Brain-computer & cognitive interfaces
Neurotech APIs for EEG analysis, cognitive state detection, and brain-computer interfaces.
Analyze EEG signals for patterns and states. Detect brain wave frequencies, anomalies, and neural patterns.
POST /api/v1/neurotech/eeg/analyze
{ "signal_data": [0.12, -0.05, 0.23, ...],
"sample_rate": 256,
"channels": ["Fp1", "Fp2", "C3", "C4"] }
// Response
{ "bands": {
"alpha": { "power": 12.5, "peak_freq": 10.2 },
"beta": { "power": 8.3, "peak_freq": 18.7 },
"theta": { "power": 6.1, "peak_freq": 5.8 }
}, "quality_score": 0.92 }Measure mental workload from biometrics. Assess cognitive demand and mental fatigue levels.
POST /api/v1/neurotech/cognitive-load
{ "eeg_data": [...],
"heart_rate": 72,
"pupil_diameter": 4.2,
"task_duration": 1800 }
// Response
{ "cognitive_load": 0.73,
"load_level": "high",
"fatigue_index": 0.45,
"recommendation": "Consider a break" }Detect attention and focus levels. Monitor concentration states and identify distractions.
POST /api/v1/neurotech/attention
{ "eeg_data": [...],
"eye_tracking": { "fixations": 45,
"saccades": 23 },
"window_ms": 5000 }
// Response
{ "attention_score": 0.82,
"focus_state": "engaged",
"distraction_events": 2,
"sustained_attention": 0.78 }Detect emotional state from brain signals. Classify valence and arousal from neural activity.
POST /api/v1/neurotech/emotion
{ "eeg_data": [...],
"channels": ["F3", "F4", "Fp1", "Fp2"],
"sample_rate": 256 }
// Response
{ "valence": 0.65,
"arousal": 0.72,
"emotion": "excited",
"confidence": 0.84,
"asymmetry_score": 0.12 }Analyze sleep stages from EEG data. Detect REM, deep sleep, and sleep quality metrics.
POST /api/v1/neurotech/sleep
{ "eeg_data": [...],
"duration_hours": 7.5,
"epoch_length": 30 }
// Response
{ "stages": {
"awake": 0.05, "rem": 0.22,
"light": 0.48, "deep": 0.25 },
"sleep_efficiency": 0.91,
"sleep_latency_min": 12,
"quality_score": 0.85 }Get your API key and start using Neurotech APIs in minutes.