Related Experiment Video
Updated: Mar 10, 2026
06:34
A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare
Published on: July 7, 2023
3.4K
Smart Helmet: Wearable Multichannel ECG and EEG
Wilhelm Von Rosenberg1, Theerasak Chanwimalueang1, Valentin Goverdovsky1
1Imperial College London London SW7 2AZ U.K.
IEEE Journal of Translational Engineering in Health and Medicine
|December 14, 2016
Summary
This study demonstrates a smart helmet capable of simultaneously recording vital signs, including electrocardiogram (ECG) and respiration, alongside electroencephalogram (EEG) during physical activities. The system effectively handles motion artifacts, proving its feasibility for real-world applications.
Area of Science:
- Biomedical Engineering
- Wearable Technology
- Neuroscience
Background:
- Continuous vital sign monitoring is crucial for high-intensity activities.
- Existing wearable sensors can be inconvenient or impractical during activities like cycling or military engagement.
- Integrating sensors into helmets offers a convenient solution for simultaneous vital sign and electroencephalogram (EEG) monitoring.
Purpose of the Study:
- To investigate the feasibility of recording electrocardiogram (ECG), respiration, and EEG from face-lead locations using electrodes embedded in a standard helmet.
- To validate the accuracy of the helmet-based sensor system against traditional methods.
- To develop strategies for mitigating motion artifacts in real-world activity recordings.
Main Methods:
- Electrodes were embedded in a standard helmet at the lower jaw, mastoids, and forehead for ECG, respiration, and EEG recording.
- A respiration belt and chest-based ECG were used as ground truth for validation.
- EEG signals were verified using steady-state evoked potentials in response to visual and auditory stimuli.
- Subjects performed cycling and walking to simulate real-world conditions and test artifact reduction techniques.
Main Results:
- The study successfully recorded ECG, respiration, and EEG signals from the helmet-mounted electrodes.
- A novel multivariate R-peak detection algorithm was proposed and demonstrated effectiveness in noisy environments.
- The system showed feasibility in capturing physiological data during activities with significant motion artifacts.
- Validation confirmed the reliability of the helmet-based system for vital sign and EEG monitoring.
Conclusions:
- A smart helmet prototype capable of simultaneously recording vital signs and EEG has been successfully developed and tested.
- The proposed system offers a practical and convenient solution for physiological monitoring during demanding physical activities.
- The findings support the proof of concept for using smart helmets in diverse applications, from sports to military operations.
