Flexible, Personal Service Robot for ALS Patients

Rivera, Genessis Perez; Eichmann, Christian; Scherzinger, Stefan; Puck, L.; Roennau, Arne; Dillmann, Rüdiger

doi:10.1109/robio49542.2019.8961424

Cited by 2 publications

(1 citation statement)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…An attempt to develop an assistive system for a severe motor-impaired disable patients has seen increasing interest over the last few decades. Rivera et al [3] presented a new robotic assistant for disabled patients. Robot capabilities are easily integrated with existing computer interfaces.…”

Section: Introductionmentioning

confidence: 99%

Design and Development of an Assistive System Based on Eye Tracking

2022

View full text Add to dashboard Cite

This research concerns the design and development of an assistive system based on eye tracking, which can be used to improve the quality of life of disabled patients. With the use of their eye movement, whose function is not affected by their illness, patients are capable of communicating with and sending notifications to caretakers, controlling various appliances, including wheelchairs. The designed system is divided into two subsystems: stationary and mobile assistive systems. Both systems provide a graphic user interface (GUI) that is used to link the eye tracker with the appliance control. There are six GUI pages for the stationary assistive system and seven for the mobile assistive system. GUI pages for the stationary assistive system include the home page, smart appliance page, eye-controlled television page, eye-controlled air conditional page, i-speak page and entertainment page. GUI pages for the mobile assistive system are similar to the GUI pages for the stationary assistive system, with the additional eye-controlled wheelchair page. To provide hand-free secure access, an authentication based on facial landmarks is developed. The operational test of the proposed assistive system provides successful and promising results.

show abstract

Section: Introductionmentioning

confidence: 99%