Electroencephalography (EEG) Technology Applications and Available Devices
Abstract
:1. Introduction
2. EEG Device Design Technology
2.1. Connection Types
2.1.1. Wired and Wireless Communications
2.1.2. Electrode Connection
2.1.3. Wet EEG Devices
2.2. Differences between Dry and Wet Devices
2.3. Electrode Placement Standards
2.4. EEG Devices with Several Sensors
- ECG sensors record the heart’s response during resting or physical activity.
- EOG sensors measure human eye movements.
- PPG sensors monitor blood volume changes.
- EMG sensors collect muscle activity data.
3. Applications of EEG
- 1.
- Autonomous navigation of digital or mechatronic devices:
- 2.
- Helping people with disabilities or motor activity impairment:
- 3.
- Neurogaming and Entertainment
- Epilepsy [48];
- Parkinson’s Disease [49];
- Memory problems like Alzheimer’s [50];
- Language impairments such as Dyslexia [51];
- Attention Deficit Hyperactivity Disorder (ADHD) [52];
- Seizures [12];
- Schizophrenia [53];
- Anxiety [58];
- Post-traumatic stress disorder [10];
- Huntington’s disease [59];
- Multiple sclerosis diagnosis [60];
- Amyotrophic lateral sclerosis [61];
- Traumatic brain injury (TBI) [62];
- Coma [63];
- Level of consciousness [64];
- Neurosurgery [65].
- Cognitive neuroscience:
- Studying sleep pattern [72];
- Behavioral neuroscience:
- Changing the workplace light and measuring brain alertness status [73];
- Measuring drowsiness or sleep detection for drivers and pilots [74];
- Measuring mental workload of deaf children exposed to a noisy environment during a word recognition task [75];
- Determining surgeon stress level while performing surgery [76];
- Identifying and reducing stress level [77];
- Environmental Psychology [78].
- Neurophysiology:
4. EEG Headset Applications and Research Usages
5. Discussion
- Designing Technology Dry/Wet (saline or gel): Unfortunately, there are few studies done on this area. Recently, some researchers [35,37] compared a dry and wet headset for their research and they concluded that although the selected dry EEG headset was more robust to line noise, it contained more artifacts;
- Setup time: Regardless of the connection type being used, the setup time for EEG electrodes tends to be longer than for most physiological sensors. Saline-based sensors are usually selected for their ease of use and quick setup time, relative to gel-based sensors. Gel based EEG devices demand a larger amount of time, relative to other connection methods, to apply, while the saline headset does not take much time to set up. Cleaning saline headsets after using them takes less time than gel-based sensors. The gel also sticks to the hair of participants, which could be uncomfortable and inconvenient for users;
- Signal quality and stability: Quality of the captured EEG data depends on several factors: connection stability, losing connection with the scalp, and wireless, which are described below:
- Losing Connection with the Scalp: The quality of the recorded EEG data highly depends on the connection between electrodes and the scalp. Gel-based sensors are usually chosen for their stability of connection and longevity, as the wet or gel-based sensors maintain a more stable connection for several hours, while wet and dry EEG headsets may lose humidity during an experiment, which can lead to a decline in signal quality. To have stable, high-quality and reliable EEG data, it is necessary to make sure that all relevant electrodes are connected and do not lose their connection during experiments by reapplying the saline solution to the electrodes, as the solution evaporates over time. In order to maintain a stable connection over long periods, it is necessary to reapply the saline solution to the electrodes, as the solution evaporates over time;
- Wireless Connectivity: Wireless EEG devices can pose a security risk to the data of the participant, as any movement of cables could potentially induce the data during transfer. Because of this, wireless EEG devices should necessarily require encryption of the data prior to wireless transfer.
- Headset Size: Most EEG devices are limited in their size adjustability, and may thus require multiple different caps or headsets in order to fit experiments and studies which collect data of individuals with large head-size discrepancies, increasing the overall price;
- Battery Life: Wireless EEG devices are most often battery-operated and, as such, are subject to potential loss of data if the current battery charge falls below threshold levels. Ensuring that batteries will be operational throughout long studies can be difficult, and the necessity of ensuring batteries are charged increases the complexity of data-gathering using EEG devices. Battery life has a negative correlation with the amount of sensory information they provide; as more information is given, the battery time decreases, which means that the research focused on long-term study of brain activities should try to rely on less sensory information, if possible;
- Sensitivity to external noise/artifacts: When collecting EEG data, it is important to ask the participants to sit in a relaxed manner because any movement of the body can cause artifacts in the data. To obtain high-quality data and better results, artifacts such as muscle and eye movement, eye blink, and line noise need to be pre-processed and artifacts should be omitted before doing any data analysis;
- Price: Most of the EEG devices designed for medical purposes like Neurofeedback and neuroscience are expensive;
- API/Software Used by Device: The software which accompanies an EEG headset can be complicated for researchers without prior extensive knowledge about brain activity, as well as knowledge of filtering and analysis techniques. The software, which is utilized by an EEG device, can have adverse effects on the ease and reliability of experiments, as well as the overall cost. In addition to research on the quality of the EEG device itself, care should be taken to understand if the software it makes use of is within acceptable cost and quality levels. Open Source software tends to be more secure, but has less built-in support for newer users, whereas integrated proprietary software tends to have better support, but is more costly. Depending on the EEG software, users may be given access to raw EEG data that has not been modified, processed data that has been modified after recording by the software in some way, or to both raw and processed data;
- Comfort to user: Wireless dry or saline solution EEG devices are more convenient for the user because of their flexibility of movement, lower setup time, and no need for cleaning the user hairs after the experiment like in gel-based solution;
- CE/FDA approved: Most of the listed commercial EEG sensors have not been CE/FDA approved. A list of EEG headsets that can be utilized for clinical treatments is given in the “MD” column of Table 3.
6. Conclusions and Future Research
Author Contributions
Funding
Conflicts of Interest
References
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Applications (Company Recommendation) | EEG Headset Product Name (Company) |
---|---|
Neuroscience Research |
|
Neuromarketing |
|
Brain computer interface and Neurogaming |
|
Ergonomics and Biometrics |
|
Neurofeedback |
|
Biofeedback |
|
Custom Solutions (e.g., Sports, education) |
|
Company | Product Name | Extra Sensors (Optional) | Motion Sensors | Communication Mode(s) | Bluetooth Range | Included Software | Battery Life (When Applicable) |
---|---|---|---|---|---|---|---|
Compumedics Neuroscan | Quick-Cap Neo Net | EOG ECG EMG | - | - | - | - | - |
Quick-cap Silicone Array | EOG ECG EMG | - | - | - | - | - | |
Quick-Cap Hydro Net | EOG ECG EMG | - | - | - | - | - | |
Quick-Cap | EOG ECG EMG | - | - | - | - | - | |
Wearable sensing | DSI 24 | EMG EOG ECG | Accelerometer (Opt) | Bluetooth Wireless | 10 m/30 feet | DSI-Streamer Data Acquisition Software and API | - |
DSI 7 | N/A | Accelerometer (Opt) | Bluetooth Wireless | 10 m/30 feet | DSI-Streamer Data Acquisition Software and API | - | |
DSI 7 Flex | N/A | Accelerometer (Opt) | Bluetooth Wireless | 10 m/30 feet | DSI-Streamer Data Acquisition Software and API | - | |
VR300 | N/A | Accelerometer (Opt) | Bluetooth Wireless | 10 m/30 feet | DSI-Streamer Data Acquisition Software, API, and Unity and Unreal SDK for VR | - | |
NeusenW | N/A | 9-axis motion sensors | Bluetooth Wireless | - | - | Up to 2 h | |
NeuroCube | N/A | 9-axis motion sensors | Bluetooth Wireless | - | - | Up to 2 h | |
Emotiv | EPOC X | N/A | 9-axis motion sensors | Bluetooth Wireless | - | EmotivPRO Emotiv BrainViz | Up to 9 h |
EPOC + | N/A | 3-axis Accelerometer | Bluetooth Wireless | - | EmotivPRO EmotivBCI Emotiv BrainViz | Up to 12 h | |
MN8 | N/A | Motion sensors | Bluetooth Wireless | - | - | Up to 6 h | |
INSIGHT | N/A | 9-axis Motion sensors | Bluetooth Wireless | - | - | Up to 9 h | |
EPOC Flex | N/A | 3-axis Accelerometer, Magnetometer | Bluetooth Wireless | - | EmotivPRO | Up to 9 h | |
OPEN BCI | EEG Electrode Cap Kit | N/A | N/A | Bluetooth Wireless | - | OpenBCI’s FREE open-source software | - |
Ultracortex “Mark IV” EEG headset | EMG ECG | 3-axis Accelerometer | Bluetooth Wireless | - | - | - | |
OpenBCI Classroom Bundle (5 kits) | EMG ECG | N/A | Bluetooth Wireless | - | - | - | |
Biosemi | ActiveTwo | EMG ECG | N/A | Wired | - | LabVIEW | N/A |
ActiveOne | EMG ECG | N/A | Wired | - | N/A | ||
Advanced Brain Monitoring | Sleep Profiler™ | EOG EMG ECG | N/A | Wireless | - | - | Up to 30 h |
Sleep Profiler PSG2TM | EEG EOG EMG | N/A | Wireless | - | - | Up to 30 h | |
Stat X-Series | ECG EOG EMG | Accelerometer | Bluetooth Wireless | 10 m | B-AlertLive LabX | Up to 8 h | |
B-Alert X-Series | ECG EOG EMG | Accelerometer | Bluetooth Wireless | 10 m | B-AlertLive LabX | Up to 8 h | |
InteraXon | Muse S | PPG | Accelerometer Gyroscope | Bluetooth Wireless | - | Muse App | 10 h |
Muse S Bundle | PPG | Accelerometer Gyroscope | Bluetooth Wireless | - | Muse App | 10 h | |
Muse 2 | PPG | Accelerometer Gyroscope | Bluetooth Wireless | - | Muse App | 5 h | |
Neuroelectrics | Enobio | N/A | 3-axis Accelerometer | Bluetooth Wireless | - | Enobio API Matlab (EEGLAB Plugin) Python (Neyp library) | Up to 20 h |
NeuroSky | MindWave Mobile 2 | ECG | N/A | Bluetooth Wireless | 10 m | MindWave Mobile apps | 8 h |
Wearable Sensing | NeusenW | EOG | 9-axis motion sensor | Bluetooth Wireless | - | - | - |
ANT Neuro | EegoTM mylab | N/A | N/A | Bluetooth Wireless | - | API | Up to 5 h |
EegoTM sports | EMG | N/A | Bluetooth Wireless | - | API | Up to 5 h | |
EegoTM mini-series | EMG | N/A | Bluetooth Wireless | - | API | Up to 5 h | |
G.tec | NAUTILUS FNIRS | N/A | 3-axis accelerometer | Bluetooth Wireless | 10 m | BSANALYZE | Up to 10 h |
Nautilus Research | N/A | 3-axis accelerometer | Bluetooth Wireless | 0 m | BSANALYZE | Up to 6 h | |
Nautilus PRO | N/A | 3-axis accelerometer | Bluetooth Wireless | 10 m | BSANALYZE | Up to 10 h | |
G. nautilus multi purpose | N/A | 3-axis accelerometer | Bluetooth Wireless | 10 m | BSANALYZE | - | |
imec | - | N/A | - | Bluetooth Wireless | - | Qt-based, MS & Android | Up to 8 h |
EB Neuro | BE Micro | - | N/A | Bluetooth Wireless | - | - | Up tp 72 h |
mBrain Train | SMARTING | N/A | 3 axis gyroscope | Bluetooth Wireless | 10 m | API | Up to 5 h |
SMARTFONES | N/A | N/A | Bluetooth Wireless | - | API | - | |
SMARTING sleep | ECG EMG EOG | 9 axis motion sensor | Bluetooth Wireless | 10 m | API | Up to 15 h | |
Cognionics (CGX) | Quick | EOG ECG EMG PPG GSR | N/A | Bluetooth Wireless | - | - | - |
Mobile | EOG ECG EMG PPG GSR | N/A | Bluetooth Wireless | - | - | - | |
Brain Product | actiCAP (Slim & Snap) | N/A | N/A | - | - | - | - |
LiveAMP | N/A | N/A | Bluetooth Wireless | - | - | - |
Company | Publications (Company) | EEG Headset/Caps | No. Publications | MD 1 | Sample Rate | No. Channels | Electrode Connection Type | Set up Time: Minutes(m) or Seconds (s) | Price |
---|---|---|---|---|---|---|---|---|---|
Compumedics Neuroscan | Quick_Cap Neo Net | X | Up to 256 | Gel | - | - | |||
Quick_Cap Silicone Array | X | Up to 256 | Saline | - | - | ||||
Quick_Cap Hydro Net | X | Up to 256 | Saline | - | - | ||||
Quick-Cap | X | Up to 256 | Gel | - | - | ||||
Emotiv | 8150 | INSIGHT | 362 | X | 128 Hz | 5 | Semi-dry polymer | 1–2 m | $299 |
EPOC X | 1 | X | 128 Hz | 14 | Wet (Saline) | 3–5 m | $849 | ||
EPOC+ | 4370 | X | 128 Hz | 14 | Saline soaked felt | 3–5 m | $699 | ||
EPOC FLEX KIT | 0 | X | 128 Hz | 32 | Saline/Gel | 15–30 m | $1699 | ||
MN8 | 0 | X | - | 2 (+4 reference) | Dry | 30 s | - | ||
OpenBCI | 835 | Ulracortex Mark IV | 26 | X | 125 HZ or 250 Hz | 8 or 16 | Dry | ~30 s | Print-It-Yourself ($299.99–399.99) |
Unassembled ($499.99–599.99) | |||||||||
Pro-Assembled ($699.99–849.99) | |||||||||
EEG Electrode Cap Kit | 1 | X | 21 | Gel | ~30 s | $399.99 | |||
BIOSEMI | 10,300 | ActiveTwo | 2650 | X | 2, 4, 8, 16 kHz | 280 | Gel | - | € 14,840 € 72,440 |
ActiveOne | 15 | - | - | Up to 144 | Gel | - | |||
Advanced Brain Monitoring | 2030 | B-Allert (X10 or X24) | 37 | ✔ | 256 Hz | 9 and 24 | Dry | - | $1000–$25,000 |
Sleep Profiler | 2 | ✔ | - | Up to 8 | Dry | - | - | ||
Sleep Profiler PSG2TM | 0 | ✔ | - | Up to 13 | Dry | - | - | ||
Stat X-Series | 0 | ✔ | - | Up to 20 | Dry | - | - | ||
InteraXon | 1140 | Muse 2 | 158 | X | 220 Hz or 500 Hz | 4 | Dry | - | $224.99 |
Muse S Bunddle | X | - | 4 | Dry | - | $444.98 | |||
Muse S | X | - | 4 | Dry | - | $344.99 | |||
Neuroelectrics | 1200 | Enobio | 59 | ✔ | 500 SPS | 8, 20, 32 | Dry/Wet | - | - |
G·tec | 4950 | Nautilus Research | 16 | X | 250 Hz or 500 Hz | 8, 16, 32, 64 | Gel | - | $1000–$25,000 |
NAUTILUS FNIRS | X | 250 Hz or 500 Hz | 8, 16, 32, 64 | Wet | - | - | |||
Nautilus PRO | ✔ | 500 Hz | 8, 16, and 32 | Dry/Wet | - | - | |||
Nautilus multi- purpose | X | 250 Hz or 500 Hz | 8, 16, 32, 64 | Wet | - | - | |||
Cognionics (CGX) | 497 | QUICK | 49 | X | 500 Hz or 1000 Hz | 8, 20, 30 | Dry | - | $1000–$25,000 |
Mobile | 21 | X | 500 Hz or 1000 Hz | 64, 128 | Gel | - | - | ||
ANT Neuro | 1110 | eego mylab | 8 | X | 16 kHZ | 32–256 | Dry/Gel | - | $1000–$25,000 |
EegoTM sports | 10 | X | - | - | - | - | - | ||
EegoTM mini-series | - | X | - | - | - | 20 m | - | ||
Brain Products | 11,700 | LiveAmp | 31 | X | 250–1000 Hz | 8–64 | Dry/Gel | $1000–$25,000 | |
ActiCAP | 899 | X | - | - | - | - | - | ||
Wearable Sensing | 1220 | Dry Sensor Interface Series | 0 | X | 300–600 Hz | 2–21 | Dry | ~5 min. | $1000–$25,000 |
VR300 | - | X | 300 Hz | 7 | Dry | 1–3 min | - | ||
NeusenW | - | - | Up to 16 kHz | 8–64 | Wet | - | - | ||
NeuroCub | - | - | 16 kHz | 8 | Wet | - | - | ||
DSI 24 | 18 | - | 300 Hz | 21 | Dry active hybrid | 3–5 min | - | ||
DSI 7 Flex | - | - | 300–600 Hz | - | Dry | - | - | ||
DSI 7 | 5 | - | 300–600 Hz | 2–6 | Dry | 1–3 min | - | ||
NeuroSky | 4910 | MindWave Mobile 2 | 1510 | - | 150 Hz | 2 | Dry | - | - |
BrainWave Bank | 7 | - | - | - | - | 16 | - | ~5 m | - |
imec | 92,200 2 (1690) | EEG Headset | 17 | - | 128, 256, 1028 Hz | 8 | Dry | - | - |
EBNeuro | 367 | BE Micro | 57 | - | - | - | - | - | - |
mBrainTrain | 159 | SMARTING | 99 | - | 250–500 Hz | 24 | - | - | - |
SMARTFONES | 1 | - | Up to 1000 Hz | 11 | Semi-dry | - | - | ||
SMARTING sleep | - | - | 250–500 Hz | 17 | Dry | - | - |
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Soufineyestani, M.; Dowling, D.; Khan, A. Electroencephalography (EEG) Technology Applications and Available Devices. Appl. Sci. 2020, 10, 7453. https://doi.org/10.3390/app10217453
Soufineyestani M, Dowling D, Khan A. Electroencephalography (EEG) Technology Applications and Available Devices. Applied Sciences. 2020; 10(21):7453. https://doi.org/10.3390/app10217453
Chicago/Turabian StyleSoufineyestani, Mahsa, Dale Dowling, and Arshia Khan. 2020. "Electroencephalography (EEG) Technology Applications and Available Devices" Applied Sciences 10, no. 21: 7453. https://doi.org/10.3390/app10217453
APA StyleSoufineyestani, M., Dowling, D., & Khan, A. (2020). Electroencephalography (EEG) Technology Applications and Available Devices. Applied Sciences, 10(21), 7453. https://doi.org/10.3390/app10217453