distal femoral angle (LDFA) remained unchanged postoperatively, while the mean medial proximal tibial angle (MPTA) increased by 2.5° (p = 0.001). By preservation of the LDFA and restoration of the MPTA, the mean hip knee ankle angle (HKA) moved through 3.5° varus to 1.2° valgus. The CPAK system was used to visually depict changes in alignment profiles for preoperative valgus, neutral and varus knees; with 63% of patients observing an interval change in classification. Encouraged by the latest evidence supporting both conventional instrumentation and kinematic-type TKA strategies, this study describes how a restricted, conventionally instrumented iKA technique may be utilised to restore constitutional lower limb alignment. Level III.

Autonomy, independence, and participation of nursing home habitants addressed by assistive technology: a scoping review

Context Assistive technologies have been identified by researchers and public policies of the Western world to be promising tools to face the challenge of maintaining quality of life of older people, and especially for nursing home habitants. Independence, autonomy, and participation are major determinants of quality of life of nursing homes habitants. Maintaining quality of life is nowadays a priority for public health policies and institutions of the where the population is growing older every year. Method This PRISMA-ScR review aims to determine which assistive technologies are used to promote autonomy, independence, and social participation of nursing home habitants. An electronic search was conducted for English, French articles to identify research studies using CINAHL, PubMed, Cochrane Library, PsycINFO, and Googlescholar. Results 12 papers published between 2009 and 2023 described 6 assistive technologies: technologies integrated into the environment, monitoring technologies, surveillance technologies, information and communication technology, social assistance robots, virtual reality. Six types of AT are currently used worldwide to maintain autonomy, independence and participation of people living in nursing homes. Their use is mainly perceived as positive by habitants, care and non-care staff, next of kin, and experts despite some concerns regarding ethical, financial, consideration. Discussion Nevertheless, their impact on habitant’s autonomy, independence and participation still needs to be measured using suitable tools to understand their real impact on the quality of life of the elderly.

Robotic-assisted spine surgery-a narrative review.

Emerging technologies have increasingly been adopted in spine surgery in the attempt to increase precision and improve outcomes. Robotic assistance is an area of significant interest, with proposed benefits including increased accuracy, decreased complication rates, and decreased radiation exposure. The purpose of this review is to provide an overview of the currently available robotic assistance systems and their associated outcomes and limitations. A review of national databases was performed using key terms "robotic", "spine", and "surgery" for literature from 2014 to 2023. Studies that aimed to describe the utilities of endoscopic surgeries, associated outcomes, limitations, and future directions were included. Studies that were not in English were excluded. This review includes a brief overview of the history of robotic spine surgery as well as its clinical outcomes, limitations, and future directions. Robotic-assisted spine surgery has seen increasing use in the attempt to increase precision and improve outcomes and has been associated with increased accuracy in pedicle screw placement and decreased complication rates. Barriers to its adoption include a significant learning curve, possibly longer operative cases, and significant associated costs. As robotic assistance continues to become increasingly popular in spine surgery, it is critical for surgeons to understand the technology available and the associated outcomes to make informed decisions when considering which system to incorporate into their practice.

Application of Robotic Stereotactic Assistance (ROSA) for spontaneous intracerebral hematoma aspiration and thrombolytic catheter placement

BackgroundSpontaneous intracerebral hemorrhage (ICH) accounts for up to 20% of all strokes and results in 40% mortality at 30 days. Although conservative medical management is still the standard treatment for ICH patients with small hematoma, patients with residual hematoma ≤15 mL after surgery are associated with better functional outcomes and survival rates. This study reported our clinical experience with using Robotic Stereotactic Assistance (ROSA) as a safe and effective approach for stereotactic ICH aspiration and intra-clot catheter placement. MethodsA retrospective analysis was conducted of patients with spontaneous ICH who underwent ROSA-guided ICH aspiration surgery. ROSA-guided ICH surgical techniques, an aspiration and intra-clot catheter placement protocol, and a specific operative workflow (pre-operative protocol, intraoperative procedure and postoperative management) were employed to aspirate ICH using the ROSA One Brain, and appropriate follow-up care was provided. ResultsFrom September 14, 2021 to May 4, 2022, a total of 7 patients were included in the study. Based on our workflow design, ROSA-guided stereotactic ICH aspiration effectively aspirated more than 50% of hematoma volume (or more than 30 mL for massive hematomas), thereby reducing the residual hematoma to less than 15 mL. The mean operative time of entire surgical procedure was 1.3 ± 0.3 h, with very little perioperative blood loss and no perioperative complications. No patients required catheter replacement and all patients’ functional status improved. ConclusionsWithin our clinical practice ROSA-guided ICH aspiration, using our established protocol and workflow, was safe and effective for reducing hematoma volume, with positive functional outcomes.

Efficacy and safety of a neurointerventional operation robotic assistance system in cerebral angiography

BackgroundAt present, neurointerventional surgery requires angiographers to perform operations in the digital subtraction angiography (DSA) room. Ionising radiation and chronic joint damage are still unavoidable for angiographers. Therefore, we researched...

Force/position tracking control of fracture reduction robot based on nonlinear disturbance observer and neural network

AbstractBackgroundFor the fracture reduction robot, the position tracking accuracy and compliance are affected by dynamic loads from muscle stretching, uncertainties in robot dynamics models, and various internal and external disturbances.MethodsA control method that integrates a Radial Basis Function Neural Network (RBFNN) with Nonlinear Disturbance Observer is proposed to enhance position tracking accuracy. Additionally, an admittance control is employed for force tracking to enhance the robot's compliance, thereby improving the safety.ResultsExperiments are conducted on a long bone fracture model with simulated muscle forces and the results demonstrate that the position tracking error is less than ±0.2 mm, the angular displacement error is less than ±0.3°, and the maximum force tracking error is 26.28 N. This result can meet surgery requirements.ConclusionsThe control method shows promising outcomes in enhancing the safety and accuracy of long bone fracture reduction with robotic assistance.

MT2 Operating Room (OR) and Sterilization Efficiencies for Total (TKA), Revision (rTKA) and Unicompartimental Knee Arthroplasty (UKA) Using a Handheld Robotic Assisted (RA) Surgical System

MT2 Operating Room (OR) and Sterilization Efficiencies for Total (TKA), Revision (rTKA) and Unicompartimental Knee Arthroplasty (UKA) Using a Handheld Robotic Assisted (RA) Surgical System

Development of an Advanced Medical Assistance Robot with Intelligent Guidance

Development of an Advanced Medical Assistance Robot with Intelligent Guidance

Design and analysis of a lower limb assistive exoskeleton robot.

In recent years, exoskeleton robot technology has developed rapidly. Exoskeleton robots that can be worn on a human body and provide additional strength, speed or other abilities. Exoskeleton robots have a wide range of applications, such as medical rehabilitation, logistics and disaster relief and other fields. The study goal is to propose a lower limb assistive exoskeleton robot to provide extra power for wearers. The mechanical structure of the exoskeleton robot was designed by using bionics principle to imitate human body shape, so as to satisfy the coordination of man-machine movement and the comfort of wearing. Then a gait prediction method based on neural network was designed. In addition, a control strategy according to iterative learning control was designed. The experiment results showed that the proposed exoskeleton robot can produce effective assistance and reduce the wearer's muscle force output. A lower limb assistive exoskeleton robot was introduced in this paper. The kinematics model and dynamic model of the exoskeleton robot were established. Tracking effects of joint angle displacement and velocity were analyzed to verify feasibility of the control strategy. The learning error of joint angle can be improved with increase of the number of iterations. The error of trajectory tracking is acceptable.

Robotic-assisted patellofemoral arthroplasty provides excellent implant survivorship and high patient satisfaction at mid-term follow-up

PurposeRobotic adoption in knee surgery has yielded several benefits, but its application in patellofemoral arthroplasty (PFA) remains barely reported. The purpose of this study was to determine implant survival, patient satisfaction, and functional outcomes after robotic-assisted PFA at an intermediate follow-up.MethodsThis prospective analysis targeted 18 knees of 16 consecutive patients who underwent robot-aided PFA with three-year minimum follow-up (range, 3 to 6 years). Each patient was evaluated collecting pre-operative and post-operative medical record data, including range of motion, radiographic images, and multiple scores, such as VAS, APKS, and OKS.ResultsAt surgery, the mean age was 55.4 years ± 14.4 (range, 32 to 78 years), and the mean BMI was 26.8 kg/m² ±5.2 (range, 20 to 36). Etiologies of patellofemoral osteoarthritis included idiopathic degeneration (28%), post-traumatic (33%), and dysplasia (39%). Pre-implantation scores were VAS 7.9 ± 1.4, AKPS 34.6 ± 23.3, and OKS 17.3 ± 10.3. One implant was revised with primary total knee arthroplasty for osteoarthritis progression. Clinical and radiographic follow-up showed no signs of loosening or infection. The maximum flexion reached an average of 131.1°±10.5° (range, 110° to 145°), accompanied by significantly improved score results (P-value < 0.01): VAS 1.1 ± 1.4, AKPS 90.2 ± 8.6, and OKS 46.3 ± 1.8.ConclusionsAt 3 years after robotic assisted patellofemoral arthroplasty, excellent implant survival and patient satisfaction rates can be expected along with significantly improved functional and pain control outcomes. Although the limitations imposed by the restricted cohort, these findings indicate that robotic assistance in PFA is both safe and effective at intermediate follow-up.

Smart Autonomous Nurse Assistant Robot (SANAR)

Abstract: In the evolving landscape of healthcare, the integration of innovative technologies has become paramount to enhance efficiency, accessibility, and usability across all sectors, particularly in the medical industry. This project proposes the development of a Smart Autonomous Nurse Assistant Robot (SANAR) aimed at revolutionizing medical care delivery, especially during emergencies and pandemics like Covid-19. SANAR utilizes cutting-edge technology to streamline disease diagnosis, monitor patient health in real-time, and facilitate drug delivery. The core of SANAR's functionality lies in its utilization of a health tracker system-based IoT platform, which continuously analyzes vital patient data, including oxygen levels, pulse rate, and temperature. Through simple text commands and a timer-based medicine scheduler, SANAR ensures timely medication administration, leveraging a cloud server for seamless data access and management with utmost security. Equipped with advanced sensors such as oximeter, heartbeat, ultrasonic sensors, and a voice module, SANAR leverages Internet of Things (IoT) technology to enable data storage and retrieval over HTTP and MQTT protocols, facilitating connectivity and scalability. The primary goal of this project is to democratize smart automation in healthcare, making it accessible and affordable to all segments of society, ultimately empowering medical staff to deliver efficient and effective care.

Beyond the manual touch: situational-aware force control for increased safety in robot-assisted skullbase surgery.

Skullbase surgery demands exceptional precision when removing bone in the lateral skull base. Robotic assistance can alleviate the effect of human sensory-motor limitations. However, the stiffness and inertia of the robot can significantly impact the surgeon's perception and control of the tool-to-tissue interaction forces. We present a situational-aware, force control technique aimed at regulating interaction forces during robot-assisted skullbase drilling. The contextual interaction information derived from the digital twin environment is used to enhance sensory perception and suppress undesired high forces. To validate our approach, we conducted initial feasibility experiments involving a medical and two engineering students. The experiment focused on further drilling around critical structures following cortical mastoidectomy. The experiment results demonstrate that robotic assistance coupled with our proposed control scheme effectively limited undesired interaction forces when compared to robotic assistance without the proposed force control. The proposed force control techniques show promise in significantly reducing undesired interaction forces during robot-assisted skullbase surgery. These findings contribute to the ongoing efforts to enhance surgical precision and safety in complex procedures involving the lateral skull base.

A framework for trust-related knowledge transfer in human–robot interaction

Trustworthy human–robot interaction (HRI) during activities of daily living (ADL) presents an interesting and challenging domain for assistive robots, particularly since methods for estimating the trust level of a human participant towards the assistive robot are still in their infancy. Trust is a multifaced concept which is affected by the interactions between the robot and the human, and depends, among other factors, on the history of the robot’s functionality, the task and the environmental state. In this paper, we are concerned with the challenge of trust transfer, i.e. whether experiences from interactions on a previous collaborative task can be taken into consideration in the trust level inference for a new collaborative task. This has the potential of avoiding re-computing trust levels from scratch for every new situation. The key challenge here is to automatically evaluate the similarity between the original and the novel situation, then adapt the robot’s behaviour to the novel situation using previous experience with various objects and tasks. To achieve this, we measure the semantic similarity between concepts in knowledge graphs (KGs) and adapt the robot’s actions towards a specific user based on personalised interaction histories. These actions are grounded and then verified before execution using a geometric motion planner to generate feasible trajectories in novel situations. This framework has been experimentally tested in human–robot handover tasks in different kitchen scene contexts. We conclude that trust-related knowledge positively influences and improves collaboration in both performance and time aspects.

Advances in the Application of AI Robots in Critical Care: Scoping Review.

In recent epochs, the field of critical medicine has experienced significant advancements due to the integration of artificial intelligence (AI). Specifically, AI robots have evolved from theoretical concepts to being actively implemented in clinical trials and applications. The intensive care unit (ICU), known for its reliance on a vast amount of medical information, presents a promising avenue for the deployment of robotic AI, anticipated to bring substantial improvements to patient care. This review aims to comprehensively summarize the current state of AI robots in the field of critical care by searching for previous studies, developments, and applications of AI robots related to ICU wards. In addition, it seeks to address the ethical challenges arising from their use, including concerns related to safety, patient privacy, responsibility delineation, and cost-benefit analysis. Following the scoping review framework proposed by Arksey and O'Malley and the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we conducted a scoping review to delineate the breadth of research in this field of AI robots in ICU and reported the findings. The literature search was carried out on May 1, 2023, across 3 databases: PubMed, Embase, and the IEEE Xplore Digital Library. Eligible publications were initially screened based on their titles and abstracts. Publications that passed the preliminary screening underwent a comprehensive review. Various research characteristics were extracted, summarized, and analyzed from the final publications. Of the 5908 publications screened, 77 (1.3%) underwent a full review. These studies collectively spanned 21 ICU robotics projects, encompassing their system development and testing, clinical trials, and approval processes. Upon an expert-reviewed classification framework, these were categorized into 5 main types: therapeutic assistance robots, nursing assistance robots, rehabilitation assistance robots, telepresence robots, and logistics and disinfection robots. Most of these are already widely deployed and commercialized in ICUs, although a select few remain under testing. All robotic systems and tools are engineered to deliver more personalized, convenient, and intelligent medical services to patients in the ICU, concurrently aiming to reduce the substantial workload on ICU medical staff and promote therapeutic and care procedures. This review further explored the prevailing challenges, particularly focusing on ethical and safety concerns, proposing viable solutions or methodologies, and illustrating the prospective capabilities and potential of AI-driven robotic technologies in the ICU environment. Ultimately, we foresee a pivotal role for robots in a future scenario of a fully automated continuum from admission to discharge within the ICU. This review highlights the potential of AI robots to transform ICU care by improving patient treatment, support, and rehabilitation processes. However, it also recognizes the ethical complexities and operational challenges that come with their implementation, offering possible solutions for future development and optimization.

First modified Delphi consensus statement on robotic-assisted da Vinci sleeve gastrectomy

BackgroundSleeve gastrectomy (SG) is the most commonly performed metabolic and bariatric surgery (MBS) procedure. Technical considerations related to the performance of SG are well established and reported in the literature but not in relation to robotic-assisted (RA) SG. We report the results of the first modified Delphi consensus-building exercise addressing technical considerations of RA da Vinci (dV) SG. ObjectivesDevelop best practices for the performance of robotic-assisted da Vinci sleeve gastrectomy. SettingSurvey based consensus statement. MethodsA consensus building committee (CBC) was created comprising 10 experts in the field of RA surgery and MBS based on strict selection criteria. The CBC developed 49 consensus statements which were then shared with 240 experts in RA surgery. Our stopping criterion was stability in responses (≤15%). The consensus cut point was 70%. ResultsThe overall response rate was 49%. In the first round of voting, there was consensus agreement on 25 statements (51%), consensus disagreement on 14 (28%), and no consensus on the remaining statements (21%). In the second round of voting, we reached agreement on 3 additional statements. Experts recommended the use of the number of pauses generated by the stapler to guide choice of staple height (91.2%) and to upsize the staple height when using buttressing (92%). There was also consensus (81.4%) that the use of the closed staple height of 1.00 mm (white) is acceptable and that stapling of the antrum using a 1.5-mm staple (blue load) is also acceptable (73%). ConclusionsCollective expert opinion structured through a modified Delphi consensus statement presents a practical guide for surgeons interested in performing dV-SG.

Impact of Insertion Speed, Depth, and Robotic Assistance on Cochlear Implant Insertion Forces and Intracochlear Pressure: A Scoping Review.

Cochlear implants are crucial for addressing severe-to-profound hearing loss, with the success of the procedure requiring careful electrode placement. This scoping review synthesizes the findings from 125 studies examining the factors influencing insertion forces (IFs) and intracochlear pressure (IP), which are crucial for optimizing implantation techniques and enhancing patient outcomes. The review highlights the impact of variables, including insertion depth, speed, and the use of robotic assistance on IFs and IP. Results indicate that higher insertion speeds generally increase IFs and IP in artificial models, a pattern not consistently observed in cadaveric studies due to variations in methodology and sample size. The study also explores the observed minimal impact of robotic assistance on reducing IFs compared to manual methods. Importantly, this review underscores the need for a standardized approach in cochlear implant research to address inconsistencies and improve clinical practices aimed at preserving hearing during implantation.

The analysis of pedestrian flow in the smart city by improved DWA with robot assistance

With the acceleration of urbanization in China, the urban population continues to grow, leading to frequent occurrences of crowded public spaces, which in turn trigger traffic congestion and even safety accidents. In order to more effectively control pedestrian flow, enhance the efficiency and safety of public spaces, this experiment conducts in-depth research and improvement on the traditional Dynamic Window Approach (DWA), and applies it to the fine control of pedestrian flow. Specifically, this study comprehensively reviews and analyzes the characteristics of pedestrian traffic flow and the working principles of traditional DWA. Based on this, the shortcomings of traditional DWA in dealing with complex pedestrian flow scenarios are identified, and targeted improvement solutions are proposed. The core of this improvement scheme lies in the introduction of a new evaluation function, enabling DWA to more accurately balance various factors in the decision-making process, including pedestrian movement speed, direction, and spatial distribution. Subsequently, the improved DWA is validated through simulation experiments. The experimental scenario is set in an area of 18 m*18 m, and compared with traditional DWA, the improved DWA shows significant advantages in trajectory length and travel time. Specifically, the trajectory length of the traditional DWA robot is 19.4 m, with a required time of 34.8 s, while the trajectory length of the improved DWA robot is shortened to 18.7 m, and the time is reduced to 18.6 s. This result fully demonstrates the effectiveness of the improved DWA in optimizing pedestrian flow control. The improved DWA proposed in this study not only has strong scientific validity but also demonstrates high efficiency in practical applications. This study has important reference value for improving the safety of urban public spaces and improving pedestrian traffic flow conditions, and provides new ideas for the further development of pedestrian flow control technology in the future.

How Can Large Language Models Enable Better Socially Assistive Human-Robot Interaction: A Brief Survey

Socially assistive robots (SARs) have shown great success in providing personalized cognitive-affective support for user populations with special needs such as older adults, children with autism spectrum disorder (ASD), and individuals with mental health challenges. The large body of work on SAR demonstrates its potential to provide at-home support that complements clinic-based interventions delivered by mental health professionals, making these interventions more effective and accessible. However, there are still several major technical challenges that hinder SAR-mediated interactions and interventions from reaching human-level social intelligence and efficacy. With the recent advances in large language models (LLMs), there is an increased potential for novel applications within the field of SAR that can significantly expand the current capabilities of SARs. However, incorporating LLMs introduces new risks and ethical concerns that have not yet been encountered, and must be carefully be addressed to safely deploy these more advanced systems. In this work, we aim to conduct a brief survey on the use of LLMs in SAR technologies, and discuss the potentials and risks of applying LLMs to the following three major technical challenges of SAR: 1) natural language dialog; 2) multimodal understanding; 3) LLMs as robot policies.