ArticleSensors (Basel, Switzerland)2019
A Human⁻Machine Interface Based on Eye Tracking for Controlling and Monitoring a Smart Home Using the Internet of Things.
Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Thrivaad: A Multilingual, Predictive Eye-Sign-Based AAC System Powered by Optimized Deep Learning.Sensors (Basel, Switzerland) · 2026Article
- Influence of Sleep Monitoring Terminal Displays-Related Factors on User Visual Perception via Eye-Tracking and Tasks.Journal of eye movement research · 2026Article
- Design of a user-centered intelligent shoe cabinet for smart home hygiene using Kano-AHP-TRIZ.Scientific reports · 2026Article
- Enhancing indoor monitoring of visually impaired people using temporal convolutional network with optimization model in IoT environment.Scientific reports · 2025Article
- Design of a Gaze-Controlled Interactive Art System for the Elderly to Enjoy Life.Sensors (Basel, Switzerland) · 2024Article
- A roadmap for improving data quality through standards for collaborative intelligence in human-robot applications.Frontiers in robotics and AI · 2024Article
- Development of a Framework for the Communication System Based on KNX for an Interactive Space for UX Evaluation.Sensors (Basel, Switzerland) · 2023Article
- Using synchronized eye movements to assess attentional engagement.Psychological research · 2023Article
- Clear Aligners and Smart Eye Tracking Technology as a New Communication Strategy between Ethical and Legal Issues.Life (Basel, Switzerland) · 2023Article
- Human-machine interface for two-dimensional steering control with the auricular muscles.Frontiers in neurorobotics · 2023Article
- An empirical study on the collaborative usability of age-appropriate smart home interface design.Frontiers in psychology · 2023Article
- Event-Related Potential-Based Brain-Computer Interface Using the Thai Vowels' and Numerals' Auditory Stimulus Pattern.Sensors (Basel, Switzerland) · 2022Article
- KlugOculus: A Vision-Based Intelligent Architecture for Security System.Computational intelligence and neuroscience · 2022Article
- Study on Smart Home Interface Design Characteristics Considering the Influence of Age Difference: Focusing on Sliders.Frontiers in psychology · 2022Article
- Sensors and Artificial Intelligence Methods and Algorithms for Human-Computer Intelligent Interaction: A Systematic Mapping Study.Sensors (Basel, Switzerland) · 2021Article
- Biosignal-Based Human-Machine Interfaces for Assistance and Rehabilitation: A Survey.Sensors (Basel, Switzerland) · 2021Review
- Article
- Toward graphene textiles in wearable eye tracking systems for human-machine interaction.Beilstein journal of nanotechnology · 2021Article
- Sensor Technology for Smart Homes.Sensors (Basel, Switzerland) · 2020Article
- Emotion Recognition Using Eye-Tracking: Taxonomy, Review and Current Challenges.Sensors (Basel, Switzerland) · 2020Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
People with severe disabilities may have difficulties when interacting with their home devices due to the limitations inherent to their disability. Simple home activities may even be impossible for this group of people. Although much work has been devoted to proposing new assistive technologies to improve the lives of people with disabilities, some studies have found that the abandonment of such technologies is quite high. This work presents a new assistive system based on eye tracking for controlling and monitoring a smart home, based on the Internet of Things, which was developed following concepts of user-centered design and usability. With this system, a person with severe disabilities was able to control everyday equipment in her residence, such as lamps, television, fan, and radio. In addition, her caregiver was able to monitor remotely, by Internet, her use of the system in real time. Additionally, the user interface developed here has some functionalities that allowed improving the usability of the system as a whole. The experiments were divided into two steps. In the first step, the assistive system was assembled in an actual home where tests were conducted with 29 participants without disabilities. In the second step, the system was tested with online monitoring for seven days by a person with severe disability (end-user), in her own home, not only to increase convenience and comfort, but also so that the system could be tested where it would in fact be used. At the end of both steps, all the participants answered the System Usability Scale (SUS) questionnaire, which showed that both the group of participants without disabilities and the person with severe disabilities evaluated the assistive system with mean scores of 89.9 and 92.5, respectively.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.