Socially assistive robots (SARs) can act as caregivers and use touch gestures to interact with people such as children with autism. However, designing a touch perception system that can reliably detect these gestures remains a challenge. To address this gap, we replicated a Do-It-Yourself (DIY) skin-like sensor and evaluated its potential to identify eight social touch gestures: Fistbump, Hitting, Holding, Poking, Squeezing, Stroking, Tapping, and Tickling. Our sensor design builds on a recent silicone-based sensor to collect spatiotemporal gesture data and a load cell to capture force information. We collected touch gestures from 20 adults in a user study. Then, we built a touch perception algorithm with a Convolutional Neural Network-Long Short-Term Memory (CNN- LSTM) model, achieving 94% in gesture classification accuracy with to-fold validation and 69 % accuracy with subject-dependent splitting with the combined touch and force data.

This article provides an overview of the emergent area of facial emotion recognition (FER). Increasingly, videoconferencing applications are being used to bridge the geographic divide, as telecommuters have opted to work remotely (e.g. from home) during the COVID-19 pandemic. organizations have established business continuity programs that want to ensure that their remote workers are maintaining their health and well-being. As a result, some videoconferencing software can now perform FER, providing feedback to supervisors about how well their workforce is coping during these unprecedented times. What might such technologies mean for how people present in front of the camera? And how do these systems work? The significance of this paper is in presenting an end-to-end technological description of FER systems in the context of a “future of work” use case scenario presenting a working prototype developed by the authors and available on GitHub. The concepts of fairness and algorithmic bias in context is considered, before proceeding to address some of the human and social dimensions of these systems.

The current pandemic has demonstrated a lot of weak links in the social and economic fabric of the society. Addressing these issues is paramount to enable any successful discussion of smart city technologies. The health inequity and accompanying problems faced by the disabled community during the pandemic underlined that our current systems are not built for resiliency. it is important for us to understand what has been done towards solving this complex problem and where we could further allocate our resources to tackle this issue. It is important for us to understand what has been done towards solving this complex problem and where we could further allocate our resources to tackle this issue.