Safety experiments for small robots investigating the potential of soft materials in mitigating the harm to the head due to impacts

There is a growing interest in social robots to be considered in the therapy of children with autism due to their effectiveness in improving the outcomes. However, children on the spectrum exhibit challenging behaviors that need to be considered when designing robots for them. A child could involuntarily throw a small social robot during meltdown and that could hit another person's head and cause harm (e.g. concussion). In this paper, the application of soft materials is investigated for its potential in attenuating head's linear acceleration upon impact. The thickness and storage modulus of three different soft materials were considered as the control factors while the noise factor was the impact velocity. The design of experiments was based on Taguchi method. A total of 27 experiments were conducted on a developed dummy head setup that reports the linear acceleration of the head. ANOVA tests were performed to analyze the data. The findings showed that the control factors are not statistically significant in attenuating the response. The optimal values of the control factors were identified using the signal-to-noise (S/N) ratio optimization technique. Confirmation runs at the optimal parameters (i.e. thickness of 3 mm and 5 mm) showed a better response as compared to other conditions. Designers of social robots should consider the application of soft materials to their designs as it help in reducing the potential harm to the head

Safe and Adaptive Social Robots for Children with Autism

Social robots are being considered to be a part of the therapy for children with autism due to the reported efficacy such technology in improving the outcomes. How ever, children diagnosed with autism exhibit challenging behaviors that could cause harm to themselves and to others around them. Throwing, hitting, kicking, and self harming are some examples of the challenging behaviors that were reported to occur among this population. The occurrence of such behaviors during the presence of a social robot could raise some safety concerns. For this reason, this research attempts toidentify the potential for harm due to the diffusion of social robots and investigate means to mitigate them. Considering the advancement in technology and the progress made in many computer science disciplines are making small and adaptable social robots a foreseeable possibility, the studies presented here focus on small robotic form factors.The first study quantities the potential harm to the head due to one of the identi?ed risky scenarios that might occur between a child and a social robot. The results re leaved that the overall harm levels based on the selected severity indices are relatively low compared to their respective thresholds. However, the investigation of harm due to throwing of a small social robot to the head revealed that it could potentially causet issue injuries, sub-concussive or even concussive events in extreme cases. The second two studies are aimed to make small robots safer by optimizing their design. Hence,studies are conducted investigating how robot design can be made safer by investigating different design factors. The study investigated the in?uence of the mass and shape on the linear acceleration of a developed dummy head. The results revealed that the two design factors considered (i.e. mass and shape) affected the resultant response. The second study investigated the in offence three different soft material sonthesa meresponse. The endings showed that the control factors considered are not statistically significant in attenuating the response. Finally, the last two studies attempt to make small robots more adaptable to promote safer interactions. This is carried out by em bedding the recognition of unwanted physical interactions into companion robot with the appropriate timing of responses. The findings of the first study highlight the pos sibility of characterizing children's negative interactions with robotic toys relying on accelerometer sensor. The second study showed that producing a late response to an action (i.e. greater than 1.0 s) could negatively affect the children's comprehension of the intended message. The work presented in this dissertation is multidisciplinary that involves the field of Mechanical Engineering and Information Technology

Influence of Reaction Time in the Emotional Response of a Companion Robot to a Child's Aggressive Interaction

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Influence of the shape and mass of a small robot when thrown to a dummy human head

Social robots have shown some efficacy in assisting children with autism and are now being considered as assistive tools for therapy. The physical proximity of a small companion social robot could become a source of harm to children with autism during aggressive physical interactions. A child exhibiting challenging behaviors could throw a small robot that could harm another child 0 s head upon impact. In this paper, we investigate the effects of the mass and the shape of objects thrown on impact at different impact velocities on the linear acceleration of a developed dummy head. This dummy head could be the head of another child or a caregiver in the room. A total of 27 main experiments were conducted based on Taguchi’s orthogonal array design. The data were then analyzed using ANOVA and signal-to-noise (S/N). Our results revealed that the two design factors considered (i.e. mass and shape) and the noise factor (i.e. impact velocities) affected the resultant response. Finally, confirmation runs at the optimal identified shape and mass (i.e. mass of 0.3 kg and shape of either cube or wedge) showed an overall reduction in the resultant peak linear acceleration of the dummy head as compared to the other conditions. These results have implications on the design and manufacturing of small social robots whereby minimizing the mass of the robots can aid in mitigating harm to the head due to impact

Reflex System for Intelligent Robotics

Background and Purpose: Great advances have occurred in the field of robotics in the past few years. The integration of robotics in our daily life became not only limited to manufacturing or industrial usage, but also in health care delivery, aerospace, humanitarian aids and others. Most of the existing robots systems rely on the programmer to set the rule it plays within the working environment or rely on a trainer to teach the system what should and need to be done and where they are ought to move. Other robotic systems might involve more intelligent systems to explore and handle tasks within their environment. Most of these systems are usually situated to work within well organized and planned environment. Having modifications on any of the parameters of the environment might produce unpredictable consequences. Depending on the complexity of the system and how intelligent it is, the consequences might be unfavorable in achieving the goals intended and reducing oneself-damages. Species in nature represents rich source of innovative ideas and creative concepts that can be investigated by researchers. Nature has been inspiring scientists into developing new ways of looking at things, by observing the various living organisms' behaviors in their own habitats. Behavior-based roboticists are concerned with the development of robots based on observing and the studying of neuroscience, psychology and ethology of animals in nature. Humans, animals and plants physiology is yet another rich source of researching potential (Fig. 1). For example, reflexes in living organisms represent a means of survival in the outer environment and means of regulating internal body operations. If we could observe and try to mimic some of the reflex behaviors, we could end up with a machine (E.g. Robots) that has the ability to avoid dangerous situations and keep the outer structure intact. Figure 1: The potential of reflex systems in intelligent robotics. Objective: Adopting an intelligent reflex system in the robot system similar to that found in humans, animals, and plants can have significant advantages on the overall behavior of the system. A reflex system can improve the risk avoiding capabilities in the unfavorable scenarios. Design: The approach toward reflex based robotic system involves the intensive investigation and review of the fundamental concepts found in the reflex systems of human, animals, and plants. Attention to details, such as the behavior of the organism when subjected to a certain stimulus and the latency it takes for the reflex arc to execute the right response, are among the most important things to consider when trying mimicking the behavior of a living organism. A deduced conceptual model should be based on the distinguishing components found in the reflex arc. An actual design based on this proposed model, will include the basic components that can be achieved by using electronic/mechanical components that are at the same time analogous in function to the ones found in the reflex arc. For example, to mimic the temperature sensing capabilities of a human hand, a simple one-point temperature sensor will not be sufficient to give a desirable realistic result. Instead, a sophisticated flexible array that is capable to sense the temperature at any point must be used. Another design consideration is the controlling method to be used. Will it be centralized or decentralized or a mix of both? Regardless of the answer the controlling mechanism involved should be independent of a central controller (i.e. the brain) and it must be localized to achieve the desirable fast response as that founded in the reflex arc. Conclusion: The reflex based robotic system will be unique and innovative for the applications intended. The system can be incorporated with pre-existing systems to add value especially in the field of medical robotics and more specifically in prosthetics. Artificial reflex systems will add great value, protective feature and life-like sensation for a smarter prosthetic artefacts. With the implementation of the reflex arc at the right latencies and order, the gap between artificial and the actual hand should get narrower.qscienc

Data on the impact of an object with different thicknesses of different soft materials at different impact velocities on a dummy head

The purpose of this data is to investigate the effect of different thicknesses of different soft materials samples added to an object on the resultant head acceleration of a developed dummy head upon impact. The object was a cylinder (10 * 10 cm2, diameter and height) and weighs 0.4 kg. The investigated materials were Ecoflex, Dragon Skin, and Clay while the thickness were 1 mm, 2 mm, 3 mm, and 5 mm. The velocities of the impacts for the 108 experiments were between 1 m/s and 3 m/s. Three severity indices (i.e. peak head linear acceleration, 3 ms criterion and the Head Injury Criterion (HIC)) were calculated from the raw acceleration data. The impact velocities were tabulated from the video recordings. A summary of the processed data and the raw data are included in this dataset. Online repository contains the files: https://doi.org/10.7910/DVN/TXOPUH. - 2019 The Author(s)The work is supported by a research grant from Qatar University under the grant No. QUST-1-CENG-2019-10 . The statements made herein are solely the responsibility of the authors. The authors declare that they have no conflict of interest.Scopu

Dataset for influence of visual and haptic feedback on the detection of threshold forces in a surgical grasping task

The data is related to minimal force thresholds perception in robotic surgical grasping applications. The experimental setup included an indenter-based haptic device acting on the fingertip of a participant and a visual system that displays grasping tasks by a surgical grasper. The experiments included the display of two presentations at different force levels (i.e., grasping and indentation) in three different modes, namely, visual-alone, haptic-alone, and bimodal (i.e., combined). For each mode, the participants were asked to identify which of the two presentations was higher. Each experiment was repeated till the termination conditions were met. Sixty participants took part in these experiments. The experiments were randomized and the threshold forces were calculated based on an algorthim. The datasets contain the individual responses of each participant, the threshold forces calculations, and the number of iterations

Heart Rate as a Predictor of Challenging Behaviours among Children with Autism from Wearable Sensors in Social Robot Interactions

Children with autism face challenges in various skills (e.g., communication and social) and they exhibit challenging behaviours. These challenging behaviours represent a challenge to their families, therapists, and caregivers, especially during therapy sessions. In this study, we have investigated several machine learning techniques and data modalities acquired using wearable sensors from children with autism during their interactions with social robots and toys in their potential to detect challenging behaviours. Each child wore a wearable device that collected data. Video annotations of the sessions were used to identify the occurrence of challenging behaviours. Extracted time features (i.e., mean, standard deviation, min, and max) in conjunction with four machine learning techniques were considered to detect challenging behaviors. The heart rate variability (HRV) changes have also been investigated in this study. The XGBoost algorithm has achieved the best performance (i.e., an accuracy of 99%). Additionally, physiological features outperformed the kinetic ones, with the heart rate being the main contributing feature in the prediction performance. One HRV parameter (i.e., RMSSD) was found to correlate with the occurrence of challenging behaviours. This work highlights the importance of developing the tools and methods to detect challenging behaviors among children with autism during aided sessions with social robots

Longitudinal Studies of Wearables in Patients with Diabetes: Key Issues and Solutions

Glucose monitoring is key to the management of diabetes mellitus to maintain optimal glucose control whilst avoiding hypoglycemia. Non-invasive continuous glucose monitoring techniques have evolved considerably to replace finger prick testing, but still require sensor insertion. Physiological variables, such as heart rate and pulse pressure, change with blood glucose, especially during hypoglycemia, and could be used to predict hypoglycemia. To validate this approach, clinical studies that contemporaneously acquire physiological and continuous glucose variables are required. In this work, we provide insights from a clinical study undertaken to study the relationship between physiological variables obtained from a number of wearables and glucose levels. The clinical study included three screening tests to assess neuropathy and acquired data using wearable devices from 60 participants for four days. We highlight the challenges and provide recommendations to mitigate issues that may impact the validity of data capture to enable a valid interpretation of the outcomes