Designing for engagement

Caltenco, Héctor; Larsen, Henrik Svarrer

doi:10.1145/2639189.2670274

Cited by 9 publications

(1 citation statement)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, many MSE products have restricted engagement capabilities and may elicit a limited set of responses. Therefore, more versatile MSE devices that interreact safely through means such as touch [6], sounds [7], lights [8,9] while generating visual, auditory, or tactile feedback are demanded.…”

Section: Introductionmentioning

confidence: 99%

AI-Based Soft Module for Safe Human–Robot Interaction towards 4D Printing

et al. 2022

View full text Add to dashboard Cite

Soft robotic modules have potential use for therapeutic and educational purposes. To do so, they need to be safe, soft, smart, and customizable to serve individuals’ different preferences and personalities. A safe modular robotic product made of soft materials, particularly silicon, programmed by artificial intelligence algorithms and developed via additive manufacturing would be promising. This study focuses on the safe tactile interaction between humans and robots by means of soft material characteristics for translating physical communication to auditory. The embedded vibratory sensors used to stimulate touch senses transmitted through soft materials are presented. The soft module was developed and verified successfully to react to three different patterns of human–robot contact, particularly users’ touches, and then communicate the type of contact with sound. The study develops and verifies a model that can classify different tactile gestures via machine learning algorithms for safe human–robot physical interaction. The system accurately recognizes the gestures and shapes of three-dimensional (3D) printed soft modules. The gestures used for the experiment are the three most common, including slapping, squeezing, and tickling. The model builds on the concept of how safe human–robot physical interactions could help with cognitive and behavioral communication. In this context, the ability to measure, classify, and reflect the behavior of soft materials in robotic modules represents a prerequisite for endowing robotic materials in additive manufacturing for safe interaction with humans.

show abstract

Section: Introductionmentioning

confidence: 99%

AI-Based Soft Module for Safe Human–Robot Interaction towards 4D Printing

et al. 2022

View full text Add to dashboard Cite

show abstract

Design of a Multisensory Room for Elderly People with Neurodegenerative Diseases

et al. 2018

View full text Add to dashboard Cite

Developing a mobile activity game for stroke survivors—lessons learned

Magnusson

Rassmus-Gröhn

Rydeman

2020

J Multimodal User Interfaces

View full text Add to dashboard Cite

Persons who have survived a stroke might lower the risk of having recurrent strokes by adopting a healthier lifestyle with more exercise. One way to promote exercising is by fitness or exergame apps for mobile phones. Health and fitness apps are used by a significant portion of the consumers, but these apps are not targeted to stroke survivors, who may experience cognitive limitations (like fatigue and neglect), have problems with mobility due to hemiplegia, and balance problems. We outline the design process, implementation and user involvement in the design of an exergame app that is specifically targeted to stroke survivors, and present the lessons learned during the design process.

show abstract

Designing for engagement

Cited by 9 publications

References 4 publications

AI-Based Soft Module for Safe Human–Robot Interaction towards 4D Printing

AI-Based Soft Module for Safe Human–Robot Interaction towards 4D Printing

Design of a Multisensory Room for Elderly People with Neurodegenerative Diseases

Developing a mobile activity game for stroke survivors—lessons learned

Contact Info

Product

Resources

About