The DOI matches its Crossref record; 66 of the 66 references it cites were found in a registry or an index.
Wearable, Wireless EEG Solutions in Daily Life Applications: What are we Missing?
Abstract
Monitoring human brain activity has great potential in helping us understand the functioning of our brain, as well as in preventing mental disorders and cognitive decline and improve our quality of life. Noninvasive surface EEG is the dominant modality for studying brain dynamics and performance in real-life interaction of humans with their environment. To take full advantage of surface EEG recordings, EEG technology has to be advanced to a level that it can be used in daily life activities. Furthermore, users have to see it as an unobtrusive option to monitor and improve their health. To achieve this, EEG systems have to be transformed from stationary, wired, and cumbersome systems used mostly in clinical practice today, to intelligent wearable, wireless, convenient, and comfortable lifestyle solutions that provide high signal quality. Here, we discuss state-of-the-art in wireless and wearable EEG solutions and a number of aspects where such solutions require improvements when handling electrical activity of the brain. We address personal traits and sensory inputs, brain signal generation and acquisition, brain signal analysis, and feedback generation. We provide guidelines on how these aspects can be advanced further such that we can develop intelligent wearable, wireless, lifestyle EEG solutions. We recognized the following aspects as the ones that need rapid research progress: application driven design, end-user driven development, standardization and sharing of EEG data, and development of sophisticated approaches to handle EEG artifacts.
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OmniPHR: a distributed architecture model to integrate personal health records
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Elger, C. E., & Hoppe, C. (2018) · The Lancet Neurology · doi:10.1016/s1474-4422(18)30038-3 · Cited by 403
A Review on the Use of Wearable Functional Near‐Infrared Spectroscopy in Naturalistic Environments
Pinti, P., Aichelburg, C., Gilbert, S., Hamilton, A., Hirsch, J., Burgess, P., & Tachtsidis, I. (2018) · Japanese Psychological Research · doi:10.1111/jpr.12206 · Cited by 325
Automated seizure detection systems and their effectiveness for each type of seizure
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Metadata
- Authors
- Mihajlovic, V., Grundlehner, B., Vullers, R., & Penders, J.
- Venue
- IEEE Journal of Biomedical and Health Informatics
- Published
- 2015-01
- Volume
- 19
- Issue
- 1
- Pages
- 6-21
- ISSN
- 2168-2194 (ISSN-L)
- 2168-2208
- OpenAlex
- W2040755506
- Cited by
- 289
- References
- 66
- FWCI
- 10.73
- Type
- journal article
- Language
- en
- Open access
- closed
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- Mihajlovic, V., Grundlehner, B., Vullers, R., & Penders, J. (2015). Wearable, Wireless EEG Solutions in Daily Life Applications: What are we Missing? IEEE Journal of Biomedical and Health Informatics. https://doi.org/10.1109/jbhi.2014.2328317
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