ArticleNeurorehabilitation and neural repair2017
Estimated Prevalence of the Target Population for Brain-Computer Interface Neurotechnology in the Netherlands.
Article in Neurorehabilitation and neural repair, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02224469 (Utrecht Neural Prosthesis), which is not on this map. Cited by 16 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Utrecht Neural Prosthesis (UNP): A Pilot Study on Controllability of Brain Signals and Application in locked-in Patients
Who cites it
16 citing papers in PubMed, 32 citations in OpenAlex.
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- Dilemma in patients with amyotrophic lateral sclerosis and expectations from brain-machine interfaces.Annals of medicine · 2024Article
- The speech neuroprosthesis.Nature reviews. Neuroscience · 2024Review
- A high-performance speech neuroprosthesis.Nature · 2023Article
- Towards clinical application of implantable brain-computer interfaces for people with late-stage ALS: medical and ethical considerations.Journal of neurology · 2023Review
- Methodological Recommendations for Studies on the Daily Life Implementation of Implantable Communication-Brain-Computer Interfaces for Individuals With Locked-in Syndrome.Neurorehabilitation and neural repair · 2022Article
- Workshops of the Eighth International Brain-Computer Interface Meeting: BCIs: The Next Frontier.Brain computer interfaces (Abingdon, England) · 2022Article
- Brain-Computer Interfaces for Communication: Preferences of Individuals With Locked-in Syndrome.Neurorehabilitation and neural repair · 2021Article
- Stability of a chronic implanted brain-computer interface in late-stage amyotrophic lateral sclerosis.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2019Article
- Encoding of kinetic and kinematic movement parameters in the sensorimotor cortex: A Brain-Computer Interface perspective.The European journal of neuroscience · 2019Review
- Neural mechanisms of training an auditory event-related potential task in a brain-computer interface context.Human brain mapping · 2019Article
- Sensorimotor ECoG Signal Features for BCI Control: A Comparison Between People With Locked-In Syndrome and Able-Bodied Controls.Frontiers in neuroscience · 2019Article
- Workshops of the Seventh International Brain-Computer Interface Meeting: Not Getting Lost in Translation.Brain computer interfaces (Abingdon, England) · 2019Article
- Comparison of Four Control Methods for a Five-Choice Assistive Technology.Frontiers in human neuroscience · 2018Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
backgroundPeople who suffer from paralysis have difficulties participating in society. Particularly burdensome is the locked-in syndrome (LIS). LIS patients are not able to move and speak but are cognitively healthy. They rely on assistive technology to interact with the world and may benefit from neurotechnological advances. Optimal research and design of such aids requires a well-defined target population. However, the LIS population is poorly characterized and the number of patients in this condition is unknown.
objectiveHere we estimated and described the LIS patient population in the Netherlands to define the target population for assistive (neuro)technology.
methodsWe asked physicians in the Netherlands if they had patients suffering from severe paralysis and communication problems in their files. Physicians responding affirmatively were asked to fill out a questionnaire on the patients' status.
resultsWe sent out 9570 letters to general practitioners (GPs), who reported 83 patients. After first screening, the GPs of 46 patients received the questionnaire. Based on the responses, 26 patients were classified as having LIS. Extrapolation of these numbers resulted in a prevalence of 0.73 patients per 100 000 inhabitants. Notable results from the questionnaire were the percentage of patients with neuromuscular disease (>50%) and living at home (>70%).
conclusionsWe revealed an etiologically diverse group of LIS patients. The functioning and needs of these patients were, however, similar and many relied on assistive technology. By characterizing the LIS population, our study may contribute to optimal development of assistive (neuro)technology.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.