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A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare

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Toward a Brain-Computer Interface- and Internet of Things-Based Smart Ward Collaborative System Using Hybrid Signals.

Xugang Cai¹, Jiahui Pan^1,2

¹School of Software, South China Normal University, Guangzhou 510631, China.

Journal of Healthcare Engineering

|April 28, 2022

Summary

This study introduces a smart ward system combining brain-computer interface (BCI) and Internet of Things (IoT) technologies. The hybrid BCI system, using EEG, EOG, and gyro signals, achieved high accuracy for improved patient care.

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Area of Science:

Biomedical Engineering
Human-Computer Interaction
Ubiquitous Computing

Background:

Traditional smart ward systems lack integrated BCI control.
Existing BCIs often struggle with accuracy and false operations.
Need for seamless integration of patient monitoring and control systems.

Purpose of the Study:

To develop a hybrid BCI and IoT system for smart ward collaboration.
To enhance BCI control accuracy using electroencephalography (EEG), electrooculography (EOG), and gyroscope (gyro) signals.
To establish an IoT architecture for efficient smart ward communication.

Main Methods:

A hybrid asynchronous BCI control system with a GUI paradigm for cursor movement.
User control via gyro for area selection and blink-related EOG for cursor clicks.
EEG signal classification using Support Vector Machine (SVM) for attention state judgment.
Development of an IoT monitoring and management system using Narrowband IoT (NB-IoT) technology.

Main Results:

The hybrid BCI control system achieved 96.65% ± 1.44% accuracy.
Low false operation rate (0.89 ± 0.42 events/min) and command response time (2.65 ± 0.48 s).
The NB-IoT based architecture demonstrated superior communication transmission quality.

Conclusions:

The proposed hybrid BCI system shows significant potential for application in daily tasks within smart wards.
The integrated BCI-IoT system offers a robust solution for collaborative smart ward environments.
This technology can improve patient interaction and monitoring efficiency in healthcare settings.