Results for “physiological-signals”

Process and analyze physiological signals including ECG, EEG, EDA, RSP, PPG, EMG, and EOG using Python.

Calculates a per-ticker panic index (0-100) from six weighted signals including VIX, IV Rank, RSI-14, volume anomaly, put/call ratio, and consecutive down days, triggering Bull Put Spread entry signals at scores ≥60.

Build clinical deep-learning pipelines with PyHealth: load EHR, signal, and imaging datasets, define prediction tasks, instantiate models, train with the PyHealth Trainer, and compute clinical metrics.

Screen US equities for parabolic exhaustion patterns, generate conditional pre-market short plans, and monitor intraday trigger signals using 5-min bars.

Detects whether current market conditions match David Tepper's historic panic-buy signal by combining VIX, FearScore, and a quality filter.

Record and analyze post-trade outcomes for trading signals, tracking false positives, missed opportunities, and regime mismatches to generate feedback for signal aggregation and skill improvement.

Analyzes Zeek conn.log connection intervals using statistical methods to detect C2 beaconing patterns, flagging periodic connections with low jitter.