Interval Detection

When analyzing a cycling session in Vekta, interval detection leverages AI technology to automatically identify and categorize each effort.

Effort Identification
Vekta’s AI scans the session to pinpoint the start and end of each effort based on power, cadence, and torque. This enables the AI to segment the session into distinct intervals, capturing each work and recovery phase with precision.

Structure Analysis
With intervals identified, the AI evaluates session structure, analyzing the intensity, duration, and frequency of each effort. Based on these factors, Vekta assigns an intensity label (see all possibilities here) and characteristic (see all possibilities here) to each interval.

Training Stimulus Labeling
Vekta then assigns a Training Stimulus label to the session, helping you understand the physiological demands and specific adaptations targeted—like Aerobic, Anaerobic, or VO2max (see full list here).

To view detected intervals, simply toggle the Show Intervals button above the session streams. For a detailed breakdown, navigate to the Intervals tab, where each interval is listed in a summary format, row by row.

With Vekta’s automated interval detection, you can skip the time-intensive analysis of raw data and get directly to insights.