The Science Behind Neve

Training load, sleep, heart-rate variability (HRV), subjective wellness and cognitive performance provide different perspectives on an athlete's state. No single measure captures every aspect of recovery, attention or performance.

Neve is designed to add resting EEG and brief cognitive tasks to this wider picture. The objective is not to replace coaches, clinicians or existing athlete-monitoring systems, but to offer additional longitudinal information that may help inform conversations and research.

Electroencephalography (EEG) records electrical potential differences at the scalp that arise primarily from synchronised neuronal activity. Spectral features, including activity in conventional alpha, theta and beta frequency ranges, can vary with attention, task demands, vigilance and other physiological conditions.

These features are not one-to-one measures of fatigue, motivation, injury risk or competitive readiness. Their interpretation depends on electrode location, recording conditions, artefacts, the individual and the analytical method. A brief resting EEG cannot independently diagnose overtraining, concussion or neurological disease.

Neve focuses on repeated observations and changes relative to an individual's own baseline rather than treating a population-wide threshold as universally meaningful.

Short behavioural tasks can capture measures such as reaction time and response accuracy. These outcomes provide information that differs from physiological recordings, although they are affected by practice, device conditions, motivation and other sources of variation.

Our preliminary internal analyses are exploring how cognitive task performance relates to self-reported state and how within-person baselines may support interpretation. These findings are exploratory and are not yet evidence of clinical validity, injury prediction or a validated readiness score.

HRV describes variation in intervals between heartbeats and can provide useful information about aspects of cardiac autonomic regulation. It is influenced by sleep, illness, stress, exercise, measurement timing and device characteristics.

HRV is best interpreted in context and over time. It does not directly measure brain activity and cannot, on its own, establish whether an athlete is neurologically recovered or at risk of injury.

Where compatible wearable data are available, Neve aims to place those measures alongside cognitive and EEG observations.

Research across EEG, cardiac signals and behavioural measures suggests that combining complementary information can improve classification for some specific tasks and datasets. Results depend on study design, the population, reference labels, validation strategy and recording conditions.

Published accuracy figures from unrelated fatigue or driving studies are not Neve performance figures. We are evaluating whether combining signals provides more useful, reproducible within-person information than considering them separately. No universal fatigue-detection accuracy or injury-prediction performance is claimed for Neve at this stage.

People differ substantially in their usual physiology and cognitive performance. Neve's scientific approach therefore prioritises repeated measurements, an individual baseline and deviations from that baseline.

Standardised differences, including within-person z-scores where methodologically appropriate, may help quantify change. A deviation is not automatically good or bad; direction and significance depend on the specific measure, measurement reliability and context. Baseline quality, missing data, artefact handling and day-to-day variability are central to the ongoing validation work.

Neve's brief EEG recording is designed to make repeat measurement practical outside a conventional laboratory. The short duration supports routine use but imposes limits on the inferences that can be made. Signal quality can be affected by electrode contact, movement, muscle activity and environmental interference.

The recording is intended to contribute one part of a broader longitudinal assessment. It is not equivalent to a comprehensive clinical EEG examination.

There is active research interest in EEG and other physiological measurements in contact-sport populations. However, the presence of an EEG change does not establish concussion, and normalisation of an EEG feature does not confirm recovery.

Neve is not intended to diagnose concussion, determine fitness to play, replace established return-to-sport protocols or provide medical clearance. Decisions about suspected head injury and return to play must remain with appropriately qualified healthcare professionals using applicable clinical guidance.

Neve is building a research programme to assess feasibility, measurement reliability, longitudinal changes and relationships among EEG, cognitive-task results, wearable measures and self-reported state. Planned evaluations include the practicality of repeat measurements in sport and whether multimodal models offer incremental value.

Early internal findings are preliminary, may change with additional data and have not yet established prospective injury prediction, diagnostic accuracy or clinical outcomes. We intend to communicate methods, limitations and results transparently as research progresses.

Neve is a performance-monitoring and research-support platform, not a substitute for clinical assessment. Its outputs should be interpreted alongside athlete history, training context, symptoms, subjective reports and professional judgement.

We do not currently claim that Neve predicts injury within 48 hours, prevents overtraining, detects concussion, confirms neurological recovery or achieves a specified fatigue-classification accuracy in professional sport. These questions require appropriately designed, independent, prospective validation.