Eye gaze tracking to operate android-based communication helper application

Cristanti, Retno Yuli; Sigit, Riyanto; Harsono, Tri; Adelina, Dyah Ceni; Nabilah, Anisah; Anggraeni, Novita Putri

doi:10.1109/kcic.2017.8228569

Cited by 12 publications

(2 citation statements)

References 7 publications

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“…However, the system was tested using a heat map on interfaces having only two targets. Cristanti [2017] proposed an eye gaze controlled Android system for people with SSMI using Haar Cascade for eye detection. However, the paper did not report any evaluation on pointing and selection times for users with SSMI and accuracy was only measured in terms of eye detection.…”

Section: Webcam Based Gaze Trackermentioning

confidence: 99%

Webcam controlled robotic arm for persons with SSMI

Sharma

Murthy

Saluja

et al. 2020

TAD

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BACKGROUND: People with severe speech and motor impairment (SSMI) often uses a technique called eye pointing to communicate with outside world. One of their parents, caretakers or teachers hold a printed board in front of them and by analyzing their eye gaze manually, their intentions are interpreted. This technique is often error prone and time consuming and depends on a single caretaker. OBJECTIVE: We aimed to automate the eye tracking process electronically by using commercially available tablet, computer or laptop and without requiring any dedicated hardware for eye gaze tracking. The eye gaze tracker is used to develop a video see through based AR (augmented reality) display that controls a robotic device with eye gaze and deployed for a fabric printing task. METHODS: We undertook a user centred design process and separately evaluated the web cam based gaze tracker and the video see through based human robot interaction involving users with SSMI. We also reported a user study on manipulating a robotic arm with webcam based eye gaze tracker. RESULTS: Using our bespoke eye gaze controlled interface, able bodied users can select one of nine regions of screen at a median of less than 2 secs and users with SSMI can do so at a median of 4 secs. Using the eye gaze controlled human-robot AR display, users with SSMI could undertake representative pick and drop task at an average duration less than 15 secs and reach a randomly designated target within 60 secs using a COTS eye tracker and at an average time of 2 mins using the webcam based eye gaze tracker. CONCLUSION: The proposed system allows users with SSMI to manipulate physical objects without any dedicated eye gaze tracker. The novelty of the system is in terms of non-invasiveness as earlier work mostly used glass based wearable trackers or head/face tracking but no other earlier work reported use of webcam based eye tracking for controlling robotic arm by users with SSMI.

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Section: Webcam Based Gaze Trackermentioning

confidence: 99%

Webcam controlled robotic arm for persons with SSMI

Sharma

Murthy

Saluja

et al. 2020

TAD

View full text Add to dashboard Cite

show abstract

“…Alguns estudos apontam a necessidade de desenvolvimento de aplicações voltadas para o público de baixa renda, fazendo uso de tecnologias de baixo custo, como é o caso de [24], onde os autores desenvolveram uma solução de TA com a webcam de um dispositivo Android com o intuito de operar um sistema de comunicação através de rastreamento ocular. Para Levy et al, é possível desenvolver soluções adaptativas altamente tecnológicas no intuito de solucionar problemas de pessoas com deficiência física severa.…”

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