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A Human⁻Machine Interface Based on Eye Tracking for Controlling and Monitoring a Smart Home Using the Internet of Things.
Sensors (Basel). 2019 Feb 19; 19(4)S

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.

Authors+Show Affiliations

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

Pub Type(s)

Journal Article

Language

eng

PubMed ID

30791414

Citation

Bissoli, Alexandre, et al. "A Human⁻Machine Interface Based On Eye Tracking for Controlling and Monitoring a Smart Home Using the Internet of Things." Sensors (Basel, Switzerland), vol. 19, no. 4, 2019.
Bissoli A, Lavino-Junior D, Sime M, et al. A Human⁻Machine Interface Based on Eye Tracking for Controlling and Monitoring a Smart Home Using the Internet of Things. Sensors (Basel). 2019;19(4).
Bissoli, A., Lavino-Junior, D., Sime, M., Encarnação, L., & Bastos-Filho, T. (2019). A Human⁻Machine Interface Based on Eye Tracking for Controlling and Monitoring a Smart Home Using the Internet of Things. Sensors (Basel, Switzerland), 19(4). https://doi.org/10.3390/s19040859
Bissoli A, et al. A Human⁻Machine Interface Based On Eye Tracking for Controlling and Monitoring a Smart Home Using the Internet of Things. Sensors (Basel). 2019 Feb 19;19(4) PubMed PMID: 30791414.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - A Human⁻Machine Interface Based on Eye Tracking for Controlling and Monitoring a Smart Home Using the Internet of Things. AU - Bissoli,Alexandre, AU - Lavino-Junior,Daniel, AU - Sime,Mariana, AU - Encarnação,Lucas, AU - Bastos-Filho,Teodiano, Y1 - 2019/02/19/ PY - 2019/01/02/received PY - 2019/02/11/revised PY - 2019/02/12/accepted PY - 2019/2/23/entrez PY - 2019/2/23/pubmed PY - 2019/3/14/medline KW - Internet of Things (IoT) KW - assistive technology KW - eye tracking KW - home automation KW - human–computer interaction (HCI) KW - human–machine interface (HMI) KW - smart home KW - usability evaluation KW - user-centered design (UCD) JF - Sensors (Basel, Switzerland) JO - Sensors (Basel) VL - 19 IS - 4 N2 - 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. SN - 1424-8220 UR - https://www.unboundmedicine.com/medline/citation/30791414/A_Human⁻Machine_Interface_Based_on_Eye_Tracking_for_Controlling_and_Monitoring_a_Smart_Home_Using_the_Internet_of_Things_ L2 - https://www.mdpi.com/resolver?pii=s19040859 DB - PRIME DP - Unbound Medicine ER -