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Development of a Medical Device for the Rapid Assessment of Concussion (S11.007)

2014· article· en· W1557916073 on OpenAlexaffabout
Donald F. Weaver, Ying Tam, Christopher Barden, Ryan C.N. D’Arcy, Love Kalra, Lauren Petley, Wei Chen

Bibliographic record

VenueNeurology · 2014
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsIzaak Walton Killam Health CentreDalhousie UniversityUniversity Health Network
Fundersnot available
KeywordsConcussionMedicinePhysical medicine and rehabilitationMedical emergencyInjury preventionPoison control

Abstract

fetched live from OpenAlex

OBJECTIVE: To develop an EEG-based medical device that can be used to assess conscious awareness in a short time frame (e.g., five minutes), particularly in traumatic brain injury patients. BACKGROUND: Incidents of traumatic brain injury are pervasive in the community, yet many such incidents are not properly diagnosed or assessed, particularly in the context of athletics. Assessment by a trained physician in these cases is hampered by a lack of public knowledge of concussion, especially where neurological symptoms may be mild or hidden. Thus, a triage tool for in-community assessment of these mild cases is a subject of active research. DESIGN/METHODS: Based upon principles of auditory evoked potential electroencephalography, a prototype medical device was developed: the Halifax Consciousness Scanner (HCS). HCS consists of a headset containing earphones and EEG electrodes placed at specified positions upon the scalp, coupled to a portable EEG amplifier, an audio tone/speech generator, and wirelessly connected to a portable computer/tablet for analysis. Upon activation, HCS presents tones and phrases to the subject that assess cortical function in five indicia related to consciousness (sensory, attention, perception, memory, and language). The aim of HCS research has been to norm this information and to compare to cases of known traumatic brain injury (mild through severe) and other traumas that exhibit abnormal auditory evoked potential EEG. RESULTS: Collection across 100 subjects showed consistent responses across all 5 indicators used in HCS. Recording of 20 major brain injury patients, approximately age-matched to controls, showed a significant difference in cortical response as measured by comparison of HCS waveforms between groups. Studies are ongoing to determine the HCS response in mild traumatic brain injury as measured in athletes suffering a first-time reported concussion. CONCLUSIONS: Preliminary data suggest that the set of auditory evoked potentials implemented in HCS represent a promising means of identifying whether or not a subject has suffered a change of conscious awareness indicative of concussion.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0190.008

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.096
GPT teacher head0.421
Teacher spread0.325 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2014
Admission routes2
Has abstractyes

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