Evaluating the Child–Robot Interaction of the NAOTherapist Platform in Pediatric Rehabilitation

Ethical Considerations in Child-Robot Interactions

Social robots hold promise in augmenting education, rehabilitative care, and leisure activities for children. Despite findings suggesting various benefits of social robot use in schools, clinics, and homes, stakeholders have voiced concerns about the potential social and emotional effects of children engaging in long-term interactions with robots. Given the challenges of conducting large long-term studies of child-robot interaction (CRI), little is known about the impact of CRI on children's socio-emotional development. Here we summarize the literature on predictions and expectations of teachers, parents, therapists, and children regarding the effects of CRI on children's socio-emotional functioning and skill building. We then highlight the limited body of empirical research examining how CRI affects children's social behavior and emotional expression, and we provide a summary of available questionnaires for measuring socio-emotional constructs relevant to CRI. We conclude with design recommendations for research studies aimed at better understanding the effects of CRI, before social robots become more ubiquitous. This review is relevant to researchers, educators, roboticists, and clinicians interested in designing and using social robots with developmental populations.

Designing a cyber-physical robotic platform to assist speech-language pathologists

This research focused on the development of a cyber-physical robotic platform to assist speech-language pathologists who are related to articulation disorders in education environments. The first goal was the design and development of the system. The second goal was the qualitative initial validation of the platform with robotics and mobile device functionalities drawing on the participation of real patients and speech-language pathologists (SLP). The research method is based on qualitative data. The first phase was the application of engineering requirements and agile techniques to build the robotic system. The second phase was to execute test sessions of the robotic platform with speech-language pathologists supervision and analyzing the experience of real male and female patients collecting data by in-depth interviews and video recordings at Heredia Special Education Center in Costa Rica. The practical approach of the cyber-physical platform has preliminarily support. Testing with SLPs and 3 other older individuals suggests that it may become a useful tool to assist professionals in the treatment of some types of articulation disorders. The time savings and data collection possibilities should be included in future investigations of efficacy.

Are Retail Customers Ready for Service Robot Assistants?

The use of service robots is rapidly expanding in many industries, including the retail sector. In some Asian countries retail companies already deploy in-store humanoid robot assistants that interact with customers in a personalized and dynamic way. However, little is known about customers' perceptions of these robot-assisted interactions. Therefore, we compared customers' perceived service quality of a human-robot interaction with a human-human interaction in a retail store, using an experiment with hypothetical scenarios (N = 425). Participants' general attitudes towards robots, their age, gender, and educational level were included as moderators in the analyses (a mixed-design ANOVA model). Results showed that participants valued service quality higher in the human-human interaction scenario. Additionally, findings from the moderation analyses indicated that perceived service quality of the human- robot interaction and the human-human interaction did not statistically significantly differ for participants with relatively high positive attitudes towards robots. Participants with relatively low positive attitudes towards robots, however, held statistically significantly lower perceptions of service quality for the human-robot interaction. Neither age, gender nor educational level statistically significantly influenced participants' perceived service quality scores for both service encounters.

A Survey of Robotic Systems for Nursing Care

An increase of the aging population with a decrease in the available nursing staff has been seen in recent years. These two factors combined present a challenging problem for the future and has since become a political issue in many countries. Technological advances in robotics have made its use possible in new application fields like care and thus it appears to be a viable technological avenue to address the projected nursing labor shortage. The introduction of robots in nursing care creates an active triangular collaboration between the patient, nurse, and robot, which makes this area significantly different from traditional human–robot interaction (HRI) settings. In this review, we identify 133 robotic systems addressing nursing. We classify them according to two schemes: 1) a technical classification extended to include both patient and nurse and 2) a novel data-derived hierarchical classification based on use cases. We then analyze their intersection and build a multidimensional view of the state of technology. With this analytical tool, we describe an observed skew of the distribution of systems and identify gaps for future research. We also describe a link between the novel hierarchical use case classification and the typical phases of nursing care from admission to recovery.

Artificial Intelligence in Rehabilitation Targeting the Participation of Children and Youth With Disabilities: Scoping Review

BACKGROUND

In the last decade, there has been a rapid increase in research on the use of artificial intelligence (AI) to improve child and youth participation in daily life activities, which is a key rehabilitation outcome. However, existing reviews place variable focus on participation, are narrow in scope, and are restricted to select diagnoses, hindering interpretability regarding the existing scope of AI applications that target the participation of children and youth in a pediatric rehabilitation setting.

OBJECTIVE

The aim of this scoping review is to examine how AI is integrated into pediatric rehabilitation interventions targeting the participation of children and youth with disabilities or other diagnosed health conditions in valued activities.

METHODS

We conducted a comprehensive literature search using established Applied Health Sciences and Computer Science databases. Two independent researchers screened and selected the studies based on a systematic procedure. Inclusion criteria were as follows: participation was an explicit study aim or outcome or the targeted focus of the AI application; AI was applied as part of the provided and tested intervention; children or youth with a disability or other diagnosed health conditions were the focus of either the study or AI application or both; and the study was published in English. Data were mapped according to the types of AI, the mode of delivery, the type of personalization, and whether the intervention addressed individual goal-setting.

RESULTS

The literature search identified 3029 documents, of which 94 met the inclusion criteria. Most of the included studies used multiple applications of AI with the highest prevalence of robotics (72/94, 77%) and human-machine interaction (51/94, 54%). Regarding mode of delivery, most of the included studies described an intervention delivered in-person (84/94, 89%), and only 11% (10/94) were delivered remotely. Most interventions were tailored to groups of individuals (93/94, 99%). Only 1% (1/94) of interventions was tailored to patients' individually reported participation needs, and only one intervention (1/94, 1%) described individual goal-setting as part of their therapy process or intervention planning.

CONCLUSIONS

There is an increasing amount of research on interventions using AI to target the participation of children and youth with disabilities or other diagnosed health conditions, supporting the potential of using AI in pediatric rehabilitation. On the basis of our results, 3 major gaps for further research and development were identified: a lack of remotely delivered participation-focused interventions using AI; a lack of individual goal-setting integrated in interventions; and a lack of interventions tailored to individually reported participation needs of children, youth, or families.

Social Robots for (Second) Language Learning in (Migrant) Primary School Children

Especially these days, innovation and support from technology to relieve pressure in education is highly urgent. This study tested the potential advantage of a social robot over a tablet in (second) language learning on performance, engagement, and enjoyment. Shortages in primary education call for new technology solutions. Previous studies combined robots with tablets, to compensate for robot’s limitations, however, this study applied direct human–robot interaction. Primary school children (N = 63, aged 4–6) participated in a 3-wave field experiment with story-telling exercises, either with a semi-autonomous robot (without tablet, using WOz) or a tablet. Results showed increased learning gains over time when training with a social robot, compared to the tablet. Children who trained with a robot were more engaged in the story-telling task and enjoyed it more. Robot’s behavioral style (social or neutral) hardly differed overall, however, seems to vary for high versus low educational abilities. While social robots need sophistication before being implemented in schools, our study shows the potential of social robots as tutors in (second) language learning.

Infants born preterm and infants born full-term generate more selective leg joint movement during the scaffolded mobile task

Infants born very preterm (PT), prior to 32 weeks gestation, are at increased risk of developing cerebral palsy. Children with spastic cerebral palsy have impaired selective leg joint movement, which contributes to lifelong walking limitations. We investigated whether infants born PT generated more selective hip-knee joint movement (e.g., hip flexes as knee extends) while participating in a scaffolded mobile task. Infants born PT and infants born full-term (FT) at 4 months corrected age participated in a scaffolded mobile task for 2-3 consecutive days. The scaffolded mobile task required infants to raise their legs vertically over a virtual threshold. Three threshold heights (low, middle, and high) were used to test whether the middle and high heights encourage infants to move their legs more selectively. Fifteen infants born FT learned the task and showed more selective hip-knee movement at each of the three threshold heights on the day that they learned, compared with their baseline spontaneous kicking. Thirteen infants born PT learned the task and showed more selective hip-knee movement on their learning day, but only when the middle and high thresholds were used. The results show that the scaffolded mobile task effectively encouraged infants to generate more selective hip-knee joint movement.

Smiles as a Signal of Prosocial Behaviors Toward the Robot in the Therapeutic Setting for Children With Autism Spectrum Disorder

We explored how robot-assisted therapy based on smile analysis may facilitate the prosocial behaviors of children with autism spectrum disorder. Prosocial behaviors, which are actions for the benefit of others, are required to belong to society and increase the quality of life. As smiling is a candidate for predicting prosocial behaviors in robot-assisted therapy, we measured smiles by annotating behaviors that were recorded with video cameras and by classifying facial muscle activities recorded with a wearable device. While interacting with a robot, the participants experienced two situations where participants' prosocial behaviors are expected, which were supporting the robot to walk and helping the robot from falling. We first explored the overall smiles at specific timings and prosocial behaviors. Then, we explored the smiles triggered by a robot and behavior changes before engaging in prosocial behaviors. The results show that the specific timing of smiles and prosocial behaviors increased in the second session of children with autism spectrum disorder. Additionally, a smile was followed by a series of behaviors before prosocial behavior. With a proposed Bayesian model, smiling, or heading predicted prosocial behaviors with higher accuracy compared to other variables. Particularly, voluntary prosocial behaviors were observed after smiling. The findings of this exploratory study imply that smiles might be a signal of prosocial behaviors. We also suggest a probabilistic model for predicting prosocial behaviors based on smile analysis, which could be applied to personalized robot-assisted therapy by controlling a robot's movements to arouse smiles and increase the probability that a child with autism spectrum disorder will engage in prosocial behaviors.

Realizing the Potential of Robotics for Aged Care Through Co-Creation

Socially assistive robots have the potential to improve aged care by providing assistance through social interaction. While some evidence suggests a positive impact of social robots on measures of well-being, the adoption of robotic technology remains slow. One approach to improve technology adoption is involving all stakeholders in the process of technology development using co-creation methods. To capture relevant stake holders' priorities and perceptions on the ethics of robotic companions, we conducted an interactive co-creation workshop at the 2019 Geriatric Services Conference in Vancouver, BC. The participants were presented with different portrayals of robotic companions in popular culture and answered questions about perceptions, expectations, and ethical concerns about the implementation of robotic technology. Our results reveal that the most pressing ethical concerns with robotic technology, such as issues related to privacy, are critical potential barriers to technology adoption. We also found that most participants agree on the types of tasks that robots should help with, such as domestic chores, communication, and medication reminders. Activities that robots should not help with, according to the stakeholders, included bathing, toileting, and managing finances. The perspectives that were captured contribute to a preliminary outline of the areas of importance for geriatric care stake holders in the process of ethical technology design and development.

Long-Term Social Human-Robot Interaction for Neurorehabilitation: Robots as a Tool to Support Gait Therapy in the Pandemic

COVID-19 pandemic has affected the population worldwide, evidencing new challenges and opportunities for several kinds of emergent and existing technologies. Social Assistive Robotics could be a potential tool to support clinical care areas, promoting physical distancing, and reducing the contagion rate. In this context, this paper presents a long-term evaluation of a social robotic platform for gait neurorehabilitation. The robot's primary roles are monitoring physiological progress and promoting social interaction with human distancing during the sessions. A clinical validation with ten patients during 15 sessions were conducted in a rehabilitation center located in Colombia. Results showed that the robot's support improves the patients' physiological progress by reducing their unhealthy spinal posture time, with positive acceptance. 65% of patients described the platform as helpful and secure. Regarding the robot's role within the therapy, the health care staff agreed (>95%) that this tool can promote physical distancing and it is highly useful to support neurorehabilitation throughout the pandemic. These outcomes suggest the benefits of this tool to be further implemented in the pandemic.

The design of Lil'Flo, a socially assistive robot for upper extremity motor assessment and rehabilitation in the community via telepresence

INTRODUCTION

We present Lil'Flo, a socially assistive robotic telerehabilitation system for deployment in the community. As shortages in rehabilitation professionals increase, especially in rural areas, there is a growing need to deliver care in the communities where patients live, work, learn, and play. Traditional telepresence, while useful, fails to deliver the rich interactions and data needed for motor rehabilitation and assessment.

METHODS

We designed Lil'Flo, targeted towards pediatric patients with cerebral palsy and brachial plexus injuries using results from prior usability studies. The system combines traditional telepresence and computer vision with a humanoid, who can play games with patients and guide them in a present and engaging way under the supervision of a remote clinician. We surveyed 13 rehabilitation clinicians in a virtual usability test to evaluate the system.

RESULTS

The system is more portable, extensible, and cheaper than our prior iteration, with an expressive humanoid. The virtual usability testing shows that clinicians believe Lil'Flo could be deployed in rural and elder care facilities and is more capable of remote stretching, strength building, and motor assessments than traditional video only telepresence.

CONCLUSIONS

Lil'Flo represents a novel approach to delivering rehabilitation care in the community while maintaining the clinician-patient connection.

A Framework for User Adaptation and Profiling for Social Robotics in Rehabilitation

Physical rehabilitation therapies for children present a challenge, and its success-the improvement of the patient's condition-depends on many factors, such as the patient's attitude and motivation, the correct execution of the exercises prescribed by the specialist or his progressive recovery during the therapy. With the aim to increase the benefits of these therapies, social humanoid robots with a friendly aspect represent a promising tool not only to boost the interaction with the pediatric patient, but also to assist physicians in their work. To achieve both goals, it is essential to monitor in detail the patient's condition, trying to generate user profile models which enhance the feedback with both the system and the specialist. This paper describes how the project NAOTherapist-a robotic architecture for rehabilitation with social robots-has been upgraded in order to include a monitoring system able to generate user profile models through the interaction with the patient, performing user-adapted therapies. Furthermore, the system has been improved by integrating a machine learning algorithm which recognizes the pose adopted by the patient and by adding a clinical reports generation system based on the QUEST metric.

GEARing smart environments for pediatric motor rehabilitation

BACKGROUND

There is a lack of early (infant) mobility rehabilitation approaches that incorporate natural and complex environments and have the potential to concurrently advance motor, cognitive, and social development. The Grounded Early Adaptive Rehabilitation (GEAR) system is a pediatric learning environment designed to provide motor interventions that are grounded in social theory and can be applied in early life. Within a perceptively complex and behaviorally natural setting, GEAR utilizes novel body-weight support technology and socially-assistive robots to both ease and encourage mobility in young children through play-based, child-robot interaction. This methodology article reports on the development and integration of the different system components and presents preliminary evidence on the feasibility of the system.

METHODS

GEAR consists of the physical and cyber components. The physical component includes the playground equipment to enrich the environment, an open-area body weight support (BWS) device to assist children by partially counter-acting gravity, two mobile robots to engage children into motor activity through social interaction, and a synchronized camera network to monitor the sessions. The cyber component consists of the interface to collect human movement and video data, the algorithms to identify the children's actions from the video stream, and the behavioral models for the child-robot interaction that suggest the most appropriate robot action in support of given motor training goals for the child. The feasibility of both components was assessed via preliminary testing. Three very young children (with and without Down syndrome) used the system in eight sessions within a 4-week period.

RESULTS

All subjects completed the 8-session protocol, participated in all tasks involving the selected objects of the enriched environment, used the BWS device and interacted with the robots in all eight sessions. Action classification algorithms to identify early child behaviors in a complex naturalistic setting were tested and validated using the video data. Decision making algorithms specific to the type of interactions seen in the GEAR system were developed to be used for robot automation.

CONCLUSIONS

Preliminary results from this study support the feasibility of both the physical and cyber components of the GEAR system and demonstrate its potential for use in future studies to assess the effects on the co-development of the motor, cognitive, and social systems of very young children with mobility challenges.

Designing and Evaluating the Face of Lil'Flo: an Affordable Social Rehabilitation Robot

We introduce Lil'Flo, an affordable robot for pediatric upper extremity rehabilitation. We present the design and fabrication methodology of the head and face of the robot, the central design element for emotional expression. Through a guided interview with 10 subjects, a number of faces which have a clear sentiment associated with them are identified. The data suggest that a digital face, characterized by eyes and a mouth, can express sadness, happiness, surprise, and mischievousness well, but that finer emotions, e.g., differentiating between happy and very happy can be difficult. The data fail to show that a robot with a dynamic face is viewed more positively than one with a static face. The results of numerical sentiment analysis and open ended questions provide a design direction for our face and a general idea of simple face designs which have a clear sentiment.

Child and parent perceptions of acceptability and therapeutic value of a socially assistive robot used during pediatric rehabilitation

Purpose: Socially assistive robots are emerging as a method of supporting the rehabilitation of children with physical disabilities. To date there has been no in-depth analysis of parent and child perspectives regarding the use of socially assistive robots for pediatric rehabilitation. The purpose of this study was to capture the experiences of parents and children who participated in a rehabilitation session with a socially assistive rehabilitation robot.Methods: An interpretivist qualitative design was used. Semi-structured interviews of five parent-child pairs were undertaken to examine their experiences during a rehabilitation session with the NAO robot. Interviews were analyzed using inductive thematic analysis.Results: Five themes were identified: 1) affective influence, 2) independence, 3) preference for human interaction, 4) accessibility of therapy and 5) familiarity with technology.Conclusion: Based on parent and child perspectives, the NAO robot is an acceptable complement to rehabilitation therapies. Children and parents perceived the NAO robot to have therapeutic value through its potential to enhance engagement, promote child independence during rehabilitation exercises and its potential support a rehabilitation program when a human therapist is not accessible.Implications for rehabilitationSocially assistive robots are an acceptable tool to support the delivery of exercise programs in pediatric rehabilitation.Therapists need to consider how to provide a positive affective experience during rehabilitation sessions, the use of socially assistive robots may be one method of doing this.When using socially assistive robots to support rehabilitation the individual needs and preferences of the child and family should be considered.Socially assistive robots may have a role in supporting home exercises programs; future work is needed to determine the feasibility of this.

Developing a Robot-Guided Interactive Simon Game for Physical and Cognitive Training

Enveloping cognitive or physical rehabilitation into a game highly increases the patients’ commitment with their treatment. Specially with children, keeping them motivated is a very time-consuming work, so therapists are demanding tools to help them with this task. NAOTherapist is a generic robotic architecture that uses Automated Planning techniques to autonomously drive noncontact upper-limb rehabilitation sessions for children with a humanoid NAO robot. Our aim is to develop more robotic games for this platform to enrich its variability and possibilities of interaction. The goal of this work is to present our first attempt to develop a different, more complex game that reuses the previous architecture. We contribute with the design description of a novel robotic Simon game that employs upper-limb poses instead of colors and could qualify as a cognitive and physical training. Statistics of evaluation tests with 14 adults and 56 children are displayed and the outcomes are analyzed in terms of human–robot interaction (HRI) quality. The results demonstrate the application-domain generalization capabilities of the NAOTherapist architecture and give an insight to further analyze the therapeutic benefits of the new developed Simon game.