Long-Term Social Human-Robot Interaction for Neurorehabilitation: Robots as a Tool to Support Gait Therapy in the Pandemic
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ABSTRACT:
SUBMITTER: Cespedes N
PROVIDER: S-EPMC7959832 | biostudies-literature | 2021 Jan
REPOSITORIES: biostudies-literature
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Project description:Social learning is a powerful method for cultural propagation of knowledge and skills relying on a complex interplay of learning strategies, social ecology and the human propensity for both learning and tutoring. Social learning has the potential to be an equally potent learning strategy for artificial systems and robots in specific. However, given the complexity and unstructured nature of social learning, implementing social machine learning proves to be a challenging problem. We study one particular aspect of social machine learning: that of offering social cues during the learning interaction. Specifically, we study whether people are sensitive to social cues offered by a learning robot, in a similar way to children's social bids for tutoring. We use a child-like social robot and a task in which the robot has to learn the meaning of words. For this a simple turn-based interaction is used, based on language games. Two conditions are tested: one in which the robot uses social means to invite a human teacher to provide information based on what the robot requires to fill gaps in its knowledge (i.e. expression of a learning preference); the other in which the robot does not provide social cues to communicate a learning preference. We observe that conveying a learning preference through the use of social cues results in better and faster learning by the robot. People also seem to form a "mental model" of the robot, tailoring the tutoring to the robot's performance as opposed to using simply random teaching. In addition, the social learning shows a clear gender effect with female participants being responsive to the robot's bids, while male teachers appear to be less receptive. This work shows how additional social cues in social machine learning can result in people offering better quality learning input to artificial systems, resulting in improved learning performance.
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Project description:BackgroundThe worldwide population of older adults will soon exceed the capacity of assisted living facilities. Accordingly, we aim to understand whether appropriately designed robots could help older adults stay active at home.MethodsBuilding on related literature as well as guidance from experts in game design, rehabilitation, and physical and occupational therapy, we developed eight human-robot exercise games for the Baxter Research Robot, six of which involve physical human-robot contact. After extensive iteration, these games were tested in an exploratory user study including 20 younger adult and 20 older adult users.ResultsOnly socially and physically interactive games fell in the highest ranges for pleasantness, enjoyment, engagement, cognitive challenge, and energy level. Our games successfully spanned three different physical, cognitive, and temporal challenge levels. User trust and confidence in Baxter increased significantly between pre- and post-study assessments. Older adults experienced higher exercise, energy, and engagement levels than younger adults, and women rated the robot more highly than men on several survey questions.ConclusionsThe results indicate that social-physical exercise with a robot is more pleasant, enjoyable, engaging, cognitively challenging, and energetic than similar interactions that lack physical touch. In addition to this main finding, researchers working in similar areas can build on our design practices, our open-source resources, and the age-group and gender differences that we found.
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Project description:Human-robot interaction research has shown that social robots can interact with humans in complex social situations and display leadership-related behaviors. Therefore, social robots could be able to take on leadership roles. The aim of our study was to investigate human followers' perceptions and reactions towards robot leadership behavior, and differences based on the robot's displayed leadership style. We implemented a robot to show either a transformational or a transactional leadership style in its speech and its movements. We presented the robot to university and executive MBA students (N = 29) and subsequently conducted semi-structured interviews and group discussions. The results of explorative coding indicated that participants differed in their perceptions and reactions based on the robot's leadership style and based on their assumptions about robots in general. We observed that participants quickly imagined either a utopia or worried about a dystopia, depending on the robot's leadership style and their assumptions, and that a subsequent reflection led to more nuanced views. We discuss the implications and recommendations for human-robot interaction and leadership research.
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Project description:Human-robot interaction has extended its application horizon to simplify how human beings interact with each other through a remotely controlled telepresence robot. The fast growth of communication technologies such as 4G and 5G has elevated the potential to establish stable audio-video-data transmission. However, human-robot physical interactions are still challenging regarding maneuverability, controllability, stability, drive layout, and autonomy. Hence, this paper presents a systematic design and control approach based on the customer's needs and expectations of telepresence mobile robots for social interactions. A system model and controller design are developed using the Lagrangian method and linear quadratic regulator, respectively, for different scenarios such as flat surface, inclined surface, and yaw (steering). The robot system is capable of traveling uphill (30 ∘ ) and has a variable height (600-1200 mm). The robot is advantageous in developing countries to fill the skill gaps as well as for sharing knowledge and expertise using a virtual and mobile physical presence.
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Project description:In order to determine optimal training parameters for robot-assisted treadmill walking, it is essential to understand how a robotic device interacts with its wearer, and thus, how parameter settings of the device affect locomotor control. The aim of this study was to assess the effect of different levels of guidance force during robot-assisted treadmill walking on cortical activity. Eighteen healthy subjects walked at 2 km.h-1 on a treadmill with and without assistance of the Lokomat robotic gait orthosis. Event-related spectral perturbations and changes in power spectral density were investigated during unassisted treadmill walking as well as during robot-assisted treadmill walking at 30%, 60% and 100% guidance force (with 0% body weight support). Clustering of independent components revealed three clusters of activity in the sensorimotor cortex during treadmill walking and robot-assisted treadmill walking in healthy subjects. These clusters demonstrated gait-related spectral modulations in the mu, beta and low gamma bands over the sensorimotor cortex related to specific phases of the gait cycle. Moreover, mu and beta rhythms were suppressed in the right primary sensory cortex during treadmill walking compared to robot-assisted treadmill walking with 100% guidance force, indicating significantly larger involvement of the sensorimotor area during treadmill walking compared to robot-assisted treadmill walking. Only marginal differences in the spectral power of the mu, beta and low gamma bands could be identified between robot-assisted treadmill walking with different levels of guidance force. From these results it can be concluded that a high level of guidance force (i.e., 100% guidance force) and thus a less active participation during locomotion should be avoided during robot-assisted treadmill walking. This will optimize the involvement of the sensorimotor cortex which is known to be crucial for motor learning.
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Project description:For robots to become integrated into our daily environment, they must be designed to gain sufficient trust of both users and bystanders. This is in particular important for social robots including those that assume the role of a mediator, working towards positively shaping relationships and interactions between individuals. One crucial factor influencing trust is the appropriate handling of personal information. Previous research on privacy has focused on data collection, secure storage, and abstract third-party disclosure risks. However, robot mediators may face situations where the disclosure of private information about one person to another specific person appears necessary. It is not clear if, how, and to what extent robots should share private information between people. This study presents an online investigation into appropriate robotic disclosure strategies. Using a vignette design, participants were presented with written descriptions of situations where a social robot reveals personal information about its owner to support pro-social human-human interaction. Participants were asked to choose the most appropriate robot behaviors, which differed in the level of information disclosure. We aimed to explore the effects of disclosure context, such as the relationship to the other person and the information content. The findings indicate that both the information content and relationship configurations significantly influence the perception of appropriate behavior but are not the sole determinants of disclosure-adequacy perception. The results also suggest that expected benefits of disclosure and individual general privacy attitudes serve as additional influential factors. These insights can inform the design of future mediating robots, enabling them to make more privacy-appropriate decisions which could foster trust and acceptance.
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Project description:Introduction: The modern worldwide trend toward sedentary behavior comes with significant health risks. An accompanying wave of health technologies has tried to encourage physical activity, but these approaches often yield limited use and retention. Due to their unique ability to serve as both a health-promoting technology and a social peer, we propose robots as a game-changing solution for encouraging physical activity. Methods: This article analyzes the eight exergames we previously created for the Rethink Baxter Research Robot in terms of four key components that are grounded in the video-game literature: repetition, pattern matching, music, and social design. We use these four game facets to assess gameplay data from 40 adult users who each experienced the games in balanced random order. Results: In agreement with prior research, our results show that relevant musical cultural references, recognizable social analogues, and gameplay clarity are good strategies for taking an otherwise highly repetitive physical activity and making it engaging and popular among users. Discussion: Others who study socially assistive robots and rehabilitation robotics can benefit from this work by considering the presented design attributes to generate future hypotheses and by using our eight open-source games to pursue follow-up work on social-physical exercise with robots.
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Project description:This study aimed to determine the proportion of individuals who voluntarily reduced interaction with their family members, friends, and colleagues or classmates to avoid coronavirus disease 2019 (COVID-19) infection and the associations of reduced social interaction with perceived social support during the COVID-19 pandemic in Taiwan. Moreover, the related factors of voluntary reduction of social interaction were examined. We recruited participants via a Facebook advertisement. We determined the reduced social interaction, perceived social support, cognitive and affective constructs of health belief and demographic characteristics among 1954 respondents (1305 women and 649 men; mean age: 37.9 years with standard deviation 10.8 years). In total, 38.1% of respondents voluntarily reduced their social interaction with friends to avoid COVID-19 infection, 36.1% voluntarily reduced their interaction with colleagues or classmates, and 11.1% voluntarily reduced interaction with family members. Respondents who voluntarily reduced interaction with other people reported lower perceived social support than those who did not voluntarily reduce interaction. Respondents who were older and had a higher level of worry regarding contracting COVID-19 were more likely to voluntarily reduce interaction with family members, friends, and colleagues or classmates to avoid COVID-19 infection than respondents who were younger and had a lower level of worry regarding contracting COVID-19, respectively. The present study revealed that despite strict social distancing measures not being implemented in Taiwan, more than one-third of respondents voluntarily reduced their interaction with friends and colleagues or classmates. The general public should be encouraged to maintain social contacts through appropriately distanced in-person visits and telecommunication.
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Project description:We present a novel functional magnetic resonance imaging paradigm for second-person neuroscience. The paradigm compares a human social interaction (human-human interaction, HHI) to an interaction with a conversational robot (human-robot interaction, HRI). The social interaction consists of 1 min blocks of live bidirectional discussion between the scanned participant and the human or robot agent. A final sample of 21 participants is included in the corpus comprising physiological (blood oxygen level-dependent, respiration and peripheral blood flow) and behavioural (recorded speech from all interlocutors, eye tracking from the scanned participant, face recording of the human and robot agents) data. Here, we present the first analysis of this corpus, contrasting neural activity between HHI and HRI. We hypothesized that independently of differences in behaviour between interactions with the human and robot agent, neural markers of mentalizing (temporoparietal junction (TPJ) and medial prefrontal cortex) and social motivation (hypothalamus and amygdala) would only be active in HHI. Results confirmed significantly increased response associated with HHI in the TPJ, hypothalamus and amygdala, but not in the medial prefrontal cortex. Future analysis of this corpus will include fine-grained characterization of verbal and non-verbal behaviours recorded during the interaction to investigate their neural correlates. This article is part of the theme issue 'From social brains to social robots: applying neurocognitive insights to human-robot interaction'.
| S-EPMC6452252 | biostudies-literature
Project description:IntroductionThe reduction of the older people's self-sufficiency and the increase in the need for help in daily activities has a significant impact on the person and their caregivers. The primary objective of the GUARDIAN project is to enable the older people to live as long as possible at home, by means of the GUARDIAN socio-technical platform.Methodsand Analysis: The GUARDIAN platform consists of two connected apps: one dedicated to the caregiver (Caregiver App) and one dedicated to the older people (Senior App), plus a robot (Misty II), to provide coaching in an engaging modality. The study is designed as a technical feasibility pilot to test the GUARDIAN system on a group of older people.DiscussionsThe proposed solution reflects the real wants and needs of the older people person, increasing the acceptability of the system. In addition, the GUARDIAN project has the potential to have distinguished two phases of testing, so that changes can be made to the platform between the first and second phases, using data, both qualitative and quantitative, collected after the first phase.Ethics and disseminationThe study was approved by the Ethic Committee of the IRCCS INRCA. It was recorded in ClinicalTrials.gov on the number NCT05284292.
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