Robotic Treatment Research Articles

The Future of Stroke Interventions.

Mechanical thrombectomy (MT) has revolutionized the treatment of large-vessel occlusion stroke and markedly improved patient outcomes. Unfortunately, there remains a large proportion of patients that do not benefit from this technology. This review takes a look at recent and upcoming technologies that may help to increase the number of MT-treated patients, thereby improving their outcomes. To that end, an overview of digital health solutions, innovative pharmacological treatment, and futuristic robotic endovascular interventions is provided.

A social robot intervention on depression, loneliness, and quality of life for Taiwanese older adults in long-term care.

To investigate the effect of a social robot intervention on depression, loneliness, and quality of life of older adults in long-term care (LTC) and to explore participants' experiences and perceptions after the intervention. A mixed-methods approach consisting of a single group, before and after quasi-experimental design, and individual interview. Twenty older adults with depression from four LTC facilities in Taiwan were recruited. Each participant participated in 8 weeks of observation and 8 weeks of intervention. In the observation stage, participants received usual care or activities without any research intervention. In the intervention stage, each participant was given a Paro (Personal Assistive RobOt) to keep for 24 hours, 7 days a week. The Geriatric Depression Scale, the UCLA Loneliness Scale Version 3, and the World Health Organization Quality of Life Questionnaire for older adults were administered at four time points. Individual qualitative interviews with thematic analysis followed. A repeated multivariate analysis of variance and Friedman's test showed no significant changes during the observation stage between T1 and T2 for depression and quality of life (p >.5). For the intervention stage, statistically significant changes in decreasing depression and loneliness and improving quality of life over time were identified. Three themes emerged from the interviews: (i) humanizing Paro through referring to personal experiences and engagement; (ii) increased social interaction with other people; and (iii) companionship resulting in improved mental well-being. There were significant improvements in mental well-being in using Paro. Further research may help us to understand the advantages of using a Paro intervention as depression therapy.

Wireless HROV Control with Compressed Visual Feedback Using Acoustic and RF Links

Underwater cooperative robotics offers the possibility to perform challenging intervention applications, such as recovering archeological objects as within the context of the MERBOTS research project, or grasping, transporting and assembly of big objects, using more than one mobile manipulator, as faced by the TWINBOT project. In order to enhance safety during the intervention, it is reasonable to avoid the umbilical, also giving more mobility to the robots, and enabling a broader set of cooperative movements. Several solutions, based on acoustic, radiofrequency (RF) or Visual Light Communication (VLC) have been proposed for underwater communications in the literature. This paper presents the architecture of an underwater wireless communication framework for the control of multiple semi-autonomous robots in cooperative interventions. The proposed framework is composed of several modules as the virtual reality interface using UWSim, the Underwater Multi-robot Cooperative Intervention Remote Control Protocol (UMCI-RCP) and a Generic Link Layer (GLL). UMCI-RCP allows the control of an underwater robot over limited communication links. UMCI-RCP integrates a progressive compression algorithm that provides visual feedback at a constant rate and ensures image reception even in channels with loses. The Time Division Multiple Access (TDMA) medium access strategy minimizes the jitter of transmitted packets. The GLL has been designed in order to provide support for multimodal transmission (i.e. acoustic, RF and VLC) and also to interface with the UWSim-NET simulator so that facilitates the experimentation either with a real or with a simulated modem. The possibility of exchange real and simulated devices in the proposed framework are demonstrated by means of a teleoperation experiment with a BlueROV equipped with the S100 RF modems. Hardware-In-the-Loop (HIL) capabilities are demonstrated repeating the experiment with the real modems and modeling the BlueROV, and also modeling both the modems and the BlueROV.

Personalized Robot Interventions for Autistic Children: An Automated Methodology for Attention Assessment

We propose a robot-mediated therapy and assessment system for children with autism spectrum disorder (ASD) of mild to moderate severity and minimal verbal capabilities. The objectives of the robot interaction sessions is to improve the academic capabilities of ASD patients by increasing the length and the quality of their attention. The system uses a NAO robot and an added mobile display to present emotional cues and solicit appropriate emotional responses. The interaction is semi-autonomous with minimal human intervention. Interaction occurs within an adaptive dynamic scenario composed of 13 sections. The scenario allows adaptive customization based on the attention score history of each patient. The attention score is autonomously generated by the system and depends on face attention and joint attention cues and sound responses. The scoring system allows us to prove that the customized interaction system increases the engagement and attention capabilities of ASD patients. After performing a pilot study, involving 6 ASD children, out of a total of 11 considered in the clinical setup, we conducted a long-term study. This study empirically proves that the proposed assessment system represents the attention state of the patient with 82.4% accuracy.

Design and analysis of a novel long-distance double tendon-sheath transmission device for breast intervention robots under MRI field

Cancer represents a major threat to human health. Magnetic resonance imaging (MRI) provides superior performance to other imaging-based examination methods in the detection of tumors and offers distinct advantages in biopsy and seed implantation. However, because of the MRI environment, the material requirements for actuating devices for the medical robots used in MRI are incredibly demanding. This paper describes a novel double tendon-sheath transmission device for use in MRI applications. LeBus grooves are used in the original transmission wheels, thus enabling the system to realize long-distance and large-stroke transmission with improved accuracy. The friction model of the transmission system and the transmission characteristics model of the novel tendon-sheath structure are then established. To address the problem that tension sensors cannot be installed in large-stroke transmission systems, a three-point force measurement method is used to measure and set an appropriate preload in the novel tendon-sheath transmission system. Additionally, experiments are conducted to verify the accuracy of the theoretical model and multiple groups of tests are performed to explore the transmission characteristics. Finally, the novel tendon-sheath transmission system is compensated to improve its accuracy and the experimental results acquired after compensation show that the system satisfies the design requirements.

Modeling engagement in long-term, in-home socially assistive robot interventions for children with autism spectrum disorders.

Socially assistive robotics (SAR) has great potential to provide accessible, affordable, and personalized therapeutic interventions for children with autism spectrum disorders (ASD). However, human-robot interaction (HRI) methods are still limited in their ability to autonomously recognize and respond to behavioral cues, especially in atypical users and everyday settings. This work applies supervised machine-learning algorithms to model user engagement in the context of long-term, in-home SAR interventions for children with ASD. Specifically, we present two types of engagement models for each user: (i) generalized models trained on data from different users and (ii) individualized models trained on an early subset of the user's data. The models achieved about 90% accuracy (AUROC) for post hoc binary classification of engagement, despite the high variance in data observed across users, sessions, and engagement states. Moreover, temporal patterns in model predictions could be used to reliably initiate reengagement actions at appropriate times. These results validate the feasibility and challenges of recognition and response to user disengagement in long-term, real-world HRI settings. The contributions of this work also inform the design of engaging and personalized HRI, especially for the ASD community.

Laser-Profiled Continuum Robot with Integrated Tension Sensing for Simultaneous Shape and Tip Force Estimation.

The development of miniaturized continuum robots has a wide range of applications in minimally invasive endoluminal interventions. To navigate inside tortuous lumens without impinging on the vessel wall and causing tissue damage or the risk of perforation, it is necessary to have simultaneous shape sensing of the continuum robot and its tip contact force sensing with the surrounding environment. Miniaturization and size constraint of the device have precluded the use of conventional sensing hardware and embodiment schemes. In this study, we propose the use of optical fibers for both actuation and tension/shape/force sensing. It uses a model-based method with structural compensation, allowing direct measurement of the cable tension near the base of the manipulator without increasing the dimensions. It further structurally filters out disturbances from the flexible shaft. In addition, a model is built by considering segment differences, cable interactions/cross talks, and external forces. The proposed model-based method can simultaneously estimate the shape of the manipulator and external force applied onto the robot tip. Detailed modeling and validation results demonstrate the accuracy and reliability of the proposed method for the miniaturized continuum robot for endoluminal intervention.

Child-Robot Collaborative Problem-Solving and the Importance of Child's Voluntary Interaction: A Developmental Perspective.

The emergence and development of cognitive strategies for the transition from exploratory actions towards intentional problem-solving in children is a key question for the understanding of the development of human cognition. Researchers in developmental psychology have studied cognitive strategies and have highlighted the catalytic role of the social environment. However, it is not yet adequately understood how this capacity emerges and develops in biological systems when they perform a problem-solving task in collaboration with a robotic social agent. This paper presents an empirical study in a human-robot interaction (HRI) setting which investigates children's problem-solving from a developmental perspective. In order to theoretically conceptualize children's developmental process of problem-solving in HRI context, we use principles based on the intuitive theory and we take into consideration existing research on executive functions with a focus on inhibitory control. We considered the paradigm of the Tower of Hanoi and we conducted an HRI behavioral experiment to evaluate task performance. We designed two types of robot interventions, “voluntary” and “turn-taking”—manipulating exclusively the timing of the intervention. Our results indicate that the children who participated in the voluntary interaction setting showed a better performance in the problem solving activity during the evaluation session despite their large variability in the frequency of self-initiated interactions with the robot. Additionally, we present a detailed description of the problem-solving trajectory for a representative single case-study, which reveals specific developmental patterns in the context of the specific task. Implications and future work are discussed regarding the development of intelligent robotic systems that allow child-initiated interaction as well as targeted and not constant robot interventions.

A Randomized Controlled Trial of an Intelligent Robotic Response to Joint Attention Intervention System.

Although there has been growing interest in utilizing robots for intervention in autism spectrum disorder (ASD), there have been very few controlled trials to assess the actual impacts of such systems on social communication vulnerabilities. This study reports a randomized controlled trial to investigate a robot-mediated response to joint attention intervention in a small (23 recruited; 20 completed) group of young children (average age = 2.54years) with ASD. Small and nonsignificant group differences were observed regarding improvements in response to joint attention skills within and beyond the intervention. The sample showed tremendous individual variability in response to the system. Results highlight the current challenges related to developing pragmatic, beneficial, and generalizable robotic intervention systems for the targeted population.

Comparisons between end-effector and exoskeleton rehabilitation robots regarding upper extremity function among chronic stroke patients with moderate-to-severe upper limb impairment

End-effector (EE) and exoskeleton (Exo) robots have not been directly compared previously. The present study aimed to directly compare EE and Exo robots in chronic stroke patients with moderate-to-severe upper limb impairment. This single-blinded, randomised controlled trial included 38 patients with stroke who were admitted to the rehabilitation hospital. The patients were equally divided into EE and Exo groups. Baseline characteristics, including sex, age, stroke type, brain lesion side (left/right), stroke duration, Fugl–Meyer Assessment (FMA)–Upper Extremity score, and Wolf Motor Function Test (WMFT) score, were assessed. Additionally, impairment level (FMA, motor status score), activity (WMFT), and participation (stroke impact scale [SIS]) were evaluated. There were no significant differences in baseline characteristics between the groups. After the intervention, improvements were significantly better in the EE group with regard to activity and participation (WMFT–Functional ability rating scale, WMFT–Time, and SIS–Participation). There was no intervention-related adverse event. The EE robot intervention is better than the Exo robot intervention with regard to activity and participation among chronic stroke patients with moderate-to-severe upper limb impairment. Further research is needed to confirm this novel finding.

A Novel Exoskeleton with Fractional Sliding Mode Control for Upper Limb Rehabilitation

SUMMARYThe robotic intervention has great potential in the rehabilitation of post-stroke patients to regain their lost mobility. In this paper, firstly, we present a design of a novel, 7 degree-of-freedom (DOF) upper limb robotic exoskeleton (u-Rob) that features shoulder scapulohumeral rhythm with a wide range of motions (ROM) compared to other existing exoskeletons. An ergonomic shoulder mechanism with two passive DOF was included in the proposed exoskeleton to provide scapulohumeral motion with corresponding full ROM. Also, the joints of u-Rob have more range of motions compared to its existing counterparts. Secondly, we propose a fractional sliding mode control (FSMC) to control u-Rob. Applying the Lyapunov theory to the proposed control algorithm, we showed the stability of it. To control u-Rob, FSMC has shown effectiveness to handle unmodeled dynamics (e.g. friction, disturbance, etc.) in terms of better tracking and chatter compared to traditional SMC.

Robots as Assistive Technology Tools to Enhance Cognitive Abilities and Foster Valuable Learning Experiences among Young Children With Autism Spectrum Disorder

This study examines the efficacy of robots as assistive technology (AT) learning tools for children with autism spectrum disorder (ASD). The study attempts to find answers to whether robots as assistive tools can (i) profoundly improve achievement in learning and (ii) provide valuable learning experiences among this group of children. Using LEGO Mindstorms EV3, a robot was built and programmed to teach the basic concept of place value in mathematics. Eight children with ASD, specifically, four females and four males, participated in the single case study, and six special education teachers took part in the interviews. The children participated in both traditional and robotic intervention lessons and were assessed at the end of each session. The results indicate a positive increase in content knowledge and an improved disposition toward learning, thus demonstrating the potential utilization of robots as AT tools for harnessing classroom learning. Data from the interviews with teachers highlighted four valuable learning experiences that occurred in the classrooms as a result of the robotic interventions; namely, with respect to young children with ASD, the AT (1) promoted interest and engagement, (2) increased attention and focus, (3) triggered interactions and communication, and (4) created a happy and fun learning environment.

Feasibility, acceptance, and impact of socially assistive robots in non-drug interventions with people with dementia: A scoping review

Feasibility, acceptance, and impact of socially assistive robots in non-drug interventions with people with dementia: A scoping review

Robotic Systems Involved in the Diagnosis of Neurodegenerative Diseases.

The continuing development of robotics on the one hand and, on the other hand, the estimated relative growth in the number of elderly individuals suffering from neurodegenerative diseases raises the question of which contribution these powerful systems could have to assist or even improve the diagnostic procedure. Up to now many research groups have designed protocols that use robotic systems that measure the performance of the subject through tracking tasks with and without a synchronized cognitive or motor task. Also, new robotic noninvasive technologies are designed for the diagnosis of neurodegenerative diseases, through the analysis of eye movements. These assessments can distinguish individuals with the disease from age-matched controls. The objective of this review is to evaluate the effects and efficiency of robot interventions in the diagnosis of these devastating neurological diseases.

Comparing the Effectiveness of Different Reinforcement Stimuli in a Robotic Therapy for Children With ASD

Recent research has shown reliability in robotic therapies for improvement in core impairments of autism. To improve the efficiency of communication using robots, this study evaluates the effectiveness of three different stimuli in a robotic intervention for children with autism spectrum disorder. Three different reinforcement stimuli presented in least-to-most (LTM) order introduced in this therapy using NAO robot are: visual (color variation), auditory and motion cues. The therapy was tested on 12 ASD children, 4 out of 12 children fall under mild category whereas 8 fall under the minimal category of autism. The experimentation was conducted for 2 months. Total 8 experiments were conducted with 1 trial per week. Total 12 cues were given per trial, 4 cues corresponding to each category. In total 96 cues were given per subject, 32 cues from each category. The results indicate a general trend for linking a particular autism category with the most effective stimulus for that category. It can be concluded that visual cue (color variation) is the most effective reinforcement stimulus for children with minimal autism as 8 out of 8 i.e., 100% were more responsive to visual cues whereas for children with mild autism category, 3 out of 4 i.e., 75% are more receptive towards the motion stimulus. The parameters used for assessment were joint attention and the time eye contact is maintained. Single factor ANOVA was used for the statistical analysis of results with alpha is 0.05 and p-value 0.0342, F value is 3.7456 and F critical value is 3.2834. The test was performed on 96 ( $8\times 12$ ) trails in total, therefore ensuring the significance and reliability of our results.

Latency of humanoid robotic intervention for individuals with autism spectrum disorders

Latency of humanoid robotic intervention for individuals with autism spectrum disorders

The influence of SRA programming on algorithmic thinking and self-efficacy using Lego robotics in two types of instruction

This study investigates the development of algorithmic thinking as a part of computational thinking skills and self-efficacy of primary school pupils using programmable robots in different instruction variants. Computational thinking is defined in the context of twenty-first century skills and describes processes involved in (re)formulating a problem in a way that a computer can process it. Programming robots offers specific affordances as it can be used to develop programs following a Sense-Reason-Act (SRA) cycle. The literature provides evidence that programming robots has the potential to enhance algorithmic thinking as a component of computational thinking. Specifically there are indications that pupils who use SRA-programming learn algorithmic skills better and achieve a higher level of self-efficacy in an open, scaffold learning environment than through direct instruction. In order to determine the influence of the instruction variant used, an experimental research design was made in which pupils solved algorithm-based mathematical problems (grid diagrams) in a preliminary measurement and their self-efficacy determined via a questionnaire. As an intervention, pupils learn to solve programming issues in pairs using “Lego NXT” robots and “Mindstorms” software in two instruction variants. The post-measurement consists of a Lego challenge, solving mathematical problems (grid diagrams), and a repeated self-efficacy questionnaire. This research shows an increase of our measures on algorithmic thinking dependent on the amount of SRA usage (though not significant). Programming using the SRA-cycle can be considered as the cause of the measured effect. The instruction variant used during the robotic intervention seems to play only a marginal role.

Developing a Parallel Robot for MRI-Guided Breast Intervention

In MRI-guided breast intervention, the biopsy procedure is carried out by manually inserting a biopsy gun. However, some lesions are barely accessible with conventional tools, and the imaging process must be repeated multiple times for a better insertion coordinate. In this paper, we present a parallel robot for MRI-guided breast intervention. The robot employs a nonmagnetic, compact design, and has a unique three-link-four-rotational (3-4R) parallel mechanism that can insert the biopsy gun from various angles. The robot is remotely driven by a cable-actuated system and piezo-electric motors. It can be safely operated inside MRI bores with promising biopsy needle targeting accuracy. Comparative experiments are performed to validate the kinematics and to evaluate the performance on repetitive accuracy, structural stiffness, cable tension, and magnetic resonance. The experimental results show that the robot satisfies the operational requirements and can provide effective assistance in clinical breast biopsy.

Practical formulation of obstacle avoidance in the Task-Priority framework for use in robotic inspection and intervention scenarios

This paper presents a new formulation of a reactive obstacle avoidance algorithm, in the Task-Priority framework, delivering a practical solution for obstacle avoidance between vehicle-manipulator systems and complex environments. The presented concepts were implemented on an intervention autonomous underwater vehicle (I-AUV) and tested in an underwater pipe structure inspection and valve turning scenario, in a test tank, using GIRONA500 with an ECA 5E Micro manipulator. The obstacle avoidance is treated as an inequality (set-based) task, which takes into account all obstacles that are interacting with the robot links. Both the robot and the obstacles are represented by spheres to allow for analytical formulation. However, the environment is wrapped with spheres based on its actual geometry stored as an Octomap, hence it can be represented at different resolutions. Depending on the type of the mission performed by the robot we defined two modes of operation: (1) Navigation and Inspection, and (2) Intervention. For each mode, the algorithm takes into account different number of key points at the I-AUV and a different resolution of the environment representation. Typically, for the Intervention mode the resolution is higher, to allow for more precise motion. We also present an escape point strategy in case of the robot getting stuck between obstacles.

Design, Modeling, and Evaluation of a Compact and Lightweight Needle End-effector with Simple Force-feedback Implementation for Robotic CT-guided Needle Interventions

We present a compact and lightweight two degrees-of-freedom (DOF) needle end-effector to be applied to a teleoperated needle interventional robotic system. The suggested needle end-effector is computerized tomography (CT)-compatible and easy to sterilize. Because the proposed needle end-effector can be attached to a robotic manipulator, the needle can translate into and rotate in the human body. In addition, a 1-axis load cell is attached to the needle end-effector to measure the longitudinal force applied to the needle. With this force measurement, force-feedback ability has been implemented in the entire master-slave robotic system. Basic performance tests of repeatability and maximum insertion force were performed. Several force-feedback experiments to determine free space response and contact response, as well as a discrimination test, were conducted. Through this verification process, the suggested needle end-effector was found to have potential for application in real environments that require robotic CT-guided needle interventions.