Evaluating the effects of humanoid robots on the story retelling skills of children on the autism spectrum

The current pilot study evaluated the effects of using a humanoid robot to help develop the perspective-taking skills of school-age children on the autism spectrum during story retelling. This current pilot study expands the use of humanoid robots to support story retelling for students on the autism spectrum. Outcomes of the study include a teacher guide to support schools and teachers interested in using a humanoid robot to support story retelling. This guide can also be used without a humanoid robot as the retelling of the story and the modelling of the language can be done by the teacher

Users’ Perceptions Toward mHealth Technologies for Health and Well-being Monitoring in Pregnancy Care: Qualitative Interview Study

BackgroundMobile health (mHealth) technologies, such as wearable sensors, smart health devices, and mobile apps, that are capable of supporting pregnancy care are emerging. Although mHealth could be used to facilitate the tracking of health changes during pregnancy, challenges remain in data collection compliance and technology engagement among pregnant women. Understanding the interests, preferences, and requirements of pregnant women and those of clinicians is needed when designing and introducing mHealth solutions for supporting pregnant women’s monitoring of health and risk factors throughout their pregnancy journey. ObjectiveThis study aims to understand clinicians’ and pregnant women’s perceptions on the potential use of mHealth, including factors that may influence their engagement with mHealth technologies and the implications for technology design and implementation. MethodsA qualitative study using semistructured interviews was conducted with 4 pregnant women, 4 postnatal women, and 13 clinicians working in perinatal care. ResultsClinicians perceived the potential benefit of mHealth in supporting different levels of health and well-being monitoring, risk assessment, and care provision in pregnancy care. Most pregnant and postnatal female participants were open to the use of wearables and health monitoring devices and were more likely to use these technologies if they knew that clinicians were monitoring their data. Although it was acknowledged that some pregnancy-related medical conditions are suitable for an mHealth model of remote monitoring, the clinical and technical challenges in the introduction of mHealth for pregnancy care were also identified. Incorporating appropriate health and well-being measures, intelligently detecting any abnormalities, and providing tailored information for pregnant women were the critical aspects, whereas usability and data privacy were among the main concerns of the participants. Moreover, this study highlighted the challenges of engaging pregnant women in longitudinal mHealth monitoring, the additional work required for clinicians to monitor the data, and the need for an evidence-based technical solution. ConclusionsClinical, technical, and practical factors associated with the use of mHealth to monitor health and well-being in pregnant women need to be considered during the design and feasibility evaluation stages. Technical solutions and appropriate strategies for motivating pregnant women are critical to supporting their long-term data collection compliance and engagement with mHealth technology during pregnancy

Sensor-Based Assessment of Social Isolation and Loneliness in Older Adults: A Survey

Social isolation (SI) and loneliness are ‘invisible enemies’. They affect older people’s health and quality of life and have significant impact on aged care resources. While in-person screening tools for SI and loneliness exist, staff shortages and psycho-social challenges fed by stereotypes are significant barriers to their implementation in routine care. Autonomous sensor-based approaches can be used to overcome these challenges by enabling unobtrusive and privacy-preserving assessments of SI and loneliness. This paper presents a comprehensive overview of sensor-based tools to assess social isolation and loneliness through a structured critical review of the relevant literature. The aim of this survey is to identify, categorise, and synthesise studies in which sensing technologies have been used to measure activity and behavioural markers of SI and loneliness in older adults. This survey identified a number of feasibility studies using ambient sensors for measuring SI and loneliness activity markers. Time spent out of home and time spent in different parts of the home were found to show strong associations with SI and loneliness scores derived from standard instruments. This survey found a lack of long-term, in-depth studies in this area with older populations. Specifically, research gaps on the use of wearable and smart phone sensors in this population were identified, including the need for co-design that is important for effective adoption and practical implementation of sensor-based SI and loneliness assessment in older adults

Working with a social robot in school: A long-term real-world unsupervised deployment

Interactive learning technologies, such as robots, increasingly find their way into schools. However, more research is needed to see how children might work with such systems in the future. This paper presents the unsupervised, four month deployment of a Robot-Extended Computer Assisted Learning (RECAL) system with 61 children working in their own classroom. Using automatically collected quantitative data we discuss how their usage patterns and self-regulated learning process developed throughout the study

EIT-Based Tactile Sensing Patches for Rehabilitation and Human Machine Interaction

We present the development of an innovative stretchable tac- tile sensor based on electrical impedance tomography (EIT) for appli- cations in wearable robotics and rehabilitation. To extract the tactile information we exploit the electrical impedance tomography technique to reconstruct the local conductivity changes of a piezoresistive fabric. The EIT method poses several new challenges in the reconstruction, counterbalanced by the overcoming of many of the drawbacks of the cur- rent tactile sensors. Results obtained are preliminary but encouraging and we believe that the combination of the EIT method with advanced machine learning techniques will enable reliable wearable tactile sensing

Skin-On Interfaces: A Bio-Driven Approach for Artificial Skin Design to Cover Interactive Devices

International audienceWe propose a paradigm called Skin-On interfaces, in which interactive devices have their own (artificial) skin, thus enabling new forms of input gestures for end-users (e.g. twist, scratch). Our work explores the design space of Skin-On interfaces by following a bio-driven approach: (1) From a sensory point of view, we study how to reproduce the look and feel of the human skin through three user studies; (2) From a gestural point of view, we explore how gestures naturally performed on skin can be transposed to Skin-On interfaces; (3) From a technical point of view, we explore and discuss different ways of fabricating interfaces that mimic human skin sensitivity and can recognize the gestures observed in the previous study; (4) We assemble the insights of our three exploratory facets to implement a series of Skin-On interfaces and we also contribute by providing a toolkit that enables easy reproduction and fabrication