Closing the loop in minimally supervised human-robot interaction: formative and summative feedback.

Human instructors fluidly communicate with hand gestures, head and body movements, and facial expressions, but robots rarely leverage these complementary cues. A minimally supervised social robot with such skills could help people exercise and learn new activities. Thus, we investigated how nonverbal feedback from a humanoid robot affects human behavior. Inspired by the education literature, we evaluated formative feedback (real-time corrections) and summative feedback (post-task scores) for three distinct tasks: positioning in the room, mimicking the robot's arm pose, and contacting the robot's hands. Twenty-eight adults completed seventy-five 30-s-long trials with no explicit instructions or experimenter help. Motion-capture data analysis shows that both formative and summative feedback from the robot significantly aided user performance. Additionally, formative feedback improved task understanding. These results show the power of nonverbal cues based on human movement and the utility of viewing feedback through formative and summative lenses.

Influence of different position modal parameters on milling chatter stability of orthopedic surgery robots.

This research is dedicated to exploring the dynamics of milling chatter stability in orthopedic surgery robots, focusing on the impact of position modal parameters on chatter stability. Initially, we develop a dynamic milling force model for the robotic milling process that integrates both modal coupling and regenerative effects. We then employ the zero-order frequency domain method to derive a chatter stability domain model, visually represented through stability lobe diagrams (SLDs). Through conducting hammer test experiments, we ascertain the robot's modal parameters at varying positions, enabling the precise generation of SLDs. This study also includes experimental validation of the chatter SLD analysis method, laying the groundwork for further examination of chatter stability across different positional modal parameters. Finally, our analysis of the variations in modal parameters on the stability of robot milling chatter yields a theoretical framework for optimizing cutting parameters and developing control strategies within the context of orthopedic surgery robots.

Optimizing shoulder elevation assist rate in exoskeletal rehabilitation based on muscular activity indices: a clinical feasibility study.

BACKGROUND: Restoring shoulder function is critical for upper-extremity rehabilitation following a stroke. The complex musculoskeletal anatomy of the shoulder presents a challenge for safely assisting elevation movements through robotic interventions. The level of shoulder elevation assistance in rehabilitation is often based on clinical judgment. There is no standardized method for deriving an optimal level of assistance, underscoring the importance of addressing abnormal movements during shoulder elevation, such as abnormal synergies and compensatory actions. This study aimed to investigate the effectiveness and safety of a newly developed shoulder elevation exoskeleton robot by applying a novel optimization technique derived from the muscle synergy index. METHODS: Twelve chronic stroke participants underwent an intervention consisting of 100 robot-assisted shoulder elevation exercises (10 × 10 times, approximately 40 min) for 10 days (4-5 times/week). The optimal robot assist rate was derived by detecting the change points using the co-contraction index, calculated from electromyogram (EMG) data obtained from the anterior deltoid and biceps brachii muscles during shoulder elevation at the initial evaluation. The primary outcomes were the Fugl-Meyer assessment-upper extremity (FMA-UE) shoulder/elbow/forearm score, kinematic outcomes (maximum angle of voluntary shoulder flexion and elbow flexion ratio during shoulder elevation), and shoulder pain outcomes (pain-free passive shoulder flexion range of motion [ROM] and visual analogue scale for pain severity during shoulder flexion). The effectiveness and safety of robotic therapy were examined using the Wilcoxon signed-rank sum test. RESULTS: All 12 patients completed the procedure without any adverse events. Two participants were excluded from the analysis because the EMG of the biceps brachii was not obtained. Ten participants (five men and five women; mean age: 57.0 [5.5] years; mean FMA-UE total score: 18.7 [10.5] points) showed significant improvement in the FMA-UE shoulder/elbow/forearm score, kinematic outcomes, and pain-free passive shoulder flexion ROM (P < 0.05). The shoulder pain outcomes remained unchanged or improved in all patients. CONCLUSIONS: The study presents a method for deriving the optimal robotic assist rate. Rehabilitation using a shoulder robot based on this derived optimal assist rate showed the possibility of safely improving the upper-extremity function in patients with severe stroke in the chronic phase.

A fully autonomous robotic ultrasound system for thyroid scanning.

The current thyroid ultrasound relies heavily on the experience and skills of the sonographer and the expertise of the radiologist, and the process is physically and cognitively exhausting. In this paper, we report a fully autonomous robotic ultrasound system, which is able to scan thyroid regions without human assistance and identify malignant nod- ules. In this system, human skeleton point recognition, reinforcement learning, and force feedback are used to deal with the difficulties in locating thyroid targets. The orientation of the ultrasound probe is adjusted dynamically via Bayesian optimization. Experimental results on human participants demonstrated that this system can perform high-quality ultrasound scans, close to manual scans obtained by clinicians. Additionally, it has the potential to detect thyroid nodules and provide data on nodule characteristics for American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) calculation.

Effects of robot-assisted gait training using the Welwalk on gait independence for individuals with hemiparetic stroke: an assessor-blinded, multicenter randomized controlled trial.

BACKGROUND: Gait disorder remains a major challenge for individuals with stroke, affecting their quality of life and increasing the risk of secondary complications. Robot-assisted gait training (RAGT) has emerged as a promising approach for improving gait independence in individuals with stroke. This study aimed to evaluate the effect of RAGT in individuals with subacute hemiparetic stroke using a one-leg assisted gait robot called Welwalk WW-1000. METHODS: An assessor-blinded, multicenter randomized controlled trial was conducted in the convalescent rehabilitation wards of eight hospitals in Japan. Participants with first-ever hemiparetic stroke who could not walk at pre-intervention assessment were randomized to either the Welwalk group, which underwent RAGT with conventional physical therapy, or the control group, which underwent conventional physical therapy alone. Both groups received 80 min of physical therapy per day, 7 days per week, while the Welwalk group received 40 min of RAGT per day, 6 days per week, as part of their physical therapy. The primary outcome was gait independence, as assessed using the Functional Independence Measure Walk Score. RESULTS: A total of 91 participants were enrolled, 85 of whom completed the intervention. As a result, 91 participants, as a full analysis set, and 85, as a per-protocol set, were analyzed. The primary outcome, the cumulative incidence of gait-independent events, was not significantly different between the groups. Subgroup analysis revealed that the interaction between the intervention group and stroke type did not yield significant differences in either the full analysis or per-protocol set. However, although not statistically significant, a discernible trend toward improvement with Welwalk was observed in cases of cerebral infarction for the full analysis and per-protocol sets (HR 4.167 [95%CI 0.914-18.995], p = 0.065, HR 4.443 [95%CI 0.973-20.279], p = 0.054, respectively). CONCLUSIONS: The combination of RAGT using Welwalk and conventional physical therapy was not significantly more effective than conventional physical therapy alone in promoting gait independence in individuals with subacute hemiparetic stroke, although a trend toward earlier gait independence was observed in individuals with cerebral infarction. TRIAL REGISTRATION: This study was registered with the Japan Registry of Clinical Trials ( https://jrct.niph.go.jp ; jRCT 042180078) on March 3, 2019.

Letter to editor: Bridging the gap: robotic applications in cerebral aneurysms neurointerventions - a systematic review.

The letter critically evaluates the role of robotic applications in cerebral aneurysm neurointerventions, synthesizing a diverse array of studies to elucidate both the potential benefits and inherent limitations of this emerging technology. The review highlights the advancements in precision, efficiency, and patient outcomes facilitated by robotic platforms, while also acknowledging challenges such as the steep learning curve and the need for further research to establish long-term efficacy and cost-effectiveness. By navigating through the complexities of robotic-assisted neurosurgery, the review provides valuable insights into the transformative potential of robotics in optimizing treatment paradigms and improving patient care.

Magnetic steering continuum robot for transluminal procedures with programmable shape and functionalities.

Millimeter-scale soft continuum robots offer safety and adaptability in transluminal procedures due to their passive compliance, but this feature necessitates interactions with surrounding lumina, leading to potential medical risks and restricted mobility. Here, we introduce a millimeter-scale continuum robot, enabling apical extension while maintaining structural stability. Utilizing phase transition components, the robot executes cycles of tip-based elongation, steered accurately through programmable magnetic fields. Each motion cycle features a solid-like backbone for stability, and a liquid-like component for advancement, thereby enabling autonomous shaping without reliance on environmental interactions. Together with clinical imaging technologies, we demonstrate the capability of navigating through tortuous and fragile lumina to transport microsurgical tools. Once it reaches larger anatomical spaces such as stomach, it can morph into functional 3D structures that serve as surgical tools or sensing units, overcoming the constraints of initially narrow pathways. By leveraging this design paradigm, we anticipate enhanced safety, multi-functionality, and cooperative capabilities among millimeter-scale continuum robots, opening new avenues for transluminal robotic surgery.

A Nanorobotics-Based Approach of Breast Cancer in the Nanotechnology Era.

We are living in an era of advanced nanoscience and nanotechnology. Numerous nanomaterials, culminating in nanorobots, have demonstrated ingenious applications in biomedicine, including breast cancer (BC) nano-theranostics. To solve the complicated problem of BC heterogeneity, non-targeted drug distribution, invasive diagnostics or surgery, resistance to classic onco-therapies and real-time monitoring of tumors, nanorobots are designed to perform multiple tasks at a small scale, even at the organelles or molecular level. Over the last few years, most nanorobots have been bioengineered as biomimetic and biocompatible nano(bio)structures, resembling different organisms and cells, such as urchin, spider, octopus, fish, spermatozoon, flagellar bacterium or helicoidal cyanobacterium. In this review, readers will be able to deepen their knowledge of the structure, behavior and role of several types of nanorobots, among other nanomaterials, in BC theranostics. We summarized here the characteristics of many functionalized nanodevices designed to counteract the main neoplastic hallmark features of BC, from sustaining proliferation and evading anti-growth signaling and resisting programmed cell death to inducing angiogenesis, activating invasion and metastasis, preventing genomic instability, avoiding immune destruction and deregulating autophagy. Most of these nanorobots function as targeted and self-propelled smart nano-carriers or nano-drug delivery systems (nano-DDSs), enhancing the efficiency and safety of chemo-, radio- or photodynamic therapy, or the current imagistic techniques used in BC diagnosis. Most of these nanorobots have been tested in vitro, using various BC cell lines, as well as in vivo, mainly based on mice models. We are still waiting for nanorobots that are low-cost, as well as for a wider transition of these favorable effects from laboratory to clinical practice.

Optimizing Human-Robot Teaming Performance through Q-Learning-Based Task Load Adjustment and Physiological Data Analysis.

The transition to Industry 4.0 and 5.0 underscores the need for integrating humans into manufacturing processes, shifting the focus towards customization and personalization rather than traditional mass production. However, human performance during task execution may vary. To ensure high human-robot teaming (HRT) performance, it is crucial to predict performance without negatively affecting task execution. Therefore, to predict performance indirectly, significant factors affecting human performance, such as engagement and task load (i.e., amount of cognitive, physical, and/or sensory resources required to perform a particular task), must be considered. Hence, we propose a framework to predict and maximize the HRT performance. For the prediction of task performance during the development phase, our methodology employs features extracted from physiological data as inputs. The labels for these predictions-categorized as accurate performance or inaccurate performance due to high/low task load-are meticulously crafted using a combination of the NASA TLX questionnaire, records of human performance in quality control tasks, and the application of Q-Learning to derive task-specific weights for the task load indices. This structured approach enables the deployment of our model to exclusively rely on physiological data for predicting performance, thereby achieving an accuracy rate of 95.45% in forecasting HRT performance. To maintain optimized HRT performance, this study further introduces a method of dynamically adjusting the robot's speed in the case of low performance. This strategic adjustment is designed to effectively balance the task load, thereby enhancing the efficiency of human-robot collaboration.

Anthropomorphic Tendon-Based Hands Controlled by Agonist-Antagonist Corticospinal Neural Network.

This article presents a study on the neurobiological control of voluntary movements for anthropomorphic robotic systems. A corticospinal neural network model has been developed to control joint trajectories in multi-fingered robotic hands. The proposed neural network simulates cortical and spinal areas, as well as the connectivity between them, during the execution of voluntary movements similar to those performed by humans or monkeys. Furthermore, this neural connection allows for the interpretation of functional roles in the motor areas of the brain. The proposed neural control system is tested on the fingers of a robotic hand, which is driven by agonist-antagonist tendons and actuators designed to accurately emulate complex muscular functionality. The experimental results show that the corticospinal controller produces key properties of biological movement control, such as bell-shaped asymmetric velocity profiles and the ability to compensate for disturbances. Movements are dynamically compensated for through sensory feedback. Based on the experimental results, it is concluded that the proposed biologically inspired adaptive neural control system is robust, reliable, and adaptable to robotic platforms with diverse biomechanics and degrees of freedom. The corticospinal network successfully integrates biological concepts with engineering control theory for the generation of functional movement. This research significantly contributes to improving our understanding of neuromotor control in both animals and humans, thus paving the way towards a new frontier in the field of neurobiological control of anthropomorphic robotic systems.

Nodes for modes: nodal honeycomb metamaterial enables a soft robot with multimodal locomotion.

Soft-bodied animals, such as worms and snakes, use many muscles in different ways to traverse unstructured environments and inspire tools for accessing confined spaces. They demonstrate versatility of locomotion which is essential for adaptation to changing terrain conditions. However, replicating such versatility in untethered soft-bodied robots with multimodal locomotion capabilities have been challenging due to complex fabrication processes and limitations of soft body structures to accommodate hardware such as actuators, batteries and circuit boards. Here, we present MetaCrawler, a 3D printed metamaterial soft robot designed for multimodal and omnidirectional locomotion. Our design approach facilitated an easy fabrication process through a discrete assembly of a modular nodal honeycomb lattice with soft and hard components. A crucial benefit of the nodal honeycomb architecture is the ability of its hard components, nodes, to accommodate a distributed actuation system, comprising servomotors, control circuits, and batteries. Enabled by this distributed actuation, MetaCrawler achieves five locomotion modes: peristalsis, sidewinding, sideways translation, turn-in-place, and anguilliform. Demonstrations showcase MetaCrawler's adaptability in confined channel navigation, vertical traversing, and maze exploration. This soft robotic system holds the potential to offer easy-to-fabricate and accessible solutions for multimodal locomotion in applications such as search and rescue, pipeline inspection, and space missions.

Improvements of mid-thigh circumferences following robotic rehabilitation in hemiparetic stroke patients.

INTRODUCTION: Stroke has emerged as the leading cause of disability globally. The provision of long-term rehabilitation to stroke survivors poses a health care burden to many countries. Robotic devices have created a major turning point in stroke rehabilitation program. Currently, the anthropometric evidence to support the benefit of robotic rehabilitation (RR) among stroke patients is scarce. Therefore, the aim of this study was to evaluate the impact of RR on the mid-thigh circumferences of the paretic limbs in stroke patients. METHODS: Twenty stroke patients from conventional rehabilitation (CR) (n = 10) and RR (n = 10) groups were recruited through a purposive sampling method. Patients in the CR group received a two-hour session of a five-day-a-week home-based CR program for 4 weeks. Patients in the RR group received a five-day-a-week of an hour combined physiotherapy and occupational therapy session and a one-hour robotic therapy session using the HAL® Cyberdyne lower-limb, for 4 weeks. The mid-thigh circumferences of both limbs were measured on day 1 (baseline), week 2 and week 4 of rehabilitation program. RESULTS: The results revealed no statistically significant difference in the mid-thigh circumferences between the paretic (F1.05,9.44 = 1.96, p = 0.20), and the normal (F1.05,9.44 = 1.96, p = 0.20) sides in the CR group (n = 10). For the comparison between the paretic and normal sides in the RR group (n = 10), the paretic mid-thigh circumferences revealed significant time effect results (F2,18 = 11.91, p = 0.001), which were due to changes between baseline and week 2, and baseline and week 4 measurements. Interestingly, the normal mid-thigh circumferences also revealed a significant time effect (F2,18 = 6.56, p = 0.007), which is due to changes between baseline and week 4. One-way analysis of variance was employed to compare the mean average between groups due to the difference in the baseline measurements of the mid-thigh circumferences between the paretic side of the CR and the RR groups. With this adjustment, the average means mid-thigh circumferences after 4 weeks of therapy were shown to be significantly different between the CR and RR groups (F1,18 = 12.49, p = 0.02). CONCLUSION: Significant increments in the mid-thigh circumferences following RR were seen in the paretic limbs of stroke patients. Hence, this study may provide some insights into further potential research related to the benefits of RR in stroke patients.

Reinforcement Learning Algorithms and Applications in Healthcare and Robotics: A Comprehensive and Systematic Review.

Reinforcement learning (RL) has emerged as a dynamic and transformative paradigm in artificial intelligence, offering the promise of intelligent decision-making in complex and dynamic environments. This unique feature enables RL to address sequential decision-making problems with simultaneous sampling, evaluation, and feedback. As a result, RL techniques have become suitable candidates for developing powerful solutions in various domains. In this study, we present a comprehensive and systematic review of RL algorithms and applications. This review commences with an exploration of the foundations of RL and proceeds to examine each algorithm in detail, concluding with a comparative analysis of RL algorithms based on several criteria. This review then extends to two key applications of RL: robotics and healthcare. In robotics manipulation, RL enhances precision and adaptability in tasks such as object grasping and autonomous learning. In healthcare, this review turns its focus to the realm of cell growth problems, clarifying how RL has provided a data-driven approach for optimizing the growth of cell cultures and the development of therapeutic solutions. This review offers a comprehensive overview, shedding light on the evolving landscape of RL and its potential in two diverse yet interconnected fields.

Development of a Two-Finger Haptic Robotic Hand with Novel Stiffness Detection and Impedance Control.

Haptic hands and grippers, designed to enable skillful object manipulation, are pivotal for high-precision interaction with environments. These technologies are particularly vital in fields such as minimally invasive surgery, where they enhance surgical accuracy and tactile feedback: in the development of advanced prosthetic limbs, offering users improved functionality and a more natural sense of touch, and within industrial automation and manufacturing, they contribute to more efficient, safe, and flexible production processes. This paper presents the development of a two-finger robotic hand that employs simple yet precise strategies to manipulate objects without damaging or dropping them. Our innovative approach fused force-sensitive resistor (FSR) sensors with the average current of servomotors to enhance both the speed and accuracy of grasping. Therefore, we aim to create a grasping mechanism that is more dexterous than grippers and less complex than robotic hands. To achieve this goal, we designed a two-finger robotic hand with two degrees of freedom on each finger; an FSR was integrated into each fingertip to enable object categorization and the detection of the initial contact. Subsequently, servomotor currents were monitored continuously to implement impedance control and maintain the grasp of objects in a wide range of stiffness. The proposed hand categorized objects' stiffness upon initial contact and exerted accurate force by fusing FSR and the motor currents. An experimental test was conducted using a Yale-CMU-Berkeley (YCB) object set consisted of a foam ball, an empty soda can, an apple, a glass cup, a plastic cup, and a small milk packet. The robotic hand successfully picked up these objects from a table and sat them down without inflicting any damage or dropping them midway. Our results represent a significant step forward in developing haptic robotic hands with advanced object perception and manipulation capabilities.

Exploring Human-Exoskeleton Interaction Dynamics: An In-Depth Analysis of Knee Flexion-Extension Performance across Varied Robot Assistance-Resistance Configurations.

Knee rehabilitation therapy after trauma or neuromotor diseases is fundamental to restore the joint functions as best as possible, exoskeleton robots being an important resource in this context, since they optimize therapy by applying tailored forces to assist or resist movements, contributing to improved patient outcomes and treatment efficiency. One of the points that must be taken into account when using robots in rehabilitation is their interaction with the patient, which must be safe for both and guarantee the effectiveness of the treatment. Therefore, the objective of this study was to assess the interaction between humans and an exoskeleton during the execution of knee flexion-extension movements under various configurations of robot assistance and resistance. The evaluation encompassed considerations of myoelectric activity, muscle recruitment, robot torque, and performed movement. To achieve this, an experimental protocol was implemented, involving an individual wearing the exoskeleton and executing knee flexion-extension motions while seated, with the robot configured in five distinct modes: passive (P), assistance on flexion (FA), assistance on extension (EA), assistance on flexion and extension (CA), and resistance on flexion and extension (CR). Results revealed distinctive patterns of movement and muscle recruitment for each mode, highlighting the complex interplay between human and robot; for example, the largest RMS tracking errors were for the EA mode (13.72 degrees) while the smallest for the CR mode (4.47 degrees), a non-obvious result; in addition, myoelectric activity was demonstrated to be greater for the completely assisted mode than without the robot (the maximum activation levels for the vastus medialis and vastus lateralis muscles were more than double those when the user had assistance from the robot). Tracking errors, muscle activations, and torque values varied across modes, emphasizing the need for careful consideration in configuring exoskeleton assistance and resistance to ensure effective and safe rehabilitation. Understanding these human-robot interactions is essential for developing precise rehabilitation programs, optimizing treatment effectiveness, and enhancing patient safety.

A six degrees-of-freedom cable-driven robotic platform for head-neck movement.

This paper introduces a novel cable-driven robotic platform that enables six degrees-of-freedom (DoF) natural head-neck movements. Poor postural control of the head-neck can be a debilitating symptom of neurological disorders such as amyotrophic lateral sclerosis and cerebral palsy. Current treatments using static neck collars are inadequate, and there is a need to develop new devices to empower movements and facilitate physical rehabilitation of the head-neck. State-of-the-art neck exoskeletons using lower DoF mechanisms with rigid linkages are limited by their hard motion constraints imposed on head-neck movements. By contrast, the cable-driven robot presented in this paper does not constrain motion and enables wide-range, 6-DoF control of the head-neck. We present the mechatronic design, validation, and control implementations of this robot, as well as a human experiment to demonstrate a potential use case of this versatile robot for rehabilitation. Participants were engaged in a target reaching task while the robot applied both assistive and resistive moments on the head during the task. Our results show that neck muscle activation increased by 19% when moving the head against resistance and decreased by 28-43% when assisted by the robot. Overall, these results provide a scientific justification for further research in enabling movement and identifying personalized rehabilitation for motor training. Beyond rehabilitation, other applications such as applying force perturbations on the head to study sensory integration and applying traction to achieve pain relief may benefit from the innovation of this robotic platform which is capable of applying controlled 6-DoF forces/moments on the head.

Real-world humanoid locomotion with reinforcement learning.

Humanoid robots that can autonomously operate in diverse environments have the potential to help address labor shortages in factories, assist elderly at home, and colonize new planets. Although classical controllers for humanoid robots have shown impressive results in a number of settings, they are challenging to generalize and adapt to new environments. Here, we present a fully learning-based approach for real-world humanoid locomotion. Our controller is a causal transformer that takes the history of proprioceptive observations and actions as input and predicts the next action. We hypothesized that the observation-action history contains useful information about the world that a powerful transformer model can use to adapt its behavior in context, without updating its weights. We trained our model with large-scale model-free reinforcement learning on an ensemble of randomized environments in simulation and deployed it to the real-world zero-shot. Our controller could walk over various outdoor terrains, was robust to external disturbances, and could adapt in context.

A meta-analysis of unilateral axillary approach for robotic surgery compared with open surgery for differentiated thyroid carcinoma.

OBJECTIVE: The Da Vinci Robot is the most advanced micro-control system in endoscopic surgical instruments and has gained a lot of valuable experience today. However, the technical feasibility and oncological safety of the robot over open surgery are still uncertain. This work is to systematically evaluate the efficacy of the unilateral axillary approach for robotic surgery compared to open surgery for differentiated thyroid carcinoma. METHODS: PubMed, Embase, Cochrane Library, and Web of Science databases were utilized to search for relevant literatures of robotic thyroid surgery using unilateral axillary approach compared to open thyroid surgery, and a meta-analysis was performed using RevMan software version 5.3. Statistical analysis was performed through Mantle-Haenszel and inverse variance methods. RESULTS: Twelve studies with a total of 2660 patients were included in the meta-analysis. The results showed that compared with the open group, the robotic group had a longer total thyroidectomy time, shorter hospital stay, less intraoperative bleeding, more postoperative drainage, fewer retrieved central lymph nodes, and higher cosmetic satisfaction (all P < 0.05). In contrast, temporary and permanent laryngeal recurrent nerve injury, temporary and permanent hypoparathyroidism or hypocalcemia, brachial plexus nerve injury, number of retrieved central lymph nodes, number of retrieved lymph nodes in the lateral cervical region, number of lymph node metastases in the lateral cervical region, hematoma, seroma, lymphatic leak, stimulated thyroglobulin (sTg) and unstimulated thyroglobulin (uTg), and the number and recurrence rate of patients with sTg <1ng/ml were not statistically different between the two groups (P > 0.05). CONCLUSIONS: The unilateral axillary approach for robotic thyroid surgery may achieve outcomes similar to those of open surgery. Further validation is required in a prospective randomized controlled trial.

A Comprehensive Review: Robot-Assisted Treatments for Gait Rehabilitation in Stroke Patients.

Robot-assisted gait training (RAGT) is at the cutting edge of stroke rehabilitation, offering a groundbreaking method to improve motor recovery and enhance the quality of life for stroke survivors. This review investigates the effectiveness and application of various RAGT systems, including both end-effector and exoskeleton robots, in facilitating gait enhancements. The selection process for this comprehensive analysis involved a meticulous review of the literature from databases such as PubMed, the Cochrane Library, and EMBASE, focusing on studies published between 2018 and 2023. Ultimately, 27 studies met the criteria and were included in the final analysis. The focus of these studies was on the various RAGT systems and their role in promoting gait and balance improvements. The results of these studies conclusively show that patients experience significant positive effects from RAGT, and when combined with other physiotherapy methods, the outcomes are notably superior in enhancing functional ambulation and motor skills. This review emphasizes RAGT's capability to deliver a more customized and effective rehabilitation experience, highlighting the importance of tailoring interventions to meet the specific needs of each patient.

Experimental evaluation of accuracy and efficiency of two control strategies for a novel foot commanded robotic laparoscope holders with surgeons.

The implementation of a laparoscope-holding robot in minimally invasive surgery enhances the efficiency and safety of the operation. However, the extra robot control task can increase the cognitive load on surgeons. A suitable interface may simplify the control task and reduce the surgeon load. Foot interfaces are commonly used for commanding laparoscope-holding robots, with two control strategies available: decoupled control permits only one Cartesian axis actuation, known as decoupled commands; hybrid control allows for both decoupled commands and multiple axes actuation, known as coupled commands. This paper aims to determine the optimal control strategy for foot interfaces by investigating two common assumptions in the literature: (1) Decoupled control is believed to result in better predictability of the final laparoscopic view orientation, and (2) Hybrid control has the efficiency advantage in laparoscope control. Our user study with 11 experienced and trainee surgeons shows that decoupled control has better predictability than hybrid control, while both approaches are equally efficient. In addition, using two surgery-like tasks in a simulator, users' choice of decoupled and coupled commands is analysed based on their level of surgical experience and the nature of the movement. Results show that trainee surgeons tend to issue more commands than the more experienced participants. Single decoupled commands were frequently used in small view adjustments, while a mixture of coupled and decoupled commands was preferred in larger view adjustments. A guideline for foot interface control strategy selection is provided.