Design‑development of an at‑home modular brain–computer interface (BCI) platform in a case study of cervical spinal cord injury

Journal of NeuroEngineering and Rehabilitation, 2022 · DOI: 10.1186/s12984-022-01026-2 · Published: May 13, 2022

Simple Explanation

This study developed a portable, modular BCI platform usable at home by individuals with paralysis. The system allows users to control devices using brain signals, offering increased independence. The BCI system includes implanted electrodes, a wheelchair-mounted computer, a smartphone app, and a mechanical glove. It allows for easy switching of output devices to accomplish various tasks. The system is designed to be user-friendly, requiring minimal caregiver setup and no daily calibration. This facilitates the transition of BCI technology from the lab to the home environment.

Study Duration

14 Months

Participants

One subject with cervical spinal cord injury (C5 ASIA A)

Evidence Level

Case Study

Key Findings

1
Bluetooth data transmission delay between the minicomputer and mobile app averaged 23 ms.
2
The average setup time for the subject’s caregiver was approximately 5.6 minutes.
3
The trained motor imagery classifier maintained a median accuracy of 87.5% over 14 months without retraining.

Research Summary

This study presents a modular BCI system designed for at-home use, featuring a user-friendly mobile interface and plug-and-play compatibility with multiple end effectors. The system was tested on a subject with cervical spinal cord injury, demonstrating its feasibility and ease of setup by caregivers. Results indicate low latency in data transmission, rapid setup times, and sustained high accuracy of the motor imagery classifier over an extended period.

Practical Implications

Increased Independence

The at-home BCI system allows individuals with paralysis to perform daily tasks more independently.

Reduced Caregiver Burden

The system's ease of setup minimizes the assistance needed from caregivers.

Wider Accessibility

The modular design and user-friendly interface make BCI technology more accessible to a broader range of users.

Study Limitations

1
Python as the development language may not result in a completely OS agnostic platform.
2
The subject in the implementation presented here was able to use the App GUI on their own using their remnant bicep function. This generally limits the GUI’s use for less abled subjects.
3
Using the Activa PC + S and Nexus telemeter isn’t completely wireless.

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