The independence of impairments in proprioception and visuomotor adaptation after stroke.

BACKGROUND: Proprioceptive impairments are common after stroke and are associated with worse motor recovery and poor rehabilitation outcomes. Motor learning may also be an important factor in motor recovery, and some evidence in healthy adults suggests that reduced proprioceptive function is associated with reductions in motor learning. It is unclear how impairments in proprioception and motor learning relate after stroke. Here we used robotics and a traditional clinical assessment to examine the link between impairments in proprioception after stroke and a type of motor learning known as visuomotor adaptation. METHODS: We recruited participants with first-time unilateral stroke and controls matched for overall age and sex. Proprioceptive impairments in the more affected arm were assessed using robotic arm position- (APM) and movement-matching (AMM) tasks. We also assessed proprioceptive impairments using a clinical scale (Thumb Localization Test; TLT). Visuomotor adaptation was assessed using a task that systematically rotated hand cursor feedback during reaching movements (VMR). We quantified how much participants adapted to the disturbance and how many trials they took to adapt to the same levels as controls. Spearman's rho was used to examine the relationship between proprioception, assessed using robotics and the TLT, and visuomotor adaptation. Data from healthy adults were used to identify participants with stroke who were impaired in proprioception and visuomotor adaptation. The independence of impairments in proprioception and adaptation were examined using Fisher's exact tests. RESULTS: Impairments in proprioception (58.3%) and adaptation (52.1%) were common in participants with stroke (n = 48; 2.10% acute, 70.8% subacute, 27.1% chronic stroke). Performance on the APM task, AMM task, and TLT scores correlated weakly with measures of visuomotor adaptation. Fisher's exact tests demonstrated that impairments in proprioception, assessed using robotics and the TLT, were independent from impairments in visuomotor adaptation in our sample. CONCLUSION: Our results suggest impairments in proprioception may be independent from impairments in visuomotor adaptation after stroke. Further studies are needed to understand factors that influence the relationship between motor learning, proprioception and other rehabilitation outcomes throughout stroke recovery.

Application of Robotics in Orthodontics: A Systematic Review.

Robotics has various applications in dentistry, particularly in orthodontics, although the potential use of these technologies is not yet clear. This review aims to summarize the application of robotics in orthodontics and clarify its function and scope in clinical practice. Original articles addressing the application of robotics in any area of orthodontic practice were included, and review articles were excluded. PubMed, Google Scholar, Scopus, and DOAJ were searched from June to August 2023. The risk of bias was established using the risk of bias in non-randomized studies (ROBINS) and certainty assessment tools following the grading of recommendations, assessment, development, and evaluation (GRADE) guidelines. A narrative synthesis of the data was generated and presented according to its application in surgical and non-surgical orthodontics. The search retrieved 2,106 articles, of which 16 articles were selected for final data synthesis of research conducted between 2011 and 2023 in Asia, Europe, and North America. The application of robotics in surgical orthodontics helps guide orthognathic surgeries by reducing the margin of error, but it does not replace the work of a clinician. In non-surgical orthodontics, robotics assists in performing customized bending of orthodontic wires and simulating orthodontic movements, but its application is expensive. The articles collected for this synthesis exhibited a low risk of bias and high certainty, and the results indicated that the advantages of the application of robotics in orthodontics outweigh the disadvantages. This project was self-financed, and a previous protocol was registered at the PROSPERO site (registration number: CRD42023463531).

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.

A fast and high precision multi-robot environment modeling based on M-BFSI: Bidirectional filtering and scene identification method.

This article designs and implements a fast and high-precision multi-robot environment modeling method based on bidirectional filtering and scene identification. To solve the problem of feature tracking failure caused by large angle rotation, a bidirectional filtering mechanism is introduced to improve the error-matching elimination algorithm. A global key frame database for multiple robots is proposed based on a pretraining dictionary to convert images into a bag of words vectors. The images captured by different sub-robots are compared with the database for similarity score calculation, so as to realize fast identification and search of similar scenes. The coordinate transformation from local map to global map and the cooperative SLAM exploration of multiple robots is completed by the best matching image and the transformation matrix. The experimental results show that the proposed algorithm can effectively close the predicted trajectory of the sub-robot, thus achieving high-precision collaborative environment modeling.

A Novel Retractable Robotic Device for Colorectal Endoscopic Submucosal Dissection.

Background/Aims: : Appropriate tissue tension and clear visibility of the dissection area using traction are essential for effective and safe endoscopic submucosal dissection (ESD). In this study, we developed a retractable robot-assisted traction device and evaluated its performance in colorectal ESD. Methods: : An experienced endoscopist performed ESD 18 times on an ex vivo porcine colon using the robot and 18 times using the conventional method. The outcome measures were procedure time, dissection speed, procedure-related adverse events, and blind dissection rate. Results: : Thirty-six colonic lesions were resected from ex vivo porcine colon samples. The total procedure time was significantly shorter in robot-assisted ESD (RESD) than in conventional ESD (CESD) (20.1±4.1 minutes vs 34.3±8.3 minutes, p<0.05). The submucosal dissection speed was significantly faster in the RESD group than in the CESD group (36.8±9.2 mm2/min vs 18.1±4.7 mm2/min, p<0.05). The blind dissection rate was also significantly lower in the RESD group (12.8%±3.4% vs 35.1%±3.9%, p<0.05). In an in vivo porcine feasibility study, the robotic device was attached to a colonoscope and successfully inserted into the proximal colon without damaging the colonic wall, and ESD was successfully performed. Conclusions: : The dissection speed and safety profile improved significantly with the retractable RESD. Thus, our robotic device has the potential to provide simple, effective, and safe multidirectional traction during colonic ESD.

Soft bioreactor systems: a necessary step toward engineered MSK soft tissue?

A key objective of tissue engineering (TE) is to produce in vitro funcional grafts that can replace damaged tissues or organs in patients. TE uses bioreactors, which are controlled environments, allowing the application of physical and biochemical cues to relevant cells growing in biomaterials. For soft musculoskeletal (MSK) tissues such as tendons, ligaments and cartilage, it is now well established that applied mechanical stresses can be incorporated into those bioreactor systems to support tissue growth and maturation via activation of mechanotransduction pathways. However, mechanical stresses applied in the laboratory are often oversimplified compared to those found physiologically and may be a factor in the slow progression of engineered MSK grafts towards the clinic. In recent years, an increasing number of studies have focused on the application of complex loading conditions, applying stresses of different types and direction on tissue constructs, in order to better mimic the cellular environment experienced in vivo. Such studies have highlighted the need to improve upon traditional rigid bioreactors, which are often limited to uniaxial loading, to apply physiologically relevant multiaxial stresses and elucidate their influence on tissue maturation. To address this need, soft bioreactors have emerged. They employ one or more soft components, such as flexible soft chambers that can twist and bend with actuation, soft compliant actuators that can bend with the construct, and soft sensors which record measurements in situ. This review examines types of traditional rigid bioreactors and their shortcomings, and highlights recent advances of soft bioreactors in MSK TE. Challenges and future applications of such systems are discussed, drawing attention to the exciting prospect of these platforms and their ability to aid development of functional soft tissue engineered grafts.

Faster both in operative time and functional recovery by the extraperitoneal daVinci SP-based robot-assisted radical prostatectomy: a propensity score matching analysis compared to transperitoneal multiport counterpart.

We aim to investigate the peri-operative outcomes after extraperitoneal single-port based robot-assisted radical prostatectomy (eSP-RARP) utilizing the da Vinci SP system compared to conventional transperitoneal multi-port counterparts (tMP-RARP), in an era when pelvic lymph node dissection (PNLD) was omitted for the node-negative case. With exclusion criteria of volume + 50 g, suspicious rectal invasion, and node-positive disease given relatively weak grasping power and limited range of motion from the current SP system, 50 consecutive patients (Since December 2021) with localized prostate cancer underwent eSP-RARP by a single urologist maintaining identical surgical technique for 100 consecutive tMP-RARP cases (Since December 2020). Given initial selection criteria, each group was matched to a 1:1 ratio based on the risk-stratification parameters and the prostate volume. The operative time, which was maintained in each group during the study period, was significantly faster in eSP-RARP groups than in tMP-RARP (149.2 vs. 163.2 min, p = 0.025), while the weight of the removed specimen (27.1 vs. 29.0 g, p = 0.420) and margin positivity (14.7% vs. 11.7% in pT2, p = 0.812) were similar. The gas-out (1.5 vs. 1.88 days, p = 0.003) and solid diet dates (2.26 vs. 3.22 days, p < 0.001) were faster in the eSP-RARP group. The single-pad continence dates (30.5 vs. 51.9 days, p = 0.145) and zero-pad continence dates (105.5 vs. 146.2 days, p = 0.210) were identical. 90-day single-pad continence rate was 92% vs. 82% (p = 0.142, 52% vs. 56% in zero-pad continence). Based on these, daVinci SP-based RARP restored bowel function faster with shorter operative time through an extraperitoneal approach than the conventional transperitoneal multi-port counterpart while maintaining similar incontinence outcomes in cases without a routine PNLD.

Neural dynamics of robust legged robots.

Legged robot control has improved in recent years with the rise of deep reinforcement learning, however, much of the underlying neural mechanisms remain difficult to interpret. Our aim is to leverage bio-inspired methods from computational neuroscience to better understand the neural activity of robust robot locomotion controllers. Similar to past work, we observe that terrain-based curriculum learning improves agent stability. We study the biomechanical responses and neural activity within our neural network controller by simultaneously pairing physical disturbances with targeted neural ablations. We identify an agile hip reflex that enables the robot to regain its balance and recover from lateral perturbations. Model gradients are employed to quantify the relative degree that various sensory feedback channels drive this reflexive behavior. We also find recurrent dynamics are implicated in robust behavior, and utilize sampling-based ablation methods to identify these key neurons. Our framework combines model-based and sampling-based methods for drawing causal relationships between neural network activity and robust embodied robot behavior.

Evaluation of co-speech gestures grounded in word-distributed representation.

The condition for artificial agents to possess perceivable intentions can be considered that they have resolved a form of the symbol grounding problem. Here, the symbol grounding is considered an achievement of the state where the language used by the agent is endowed with some quantitative meaning extracted from the physical world. To achieve this type of symbol grounding, we adopt a method for characterizing robot gestures with quantitative meaning calculated from word-distributed representations constructed from a large corpus of text. In this method, a "size image" of a word is generated by defining an axis (index) that discriminates the "size" of the word in the word-distributed vector space. The generated size images are converted into gestures generated by a physical artificial agent (robot). The robot's gesture can be set to reflect either the size of the word in terms of the amount of movement or in terms of its posture. To examine the perception of communicative intention in the robot that performs the gestures generated as described above, the authors examine human ratings on "the naturalness" obtained through an online survey, yielding results that partially validate our proposed method. Based on the results, the authors argue for the possibility of developing advanced artifacts that achieve human-like symbolic grounding.

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.

Bimanual coordinated motor skill learning in patients with a chronic cerebellar stroke.

Cerebellar strokes induce coordination disorders that can affect activities of daily living. Evidence-based neurorehabilitation programs are founded on motor learning principles. The cerebellum is a key neural structure in motor learning. It is unknown whether and how well chronic cerebellar stroke individuals (CCSIs) can learn to coordinate their upper limbs through bimanual motor skill learning. The aim was to determine whether CCSIs could achieve bimanual skill learning through a serious game with the REAplan® robot and to compare CCSIs with healthy individuals (HIs). Over three consecutive days, sixteen CCSIs and eighteen HIs were trained on an asymmetric bimanual coordination task ("CIRCUIT" game) with the REAplan® robot, allowing quantification of speed, accuracy and coordination. The primary outcomes were the bimanual speed/accuracy trade-off (BiSAT) and bimanual coordination factor (BiCo). They were also evaluated on a bimanual REACHING task on Days 1 and 3. Correlation analyses between the robotic outcomes and clinical scale scores were computed. Throughout the sessions, BiSAT and BiCo improved during the CIRCUIT task in both HIs and CCSIs. On Day 3, HIs and CCSIs showed generalization of BiSAT, BiCo and transferred to the REACHING task. There was no significant between-group difference in progression. Four CCSIs and two HIs were categorized as "poor learners" according to BiSAT and/or BiCo. Increasing age correlated with reduced BiSAT but not BiCo progression. Over three days of training, HIs and CCSIs improved, retained, generalized and transferred a coordinated bimanual skill. There was no between-group difference, suggesting plastic compensation in CCSIs. Clinical trial NCT04642599 approved the 24th of November 2020.

How does the status of errant robot affect our desire for contact? - The moderating effect of team interdependence.

Technological breakthroughs such as artificial intelligence and sensors make human-robot collaboration a reality. Robots with highly reliable, specialised skills gain informal status in collaborative teams, but factors such as unstructured work environments and task requirements make robot error inevitable. So how do status differences of errant robots affect the desire for contact, and do team characteristics also have an impact? This paper describes an intergroup experiment using the Experimental Vignette Method (EVM), based on the Expectation Violation Theory, 214 subjects were invited to test the following hypotheses: (1) Errant robot status has an influence on employees' desire for contact and support for robotics research through negative emotions; (2) Team interdependence is a boundary condition for the effect of errant robot status on negative emotions. This paper contributes to the literature on employee reactions to robot errors in human-robot collaboration and provides suggestions for robot status design.

Complex human-robot collaboration inevitably leads to the phenomenon of robot errors. Based on this, we used an Experimental Vignette Method and found that differences in robot status design and human-robot team design features significantly affect employees' cognitive psychology after robot errors and reduce the negative consequences.

Telestroke network to robotic telestroke network: How to upgrade regional stroke care to include remote robotics?

Objective: Selected patients with large vessel occlusion (LVO) strokes can benefit from endovascular therapy (EVT). However, the effectiveness of EVT is largely dependent on how quickly the patient receives treatment. Recent technological developments have led to the first neurointerventional treatments using robotic assistance, opening up the possibility of performing remote stroke interventions. Existing telestroke networks provide acute stroke care, including remote administration of intravenous thrombolysis (IVT). Therefore, the introduction of remote EVT in distant stroke centers requires an adaptation of the existing telestroke networks. The aim of this work was to propose a framework for centers that are potential candidates for telerobotics according to the resources currently available in these centers. Methods: In this paper, we highlight the future challenges for including remote robotics in telestroke networks. A literature review provides potential solutions. Results: Existing telestroke networks need to determine which centers to prioritize for remote robotic technologies based on objective criteria and cost-effectiveness analysis. Organizational challenges include regional coordination and specific protocols. Technological challenges mainly concern telecommunication networks. Conclusions: Specific adaptations will be necessary if regional telestroke networks are to include remote robotics. Some of these can already be put in place, which could greatly help the future implementation of the technology.

Artificial intelligence in respiratory care: Current scenario and future perspective.

BACKGROUND: This narrative review aims to explore the current state and future perspective of artificial intelligence (AI) in respiratory care. The objective is to provide insights into the potential impact of AI in this field. METHODS: A comprehensive analysis of relevant literature and research studies was conducted to examine the applications of AI in respiratory care and identify areas of advancement. The analysis included studies on remote monitoring, early detection, smart ventilation systems, and collaborative decision-making. RESULTS: The obtained results highlight the transformative potential of AI in respiratory care. AI algorithms have shown promising capabilities in enabling tailored treatment plans based on patient-specific data. Remote monitoring using AI-powered devices allows for real-time feedback to health-care providers, enhancing patient care. AI algorithms have also demonstrated the ability to detect respiratory conditions at an early stage, leading to timely interventions and improved outcomes. Moreover, AI can optimize mechanical ventilation through continuous monitoring, enhancing patient comfort and reducing complications. Collaborative AI systems have the potential to augment the expertise of health-care professionals, leading to more accurate diagnoses and effective treatment strategies. CONCLUSION: By improving diagnosis, AI has the potential to revolutionize respiratory care, treatment planning, and patient monitoring. While challenges and ethical considerations remain, the transformative impact of AI in this domain cannot be overstated. By leveraging the advancements and insights from this narrative review, health-care professionals and researchers can continue to harness the power of AI to improve patient outcomes and enhance respiratory care practices. IMPROVEMENTS: Based on the findings, future research should focus on refining AI algorithms to enhance their accuracy, reliability, and interpretability. In addition, attention should be given to addressing ethical considerations, ensuring data privacy, and establishing regulatory frameworks to govern the responsible implementation of AI in respiratory care.

Dielectric Elastomer Actuators with Enhanced Durability by Introducing a Reservoir Layer.

A Dielectric Elastomer Actuator (DEA) consists of electrodes with a dielectric layer between them. By controlling the design of the electrodes, voltage, and frequency, the operating range and speed of the DEA can be adjusted. These DEAs find applications in biomimetic robots, artificial muscles, and similar fields. When voltage is applied to the DEA, the dielectric layer undergoes compression and expansion due to electrostatic forces, which can lead to electrical breakdown. This phenomenon is closely related to the performance and lifespan of the DEA. To enhance stability and improve dielectric properties, a DEA Reservoir layer is introduced. Here, stability refers to the ability of the DEA to perform its functions even as the applied voltage increases. The Reservoir layer delays electrical breakdown and enhances stability due to its enhanced thickness. The proposed DEA in this paper is composed of a Reservoir layer and electrode layer. The Reservoir layer is placed between the electrode layers and is independently configured, not subjected to applied voltage like the electrode layers. The performance of the DEA was evaluated by varying the number of polymer layers in the Reservoir and electrode designs. Introducing the Reservoir layer improved the dielectric properties of the DEA and delayed electrical breakdown. Increasing the dielectric constant through the DEA Reservoir can enhance output characteristics in response to electrical signals. This approach can be utilized in various applications in wearable devices, artificial muscles, and other fields.

Autonomous control of an ultrasound probe for intra-operative ultrasonography using vision-based shape sensing of pneumatically attachable flexible rails.

PURPOSE: In robotic-assisted minimally invasive surgery, surgeons often use intra-operative ultrasound to visualise endophytic structures and localise resection margins. This must be performed by a highly skilled surgeon. Automating this subtask may reduce the cognitive load for the surgeon and improve patient outcomes. METHODS: We demonstrate vision-based shape sensing of the pneumatically attachable flexible (PAF) rail by using colour-dependent image segmentation. The shape-sensing framework is evaluated on known curves ranging from r = 30 to r = 110 mm, replicating curvatures in a human kidney. The shape sensing is then used to inform path planning of a collaborative robot arm paired with an intra-operative ultrasound probe. We execute 15 autonomous ultrasound scans of a tumour-embedded kidney phantom and retrieve viable ultrasound images, as well as seven freehand ultrasound scans for comparison. RESULTS: The vision-based sensor is shown to have comparable sensing accuracy with FBGS-based systems. We find the RMSE of the vision-based shape sensing of the PAF rail compared with ground truth to be 0.4975 ± 0.4169 mm. The ultrasound images acquired by the robot and by the human were evaluated by two independent clinicians. The median score across all criteria for both readers was '3-good' for human and '4-very good' for robot. CONCLUSION: We have proposed a framework for autonomous intra-operative US scanning using vision-based shape sensing to inform path planning. Ultrasound images were evaluated by clinicians for sharpness of image, clarity of structures visible, and contrast of solid and fluid areas. Clinicians evaluated that robot-acquired images were superior to human-acquired images in all metrics. Future work will translate the framework to a da Vinci surgical robot.

Self-Amputating and Interfusing Machines.

Biological organisms exhibit phenomenal adaptation through morphology-shifting mechanisms including self-amputation, regeneration, and collective behavior. For example, reptiles, crustaceans, and insects amputate their own appendages in response to threats. Temporary fusion between individuals enables collective behaviors, such as in ants that temporarily fuse to build bridges. The concept of morphological editing, involving the addition and subtraction of mass can be linked to modular robotics, wherein synthetic body morphology may be revised by rearranging parts. In this work, we  introduce a reversible cohesive interface made of thermoplastic elastomer that allows for strong attachment and easy detachment of distributed soft robot modules without direct human handling. The reversible joint boasts a modulus similar to materials commonly used in soft robotics, and can thus be distributed throughout soft robot bodies without introducing mechanical incongruities. To demonstrate utility, we  exploit the reversible joint in two embodiments: a soft quadruped robot that self-amputates a limb when stuck, and a cluster of three soft-crawling robots that fuse to cross a land-gap. This work points toward future robots capable of radical shape-shifting via changes in mass through autotomy and interfusion, as well as highlighting the crucial role that interfacial stiffness change plays in autotomizable biological and artificial systems. This article is protected by copyright. All rights reserved.

ROBOT-ASSISTED TARGETED GAIT TRAINING.

Background: Millions of people are affected yearly by "runner's knee" and osteoarthritis, which is thought to be related to impact force. Millions are also affected by chronic falling, who are usually both difficult to identify and train. While at first glance, these topics seem to be entirely disconnected, there appears to be a need for a device that would address both issues. This paper proposes and investigates the use of the Variable Stiffness Treadmill (VST) as a targeted training device for the different populations described above. Materials and Methods: The VST is the authors' unique robotic split-belt treadmill that can reduce the vertical ground stiffness of the left belt, while the right belt remains rigid. In this work, heart rate and energy expenditure are measured for healthy subjects in the challenging asymmetric environment created by the VST and compared to a traditional treadmill setting. Results: This study shows that this asymmetric environment results in an increase in heart rate and energy expenditure, an increase in activity in the muscles about the hip and knee, and a decrease in impact force at heel strike. Conclusions: Compliant environments, like those created on the VST, may be a beneficial tool as they can: reduce high-impact forces during running and walking, significantly engage the muscles surrounding the hip and knee allowing for targeted training and rehabilitation, and assist in identifying and training high fall-risk individuals.

School-age children are more skeptical of inaccurate robots than adults.

We expect children to learn new words, skills, and ideas from various technologies. When learning from humans, children prefer people who are reliable and trustworthy, yet children also forgive people's occasional mistakes. Are the dynamics of children learning from technologies, which can also be unreliable, similar to learning from humans? We tackle this question by focusing on early childhood, an age at which children are expected to master foundational academic skills. In this project, 168 4-7-year-old children (Study 1) and 168 adults (Study 2) played a word-guessing game with either a human or robot. The partner first gave a sequence of correct answers, but then followed this with a sequence of wrong answers, with a reaction following each one. Reactions varied by condition, either expressing an accident, an accident marked with an apology, or an unhelpful intention. We found that older children were less trusting than both younger children and adults and were even more skeptical after errors. Trust decreased most rapidly when errors were intentional, but only children (and especially older children) outright rejected help from intentionally unhelpful partners. As an exception to this general trend, older children maintained their trust for longer when a robot (but not a human) apologized for its mistake. Our work suggests that educational technology design cannot be one size fits all but rather must account for developmental changes in children's learning goals.