Invasive brain–machine interfaces: a survey of paralyzed patients' attitudes, knowledge and methods of information retrieval. (14th July 2015)
- Record Type:
- Journal Article
- Title:
- Invasive brain–machine interfaces: a survey of paralyzed patients' attitudes, knowledge and methods of information retrieval. (14th July 2015)
- Main Title:
- Invasive brain–machine interfaces: a survey of paralyzed patients' attitudes, knowledge and methods of information retrieval
- Authors:
- Lahr, Jacob
Schwartz, Christina
Heimbach, Bernhard
Aertsen, Ad
Rickert, Jörn
Ball, Tonio - Abstract:
- Abstract: Objective. Brain–machine interfaces (BMI) are an emerging therapeutic option that can allow paralyzed patients to gain control over assistive technology devices (ATDs). BMI approaches can be broadly classified into invasive (based on intracranially implanted electrodes) and noninvasive (based on skin electrodes or extracorporeal sensors). Invasive BMIs have a favorable signal-to-noise ratio, and thus allow for the extraction of more information than noninvasive BMIs, but they are also associated with the risks related to neurosurgical device implantation. Current noninvasive BMI approaches are typically concerned, among other issues, with long setup times and/or intensive training. Recent studies have investigated the attitudes of paralyzed patients eligible for BMIs, particularly patients affected by amyotrophic lateral sclerosis (ALS). These studies indicate that paralyzed patients are indeed interested in BMIs. Little is known, however, about the degree of knowledge among paralyzed patients concerning BMI approaches or about how patients retrieve information on ATDs. Furthermore, it is not yet clear if paralyzed patients would accept intracranial implantation of BMI electrodes with the premise of decoding improvements, and what the attitudes of a broader range of patients with diseases such as stroke or spinal cord injury are towards this new kind of treatment. Approach. Using a questionnaire, we surveyed 131 paralyzed patients for their opinions on invasiveAbstract: Objective. Brain–machine interfaces (BMI) are an emerging therapeutic option that can allow paralyzed patients to gain control over assistive technology devices (ATDs). BMI approaches can be broadly classified into invasive (based on intracranially implanted electrodes) and noninvasive (based on skin electrodes or extracorporeal sensors). Invasive BMIs have a favorable signal-to-noise ratio, and thus allow for the extraction of more information than noninvasive BMIs, but they are also associated with the risks related to neurosurgical device implantation. Current noninvasive BMI approaches are typically concerned, among other issues, with long setup times and/or intensive training. Recent studies have investigated the attitudes of paralyzed patients eligible for BMIs, particularly patients affected by amyotrophic lateral sclerosis (ALS). These studies indicate that paralyzed patients are indeed interested in BMIs. Little is known, however, about the degree of knowledge among paralyzed patients concerning BMI approaches or about how patients retrieve information on ATDs. Furthermore, it is not yet clear if paralyzed patients would accept intracranial implantation of BMI electrodes with the premise of decoding improvements, and what the attitudes of a broader range of patients with diseases such as stroke or spinal cord injury are towards this new kind of treatment. Approach. Using a questionnaire, we surveyed 131 paralyzed patients for their opinions on invasive BMIs and their attitude toward invasive BMI treatment options. Main results. The majority of the patients knew about and had a positive attitude toward invasive BMI approaches. The group of ALS patients was especially open to the concept of BMIs. The acceptance of invasive BMI technology depended on the improvements expected from the technology. Furthermore, the survey revealed that for paralyzed patients, the Internet is an important source of information on ATDs. Significance. Websites tailored to prospective BMI users should be further developed to provide reliable information to patients, and also to help to link prospective BMI users with researchers involved in the development of BMI technology. … (more)
- Is Part Of:
- Journal of neural engineering. Volume 12:Number 4(2015:Aug.)
- Journal:
- Journal of neural engineering
- Issue:
- Volume 12:Number 4(2015:Aug.)
- Issue Display:
- Volume 12, Issue 4 (2015)
- Year:
- 2015
- Volume:
- 12
- Issue:
- 4
- Issue Sort Value:
- 2015-0012-0004-0000
- Page Start:
- Page End:
- Publication Date:
- 2015-07-14
- Subjects:
- brain–machine interface (BMI) -- brain-computer interface (BCI) -- electrocorticography (ECoG) -- intercranial EEG (iEEG) -- survey -- electroencephalography (EEG)
Neurosciences -- Periodicals
Biomedical engineering -- Periodicals
612.8 - Journal URLs:
- http://iopscience.iop.org/1741-2552/ ↗
http://ioppublishing.org/ ↗ - DOI:
- 10.1088/1741-2560/12/4/043001 ↗
- Languages:
- English
- ISSNs:
- 1741-2560
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
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