Spike Detection Algorithm

Automated computational system for identifying and removing physiological and electrical artifacts from EEG recordings.

A software algorithm that automatically identifies and classifies cardiac arrhythmias from electrocardiogram waveforms. The algorithm alerts clinicians to potentially dangerous rhythm disturbances.

Advanced signal processing algorithm for identifying heartbeat indicators in ECG data with customizable filtering. Reduces false detection rates even with motion artifacts and non-traditional electrode configurations.

Software-based cardiac rhythm analysis system for automated arrhythmia identification and classification. Enhances diagnostic accuracy in cardiac assessment.

Machine learning software for automated detection and classification of cardiac arrhythmias from ECG data. Analyzes heart rhythm patterns to identify pathological conditions and assist in clinical diagnosis. Compatible with multiple cardiac monitoring devices.

An artificial intelligence algorithm analyzing electrocardiogram waveforms for ST-segment and T-wave changes indicative of myocardial ischemia. The algorithm assists in rapid identification of acute coronary syndrome.

Proprietary AI algorithms that continuously classify heartbeats and detect the onset and offset of all cardiac arrhythmias. The system provides real-time analysis with the highest diagnostic yield for detecting ventricular and supraventricular arrhythmias.

Automated software tools for identifying and alerting to seizure activity within continuous EEG recordings. Supports early intervention and clinical management of epilepsy patients.

Software algorithms designed to process, filter, and analyze raw EEG signals from medical-grade devices. The system performs artifact removal, feature extraction, and signal normalization for clinical analysis.

Software solution for analysis and review of EEG recordings from the Trackit T4A ambulatory recorder and routine EEG systems. The software supports clinical and ICU monitoring applications, includes artifact-free EEG analysis and pre-selection of important spikes and seizures, and integrates with esumedics patient database through HL7/GDT interfaces. It provides a uniform database solution for multiple recording types including EEG, EMG/ENG/EP.

Software platform for processing, analyzing, and interpreting electroencephalography signals for neurological diagnosis and monitoring. Provides real-time data visualization and clinical reporting capabilities.

EEG-based software system to assist clinical diagnosis and treatment planning. Utilizes pattern recognition and normative database comparisons to identify abnormal brain activity.