Plug&Play Brain-Computer Interfaces for effective Active and Assisted Living control.
Brain-Computer Interfaces (BCI) rely on the interpretation of brain activity to provide people with disabilities with an alternative/augmentative interaction path. In light of this, BCI could be considered as enabling technology in many fields, including Active and Assisted Living (AAL) systems cont...
| Published in: | Medical & Biological Engineering & Computing Vol. 55; no. 8; pp. 1339 - 1353 |
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| Main Authors: | , , , , |
| Format: | algorithm equations & formulas pictorial research tables/charts Journal Article |
| Published: |
Springer Nature
Aug2017
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=124485681&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 124485681 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Aug2017 vid: 55 iid: 8 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 124485681 124485681 144035146 NLM27858227 124485681 10.1007/s11517-016-1596-4 NLM27858227 124485681 ppf: 1339 ppct: 14 formats: fmt: @attributes: type: P tig: atl: Plug&Play Brain-Computer Interfaces for effective Active and Assisted Living control. aug: au: Mora, Niccolò De Munari, Ilaria Ciampolini, Paolo Millán, José Mora, Niccolò Del R Millán, José affil: Dipartimento di Ingegneria dell'Informazione , Università degli Studi di Parma , Parco Area delle Scienze 181/A 43124 Parma Italy sug: subj: Electroencephalography Equipment and Supplies Electroencephalography Methods Signal Processing, Computer Assisted Equipment and Supplies Assistive Technology Devices Evoked Potentials, Visual Physiology Occipital Lobe Physiology Brain-Computer Interfaces User-Computer Interface Sensitivity and Specificity Equipment Failure Equipment Design Reproducibility of Results Brain Mapping Methods Brain Mapping Equipment and Supplies ab: Brain-Computer Interfaces (BCI) rely on the interpretation of brain activity to provide people with disabilities with an alternative/augmentative interaction path. In light of this, BCI could be considered as enabling technology in many fields, including Active and Assisted Living (AAL) systems control. Interaction barriers could be removed indeed, enabling user with severe motor impairments to gain control over a wide range of AAL features. In this paper, a cost-effective BCI solution, targeted (but not limited) to AAL system control is presented. A custom hardware module is briefly reviewed, while signal processing techniques are covered in more depth. Steady-state visual evoked potentials (SSVEP) are exploited in this work as operating BCI protocol. In contrast with most common SSVEP-BCI approaches, we propose the definition of a prediction confidence indicator, which is shown to improve overall classification accuracy. The confidence indicator is derived without any subject-specific approach and is stable across users: it can thus be defined once and then shared between different persons. This allows some kind of Plug&Play interaction. Furthermore, by modelling rest/idle periods with the confidence indicator, it is possible to detect active control periods and separate them from "background activity": this is capital for real-time, self-paced operation. Finally, the indicator also allows to dynamically choose the most appropriate observation window length, improving system's responsiveness and user's comfort. Good results are achieved under such operating conditions, achieving, for instance, a false positive rate of 0.16 min-1, which outperform current literature findings. pubtype: Academic Journal doctype: algorithm equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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