Development of a Brain Controlled Assistive Feeding System with OpenBCI

Amyotrophic Lateral Sclerosis (ALS) Patients, individuals confined to respective homes, and those with upper limb disabilities frequently experience feeding issues and malnourishment.Asphyxia or choking can occur during feeding, which is frequently uncomfortable and time-consuming.Currently, these individuals are assisted in eating by robotic devices.All the same, persons with severe disabilities-such as sensory loss-or trouble with basic physical mobility should not employ assistive robots that need movement from the user.An amazing help in this area is a robotic system that is controlled only by brain signals.Therefore, a prototype of an electroencephalogram (EEG)-based feeding robot is proposed based on the specifications for a real-time helpful robot which is a Brain Computer Interface (BCI).An assistive technology called a feeding assistance robot is used to help people who are unable to independently move food from a container into their mouths.Feeding assistance robots have been introduced to help those who experience upper limb function loss due to cerebral palsy, spinal cord injuries, or amputations.These individuals may find it impossible to feed themselves.A set of experiments were carried out with healthy subjects to validate the proposed system and results are here presented.According to experimental data, the built system can do the necessary tasks in real-time with acceptable errors of an average of about 21% with a 77% overall accuracy for the system in performing the feeding of the users.With further supervision, this level of inaccuracy can be decreased or, in certain situations, completely eliminated.

Authors

Publication Details

Journal
Journal Européen des Systèmes Automatisés
Published
2025-02-28
DOI
https://doi.org/10.18280/jesa.580203
Primary Topic
Child Nutrition and Feeding Issues
Type
article
Field-Weighted Citation Impact
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article

Development of a Brain Controlled Assistive Feeding System with OpenBCI

Andrew L. Alexander, Sunday A. Afolalu, Ting Tin Tin, Olawale C. Ogunnigbo
Journal Européen des Systèmes Automatisés
Child Nutrition and Feeding Issues
article

Development of a Brain Controlled Assistive Feeding System with OpenBCI

Andrew L. Alexander, Sunday A. Afolalu, Ting Tin Tin, Olawale C. Ogunnigbo
article en

Abstract

Amyotrophic Lateral Sclerosis (ALS) Patients, individuals confined to respective homes, and those with upper limb disabilities frequently experience feeding issues and malnourishment.Asphyxia or choking can occur during feeding, which is frequently uncomfortable and time-consuming.Currently, these individuals are assisted in eating by robotic devices.All the same, persons with severe disabilities-such as sensory loss-or trouble with basic physical mobility should not employ assistive robots that need movement from the user.An amazing help in this area is a robotic system that is controlled only by brain signals.Therefore, a prototype of an electroencephalogram (EEG)-based feeding robot is proposed based on the specifications for a real-time helpful robot which is a Brain Computer Interface (BCI).An assistive technology called a feeding assistance robot is used to help people who are unable to independently move food from a container into their mouths.Feeding assistance robots have been introduced to help those who experience upper limb function loss due to cerebral palsy, spinal cord injuries, or amputations.These individuals may find it impossible to feed themselves.A set of experiments were carried out with healthy subjects to validate the proposed system and results are here presented.According to experimental data, the built system can do the necessary tasks in real-time with acceptable errors of an average of about 21% with a 77% overall accuracy for the system in performing the feeding of the users.With further supervision, this level of inaccuracy can be decreased or, in certain situations, completely eliminated.

Journal Européen des Systèmes AutomatisésVol. 58(2)
Zero hunger
Openalex Percentile: Top 93%
Child Nutrition and Feeding Issues
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