An SSVEP based BCI to control a humanoid robot by using portable EEG device

Özgür, Arzu Güneysu; Akın, H. Levent

doi:10.1109/embc.2013.6611145

Cited by 57 publications

(38 citation statements)

References 8 publications

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“…Another possible interaction is the robot recognizing the emotions of the human, which could be measured and transmitted by the BCI device, and then reacting and learning from the human input. Even though both the BCI and the Sex Robots technology are not sophisticated enough yet, we should consider that this integration and application is real [40], and we must advance in studies related to ethical, moral, and social issues that may affect our future. Are we prepared to live with human-like robots and eventually fall in love and have sex with them?…”

Section: Current Usage Scenarios and Future Possibilitesmentioning

confidence: 99%

User Evaluation of the Neurodildo: A Mind-Controlled Sex Toy for People with Disabilities and an Exploration of Its Applications to Sex Robots

Gomes

2018

Robotics

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Abstract:In this paper, we present the Neurodildo, a sex toy remotely controlled by brain waves, which is pressure sensitive and has electrical stimulation (e-stim) feedback. The Neurodildo was originally presented as a conference paper at the 3rd International Congress on Love and Sex with Robots (2017). We designed and explored the application of a mind-controlled sex toy for the people with mobility disabilities, for example with spinal cord injury (SCI), who have difficulty handling a commercial toy and that might experience difficulties in a sexual encounter. The system consists of the sex toy with Bluetooth and sensors, the brain-computer interface (BCI) headset, the e-stim device, and a computer for running the necessary software. The first user wears the headset and the e-stim device, and by focusing in trained patterns, he/she can control the vibration of the sex toy. The pressure applied to the sex toy by the second user is measured by sensors and transmitted and converted to the first user, who feels muscle contractions. We discuss the design process, the limitations of the prototype and how evaluating the user requirements is necessary for a better product. We also included a background and discussion on the application of sex robots for assisting disabled people and how the Neurodildo could be integrated with this futuristic technology. The goal of this project is to design a sex toy that might help people with disabilities and people in long-distance relationships (LDR), trying to fill the gap of sex toys designed for people with disabilities.

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Section: Current Usage Scenarios and Future Possibilitesmentioning

confidence: 99%

User Evaluation of the Neurodildo: A Mind-Controlled Sex Toy for People with Disabilities and an Exploration of Its Applications to Sex Robots

Gomes

2018

Robotics

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“…Güneysu et al [20] control a humanoid robot with a panel of LEDs instead of a computer screen. Although the principle of displaying a set of possible commands on an LED matrix is identical to the principle used with computer screens, the choice of LEDs allows a better flexibility in the choice of frequencies.…”

Section: State Of the Artmentioning

confidence: 99%

Electroencephalography as implicit communication channel for proximal interaction between humans and robot swarms

Luca¹,

Karim

Mondada

2016

Swarm Intell

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Search and rescue, autonomous construction, and many other semi-autonomous multi-robot applications can benefit from proximal interactions between an operator and a swarm of robots. Most research on proximal interaction is based on explicit communication techniques such as gesture and speech. This study proposes a new implicit proximal communication technique to approach the problem of robot selection. We use electroencephalography (EEG) signals to select the robot at which the operator is looking. This is achieved using steady-state visually evoked potential (SSVEP), a repeatable neural response to a regularly blinking visual stimulus that varies predictively based on the blinking frequency. In our experiments, each robot was equipped with LEDs blinking at a different frequency, and the operator's SSVEP neural response was extracted from the EEG signal to detect and select the robot without requiring any conscious action by the user. This study systematically investigates several parameters affecting the SSVEP neural response: blinking frequency of the LED, distance between the robot and the operator, and color of the LED. Based on these parameters, we study two signal processing approaches and critically analyze their performance on 10 subjects controlling a set of physical robots. Our results show that despite numerous artifacts, it is possible to achieve a recognition rate higher than 85% on some subjects, while the average over the ten subjects was 75%.

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“…It has already proved its usability in many experiments (e.g. [12], [10], [13], [14]) and the price (about 700USD) is much more affordable than clinical-grade amplifiers (thousands of USD). The cap was put backwards, so that more electrodes were placed over the visual cortex.…”

Section: B Eeg Recordingmentioning

confidence: 99%

“…So far only a few studies utilizing low-cost EEG equipment have been performed. In [8], [9], and [10] an accuracy of 95%, 80% and 75% respectively was obtained for detecting frequencies below 15Hz. [11] evaluated 54 users applying frequencies in 6-24Hz range, and reported a maximum classification accuracy of 85% for the stimulus pair 8Hz and 10Hz.…”

Section: Introductionmentioning

confidence: 99%

A high frequency steady-state visually evoked potential based brain computer interface using consumer-grade EEG headset

Białas

Milanowski²

2014

2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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This work evaluates a possibility of creating a high-frequency, SSVEP-based brain computer interface using a low cost EEG recording hardware - an Emotiv EEG Neuro-headset. Both above aspects are crucial to enable deploying the BCI technology in the consumer market. High frequencies can be used to create a non-tiring and more pleasant interface. Commercial EEG systems, as the Emotiv EEG, although demonstrating large underperformance, are much more affordable than standard, clinical-grade EEG amplifiers. A system classifying between two stimuli and rest is designed and tested in two experiments: on five and ten subject respectively. First, the accuracy of the system is compared for frequencies in lower range (17Hz, 19Hz, 23Hz, 25Hz) and higher range (31Hz, 33Hz, 37Hz, 40Hz). The mean online accuracy is 80%±15% for the former and 67%±12% for the latter. Second, a more thorough investigation is done by evaluating the system for frequencies within a set of 35Hz-40Hz. Although the mean accuracy, 64% ± 22%, is relatively low, most of the users were able to achieve satisfying accuracy, with the mean reaching 82%±5%, which would allow for an efficient, and yet pleasant, usage of the BCI system. In each case a user dependent approach is applied, with a calibration session lasting about five minutes. EEG feature extraction is done using common spatial pattern (CSP) filtering, canonical correlation analysis (CCA), and linear discrimination analysis (LDA).

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An SSVEP based BCI to control a humanoid robot by using portable EEG device

Cited by 57 publications

References 8 publications

User Evaluation of the Neurodildo: A Mind-Controlled Sex Toy for People with Disabilities and an Exploration of Its Applications to Sex Robots

User Evaluation of the Neurodildo: A Mind-Controlled Sex Toy for People with Disabilities and an Exploration of Its Applications to Sex Robots

Electroencephalography as implicit communication channel for proximal interaction between humans and robot swarms

A high frequency steady-state visually evoked potential based brain computer interface using consumer-grade EEG headset

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