Portable wireless and fibreless fNIRS headband compares favorably to a stationary headcap-based system
Bibliographic record
Abstract
This study's purpose is to characterize the performance of a prototype functional near-infrared spectroscopy (fNIRS) headband meant to enable quick and easy measurements from the sensorimotor cortices. The fact that fNIRS is well-suited to ergonomic designs (i.e., their ability to be made wireless, their relative robustness to movement artifacts among other characteristics) has resulted in many recent examples of novel ergonomic fNIRS systems; however, the optical nature of fNIRS measurement presents an inherent challenge to measurement at areas of the brain underlying haired parts of the head. It is for this reason that the majority of ergonomic fNIRS systems that have been developed to date target the prefrontal cortex. In the present study we compared the performance of a novel, portable fNIRS headband compared with a stationary full headcap fNIRS system to measure sensorimotor activity during simple upper- and lower-extremity tasks, in healthy individuals >50 years of age. Both fNIRS systems demonstrated the expected pattern of hemodynamic activity in both upper- and lower-extremity tasks, and a comparison of the contrast-to-noise ratio between the two systems suggests the prototype fNIRS headband is non-inferior to a full head cap fNIRS system regarding the ability to detect a physiological response at the sensorimotor cortex during these tasks. These results suggest the use of a wireless and fibreless fNIRS design is feasible for measurement at the sensorimotor cortex.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".