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Sensors (Basel). 2019 Feb 19;19(4). pii: E859. doi: 10.3390/s19040859.

A Human⁻Machine Interface Based on Eye Tracking for Controlling and Monitoring a Smart Home Using the Internet of Things.

Author information

1
Postgraduate Program in Electrical Engineering, Federal University of Espirito Santo (UFES), Vitoria 29075-910, Brazil. alexandre-bissoli@hotmail.com.
2
Electrical Engineering Department, Federal University of Espirito Santo (UFES), Vitoria 29075-910, Brazil. daniel_lavino@hotmail.com.
3
Postgraduate Program in Biotechnology, Federal University of Espirito Santo (UFES), Vitoria 29047-105, Brazil. mariana.midori@gmail.com.
4
Postgraduate Program in Electrical Engineering, Federal University of Espirito Santo (UFES), Vitoria 29075-910, Brazil. lucas@ele.ufes.br.
5
Electrical Engineering Department, Federal University of Espirito Santo (UFES), Vitoria 29075-910, Brazil. lucas@ele.ufes.br.
6
Postgraduate Program in Electrical Engineering, Federal University of Espirito Santo (UFES), Vitoria 29075-910, Brazil. teodiano.bastos@ufes.br.
7
Electrical Engineering Department, Federal University of Espirito Santo (UFES), Vitoria 29075-910, Brazil. teodiano.bastos@ufes.br.

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.

KEYWORDS:

Internet of Things (IoT); assistive technology; eye tracking; home automation; human–computer interaction (HCI); human–machine interface (HMI); smart home; usability evaluation; user-centered design (UCD)

PMID:
30791414
PMCID:
PMC6412435
DOI:
10.3390/s19040859
[Indexed for MEDLINE]
Free PMC Article

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