Abstract: A scenario identification system and a computer implemented method for identifying one or more critical scenarios from vehicle data associated with one or more vehicles are provided. The scenario identification system obtains at least the inertial measurement unit (IMU) data from the vehicle data, derives one or more IMU-based driving parameters from the IMU data, and analyzes the IMU-based driving parameters based on one or more predefined thresholds for identifying the critical scenario(s).

Abstract: A system automatically detects and measures ST deviation of a heart wave ECG signal in the presence of noise and accommodates baseline variation of the signal and other artifacts. A system identifies a particular point in an electrophysiological signal representing heart electrical activity using an interface for receiving an electrical signal waveform comprising an R-wave and including an ST segment portion associated with heart electrical activity of a patient over a heart beat cycle. A signal processor processes data representing the electrical signal waveform by identifying an S point and T point in the electrical signal waveform and determining a first candidate J point in the electrical signal waveform having substantially a maximum distance from a line between the identified S and T points, the distance being measured perpendicularly to the line.

Abstract: A system automatically detects and measures ST deviation of a heart wave ECG signal in the presence of noise and accommodates baseline variation of the signal and other artifacts. A system identifies a particular point in an electrophysiological signal representing heart electrical activity using an interface for receiving an electrical signal waveform comprising an R-wave and including an ST segment portion associated with heart electrical activity of a patient over a heart beat cycle. A signal processor processes data representing the electrical signal waveform by identifying an S point and T point in the electrical signal waveform and determining a first candidate J point in the electrical signal waveform having substantially a maximum distance from a line between the identified S and T points, the distance being measured perpendicularly to the line.

Abstract: A system automatically detects and measures ST deviation of a heart wave ECG signal in the presence of noise and accommodates baseline variation of the signal and other artefacts. A system identifies a particular point in an electrophysiological signal representing heart electrical activity using an interface for receiving an electrical signal waveform comprising an R-wave and including an ST segment portion associated with heart electrical activity of a patient over a heart beat cycle. A signal processor processes data representing the electrical signal waveform by identifying an S point and T point in the electrical signal waveform and determining a first candidate J point in the electrical signal waveform having substantially a maximum distance from a line between the identified S and T points, the distance being measured perpendicularly to the line.

Abstract: A system automatically detects and measures ST deviation of a heart wave ECG signal in the presence of noise and accommodates baseline variation of the signal and other artefacts. A system identifies a particular point in an electrophysiological signal representing heart electrical activity using an interface for receiving an electrical signal waveform comprising an R-wave and including an ST segment portion associated with heart electrical activity of a patient over a heart beat cycle. A signal processor processes data representing the electrical signal waveform by identifying an S point and T point in the electrical signal waveform and determining a first candidate J point in the electrical signal waveform having substantially a maximum distance from a line between the identified S and T points, the distance being measured perpendicularly to the line.