Brain-computer interface and Arduino microcontroller family software interconnection solution

Madoš, Branislav; Ádám, Norbert; Hurtuk, Ján; Copjak, Marek

doi:10.1109/sami.2016.7423010

Cited by 17 publications

(5 citation statements)

References 8 publications

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“…Many papers released were related to the case when the brain and eye control of immobilized people work normally and can be employed to manage the smart home. The BCI with EEG non-invasive electrodes and a headset installation is broadly applied to manage smart home appliances using IoT techniques [4][5][6][7][8][9][10][11][12][13][14][15][16]. It is also important to personalize smart home interactions to help disabled people improve their daily life routines through solutions based on AI.…”

Section: Review Of the Literaturementioning

confidence: 99%

“…The EEG signals are transmitted via Bluetooth to the HC-05 module connected to the Arduino Mega board. The information about edge IoT devices [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19] is pre-sented to the disabled on the LCD 1602 display with an IIC adapter wired to the same Arduino Mega microcontroller. The double blink is used to detect an event where the disabled person chooses the option shown on display.…”

Section: Introductionmentioning

confidence: 99%

“…Analysis of the concepts and soft-/hardware solutions presented in [4][5][6][7][8][9][10][11][12][13][14][15][16] shows that none of them implement WBCI to control smart home appliances using IoT data protocol(s) along with budget EEG-based brain kit(s). The perspective approach is the WBCI based on the low-cost brainwave EEG sensor such as Sichiray TGAM and lightweight publish/subscribe IoT data protocol such as MQTT.…”

Section: Introductionmentioning

confidence: 99%

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Prototyping Smart Home for Immobilized People: Eeg/MQTT-Based Brain-to-Thing Communication

Zubov

Qureshi²,

Köse³

et al. 2022

RIC

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Context. Immobilized people face additional barriers in almost all areas of life, including simple operations like turning the light on/off and controlling the air conditioner. The object of the study was to develop the brain-to-thin communication of affordable priceto control the smart home appliances by immobilized people from neck to toes. Objective. The goal of the work is to manage smart home appliances via brain-to-thing communication with EEG non-invasive electrodes, edge IoT devices, and MQTT protocol if the brain and eye control of the disabled work normally. Method. A non-invasive Sichiray TGAM brainwave EEG sensor kit captures signals and then transmit them via Bluetooth to the HC-05 module connected to the Arduino Mega microcontroller. Information about edge IoT devices is presented to the disabled on the LCD 1602 display wired to the same Arduino Mega. The disabled person chooses the option shown on display via the double blink that is detected if the quality of signal equals zero and low/mid gamma waves are less than ten in three consecutive Bluetooth packets. Control commands are sent from Arduino Mega (MQTT publisher) to the edge IoT devices (MQTT subscribers) that analyze them and start a specific operation like opening a door and turning the alarm on/off. Results. Five females and five males of different ages from 8 to 59 years old examined the control of smart home appliances with the Sichiray TGAM brainwave sensor kit. Everyone successfully handled the Sichiray headset and showed satisfaction with the brain-to-thing system. Conclusions. In this work, a smart home concept for immobilized people was developed using the brain-to-thing approach and the MQTT communication between the MQTT publisher, Sichiray TGAM brainwave EEG sensor kit connected via Bluetooth to the Arduino Mega microcontroller, and edge IoT devices total priced at USD 150. The most likely prospect of the presented work is to produce the sample that is ready to market.

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Section: Review Of the Literaturementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Prototyping Smart Home for Immobilized People: Eeg/MQTT-Based Brain-to-Thing Communication

Zubov

Qureshi²,

Köse³

et al. 2022

RIC

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“…With this solution it is also important that, the modules need to be monitored from time to time [20]. The monitoring task can be done by an artificial load [21] (preferably with an electrical load), or with swapping the modules for a short period [22] (just for heating up or just until the time of measurement).…”

Section: Software Realizationmentioning

confidence: 99%

Concept of a Reliable Redundant Off-grid Power Supply Chain

Györök

Beszedes

2019

2019 IEEE 13th International Symposium on Applied Computational Intelligence and Informatics (SACI)

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Electricity plays an increasingly important role in today's civil, industrial, medical and military applications. For optimal operation, it is essential to diagnose and the state of the device's power supply. In the case of an offgrid power supply system, it is required to check the status of all modules of the power supply chain. In order to ensure dependability, the redundancy of the power supply chain modules are needful, especially in critical applications. This paper proposes a microcontroller based embedded solution, which measures the different parameters of the distinct modules, and controls the redundant electronic units of the power supply line, to improve the reliability of the redundant off-grid power supply chain.

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“…The low number of microcontroller input pin also represented as a limit during development. [19] This and the problem of sharing the SPI bus [20] led to the development of an improved model, which contains two controllers, these are working on separate tasks, but communicate with each other [21]. The first controller is responsible for communicating with the outside world and the user.…”

Section: F Changing Physical Propertiesmentioning

confidence: 99%

Reliable Presence and Intrusion Detection with Collaborative Sensor Modules in Electronic Property Protection Systems

Beszedes

2019

2019 IEEE 17th World Symposium on Applied Machine Intelligence and Informatics (SAMI)

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This article deals with components (that effectuate the electronic protection) of property protection systems. Within this, mostly with to delineate the electronic outdoor protection, the intrusion detection system and some possible additional functions of the access control system. The solutions presented here are aimed to keep the cost low from the viewpoint of hardware requirements, together with to take advantage of the software opportunities.

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Brain-computer interface and Arduino microcontroller family software interconnection solution

Cited by 17 publications

References 8 publications

Prototyping Smart Home for Immobilized People: Eeg/MQTT-Based Brain-to-Thing Communication

Prototyping Smart Home for Immobilized People: Eeg/MQTT-Based Brain-to-Thing Communication

Concept of a Reliable Redundant Off-grid Power Supply Chain

Reliable Presence and Intrusion Detection with Collaborative Sensor Modules in Electronic Property Protection Systems

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