This work presents a method for recognition of walking activities and prediction of gait periods using wearable sensors. First, a Convolutional Neural Network (CNN) is used to recognise the walking activity and gait period. Second, the output of the CNN is used by a Predicted Information Gain (PIG) method to predict the next most probable gait period while walking. The output of these two processes are combined to adapt the recognition accuracy of the system. This adaptive combination allows us to achieve an optimal recognition accuracy over time.

Parents’ Views on Using Social Robots for Language Learning


**Session Chairs:** Valdés, Bulmaro A. (Simon Fraser University) and Ayub, Ali (The Pennsylvania State University)

Panel 16 - Detecting and Understanding Human Activity 2

panel

RO-MAN 2021's theme is trustworthiness and cooperation. We chose this term well before the pandemic put the world on edge and added a new reason for us to question our own personal safety when in the company of others. But what about in the company of social robots? What would cause us to trust, or not trust, them? How do we as researchers create that feeling, that critical component of any relationship? With social robots, it is of course largely in our power to design the physical form, the control code and the interface software to maximize trustworthiness, facilitate cooperation and enhance the quality of human-robot interaction. This theme also touches upon people's expectations and perceptions of robots, as well as other social, cognitive and cultural factors that will influence human-robot interactions. We will have a special session/track on this topic, invite targeted submissions and include plenary speakers who are specialist in this area. We sincerely hope that this focus will help enlighten the design-thinking of all of us as we fabricate and program our own various systems.

To access RO-MAN Virtual 2021, [please register here.](https://ro-man2021.org/registration/)

IEEE RO-MAN 2021

RO-MAN 2021's theme is trustworthiness and cooperation. We chose this term well before the pandemic put the world on edge and added a new reason for us to question our own personal safety when in the company of others. But what about in the company of social robots? What would cause us to trust, or not trust, them? How do we as researchers create that feeling, that critical component of any relationship? With social robots, it is of course largely in our power to design the physical form, the control code and the interface software to maximize trustworthiness, facilitate cooperation and enhance the quality of human-robot interaction. 

Uriel Martinez-Hernandez

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Parents’ Views on Using Social Robots for Language Learning

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