Harnessing the Power of Movement: A Body-Weight Support System & Assistive Robot Case Study.

Young children with motor disabilities face extra obstacles to engaging in movement and initiating social interaction. A body-weight support harness system (BWSS) allows a child to take steps, explore the environment, and interact with people and objects, but further research is needed to understand how this type of system can help children with motor disabilities. Assistive robots have the potential to keep a child engaged and motivated during physical therapy sessions with a BWSS. We conducted a case study over three and a half months to understand if the BWSS alone and if the BWSS with an assistive robot could promote child movement and engagement. Our results show that the child tended to increase their amount of movement over each session with the BWSS. The assistive robots used in this study also tended to keep the child engaged. The products of this work can benefit clinicians and researchers interested in early mobility intervention technologies, as well as roboticists working in the child mobility domain.

Deep Pressure Therapy: A Promising Anxiety Treatment for Individuals With High Touch Comfort?

One method for managing anxiety, a highly prevalent modern mental health condition, is the calming touch sensations of deep pressure therapy (DPT). Solutions for administering DPT include the Automatic Inflatable DPT (AID) Vest, which we designed in past work. Although benefits of DPT are clear in a subset of the related literature, these benefits are not ubiquitous. There is limited understanding of what factors lead to DPT success for a given user. In this work, we present the findings of a user study ( N = 25) that evaluates the effects of the AID Vest on anxiety. We compared physiological and self-reported measures of anxiety across Active (inflating) and Control (inactive) states of the AID Vest. In addition, we considered the presence of placebo effects and assessed participant comfort with social touch as a potential moderator. The results support our ability to reliably induce anxiety, and show that the Active AID Vest tended to reduce biosignals related to anxiety. We also found a significant relationship between comfort with social touch and reductions in self-reported state anxiety for the Active condition. Those who seek to successfully deploy DPT can benefit from this work.

How should robots exercise with people? Robot-mediated exergames win with music, social analogues, and gameplay clarity.

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.

Influence of a Socially Assistive Robot on Physical Activity, Social Play Behavior, and Toy-Use Behaviors of Children in a Free Play Environment: A Within-Subjects Study.

Background: Play is critical for children's physical, cognitive, and social development. Technology-based toys like robots are especially of interest to children. This pilot study explores the affordances of the play area provided by developmentally appropriate toys and a mobile socially assistive robot (SAR). The objective of this study is to assess the role of the SAR on physical activity, play behavior, and toy-use behavior of children during free play. Methods: Six children (5 females, Mage = 3.6 ± 1.9 years) participated in the majority of our pilot study's seven 30-minute-long weekly play sessions (4 baseline and 3 intervention). During baseline sessions, the SAR was powered off. During intervention sessions, the SAR was teleoperated to move in the play area and offered rewards of lights, sounds, and bubbles to children. Thirty-minute videos of the play sessions were annotated using a momentary time sampling observation system. Mean percentage of time spent in behaviors of interest in baseline and intervention sessions were calculated. Paired-Wilcoxon signed rank tests were conducted to assess differences between baseline and intervention sessions. Results: There was a significant increase in children's standing (∼15%; Z = -2.09; p = 0.037) and a tendency for less time sitting (∼19%; Z = -1.89; p = 0.059) in the intervention phase as compared to the baseline phase. There was also a significant decrease (∼4.5%, Z = -2.70; p = 0.007) in peer interaction play and a tendency for greater (∼4.5%, Z = -1.89; p = 0.059) interaction with adults in the intervention phase as compared to the baseline phase. There was a significant increase in children's interaction with the robot (∼11.5%, Z = -2.52; p = 0.012) in the intervention phase as compared to the baseline phase. Conclusion: These results may indicate that a mobile SAR provides affordances through rewards that elicit children's interaction with the SAR and more time standing in free play. This pilot study lays a foundation for exploring the role of SARs in inclusive play environments for children with and without mobility disabilities in real-world settings like day-care centers and preschools.

Toward Predicting Infant Developmental Outcomes From Day-Long Inertial Motion Recordings.

As improvements in medicine lower infant mortality rates, more infants with neuromotor challenges survive past birth. The motor, social, and cognitive development of these infants are closely interrelated, and challenges in any of these areas can lead to developmental differences. Thus, analyzing one of these domains - the motion of young infants - can yield insights on developmental progress to help identify individuals who would benefit most from early interventions. In the presented data collection, we gathered day-long inertial motion recordings from N = 12 typically developing (TD) infants and N = 24 infants who were classified as at risk for developmental delays (AR) due to complications at or before birth. As a first research step, we used simple machine learning methods (decision trees, k-nearest neighbors, and support vector machines) to classify infants as TD or AR based on their movement recordings and demographic data. Our next aim was to predict future outcomes for the AR infants using the same simple classifiers trained from the same movement recordings and demographic data. We achieved a 94.4% overall accuracy in classifying infants as TD or AR, and an 89.5% overall accuracy predicting future outcomes for the AR infants. The addition of inertial data was much more important to producing accurate future predictions than identification of current status. This work is an important step toward helping stakeholders to monitor the developmental progress of AR infants and identify infants who may be at the greatest risk for ongoing developmental challenges.

Exercising with Baxter: preliminary support for assistive social-physical human-robot interaction.

BACKGROUND: The 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. METHODS: Building 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. RESULTS: Only 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. CONCLUSIONS: The 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.

Teaching a Robot Bimanual Hand-Clapping Games via Wrist-Worn IMUs.

Colleagues often shake hands in greeting, friends connect through high fives, and children around the world rejoice in hand-clapping games. As robots become more common in everyday human life, they will have the opportunity to join in these social-physical interactions, but few current robots are intended to touch people in friendly ways. This article describes how we enabled a Baxter Research Robot to both teach and learn bimanual hand-clapping games with a human partner. Our system monitors the user's motions via a pair of inertial measurement units (IMUs) worn on the wrists. We recorded a labeled library of 10 common hand-clapping movements from 10 participants; this dataset was used to train an SVM classifier to automatically identify hand-clapping motions from previously unseen participants with a test-set classification accuracy of 97.0%. Baxter uses these sensors and this classifier to quickly identify the motions of its human gameplay partner, so that it can join in hand-clapping games. This system was evaluated by N = 24 naïve users in an experiment that involved learning sequences of eight motions from Baxter, teaching Baxter eight-motion game patterns, and completing a free interaction period. The motion classification accuracy in this less structured setting was 85.9%, primarily due to unexpected variations in motion timing. The quantitative task performance results and qualitative participant survey responses showed that learning games from Baxter was significantly easier than teaching games to Baxter, and that the teaching role caused users to consider more teamwork aspects of the gameplay. Over the course of the experiment, people felt more understood by Baxter and became more willing to follow the example of the robot. Users felt uniformly safe interacting with Baxter, and they expressed positive opinions of Baxter and reported fun interacting with the robot. Taken together, the results indicate that this robot achieved credible social-physical interaction with humans and that its ability to both lead and follow systematically changed the human partner's experience.

Effects of Grip-Force, Contact, and Acceleration Feedback on a Teleoperated Pick-and-Place Task.

The multifaceted human sense of touch is fundamental to direct manipulation, but technical challenges prevent most teleoperation systems from providing even a single modality of haptic feedback, such as force feedback. This paper postulates that ungrounded grip-force, fingertip-contact-and-pressure, and high-frequency acceleration haptic feedback will improve human performance of a teleoperated pick-and-place task. Thirty subjects used a teleoperation system consisting of a haptic device worn on the subject's right hand, a remote PR2 humanoid robot, and a Vicon motion capture system to move an object to a target location. Each subject completed the pick-and-place task 10 times under each of the eight haptic conditions obtained by turning on and off grip-force feedback, contact feedback, and acceleration feedback. To understand how object stiffness affects the utility of the feedback, half of the subjects completed the task with a flexible plastic cup, and the others used a rigid plastic block. The results indicate that the addition of grip-force feedback with gain switching enables subjects to hold both the flexible and rigid objects more stably, and it also allowed subjects who manipulated the rigid block to hold the object more delicately and to better control the motion of the remote robot's hand. Contact feedback improved the ability of subjects who manipulated the flexible cup to move the robot's arm in space, but it deteriorated this ability for subjects who manipulated the rigid block. Contact feedback also caused subjects to hold the flexible cup less stably, but the rigid block more securely. Finally, adding acceleration feedback slightly improved the subject's performance when setting the object down, as originally hypothesized; interestingly, it also allowed subjects to feel vibrations produced by the robot's motion, causing them to be more careful when completing the task. This study supports the utility of grip-force and high-frequency acceleration feedback in teleoperation systems and motivates further improvements to fingertip-contact-and-pressure feedback.