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Documentation Index

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KERN’s analytics dashboard gives you a live view of your cumulative training activity — total sessions completed, steps taken across all workouts, days you trained, and a line chart of how your lifting volume evolves over time. All of this is derived from the WorkoutSession records created each time you finish a session.

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Dashboard statistics

The home dashboard reads from GET /users/stats, which aggregates data across every session you have ever completed. 
GET /users/stats
Authorization: Bearer <token>
Response: 
{
  "total_workouts": 24,
  "total_steps": 18430,
  "training_days": [
    "2026-04-01",
    "2026-04-03",
    "2026-04-05"
  ]
}

Total workouts

Count of all WorkoutSession rows for the authenticated user. Increments by 1 each time you complete and save a session.

Total steps

Sum of the steps field across all sessions. Represents cumulative steps recorded by the foreground step counter service.

Training days

List of unique calendar dates (YYYY-MM-DD) on which at least one session was saved. Used to visualize training frequency.

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Training volume chart

The dashboard renders a line chart of your total volume per session using the MPAndroidChart library (v3.1.0). Each data point on the chart corresponds to the total_volume field of one WorkoutSession. What is volume? Volume is the sum of kilos × reps across every completed series in a session. It is calculated on the Android client in real time during the workout and submitted with the session payload. 
total_volume = Σ (kilos × reps)  for all completed series
A rising volume trend over time indicates progressive overload — you are doing more total work per session than before.
Volume increases when you add weight, add reps, or add sets. You do not need to lift heavier to improve — increasing reps with the same weight also raises volume.

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Historical progression per exercise

Beyond the dashboard, KERN shows you what you lifted last time for every individual exercise when you open a routine. This data comes from GET /routines/{routine_id}. The API finds the most recent WorkoutSession matching the routine name and extracts per-exercise, per-series history from data_json. The matching result is embedded in each series object:
FieldDescription
anteriorHuman-readable string shown in the UI, e.g. "60kg x 10".
prev_kilosNumeric weight from the previous session. Pre-fills the input.
prev_repsNumeric rep count from the previous session. Pre-fills the input.

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Series matching logic

The API builds a lookup map from the last session’s series, keyed by numSerie. For each series in the current routine, it looks up the same numSerie. This is the preferred path because series numbers are stable across routine edits.
If no numSerie match is found — for example, sessions recorded before numSerie was introduced — the API falls back to positional matching: series at index i in the routine is matched to series at index i in the session snapshot.

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The data_json snapshot

Every WorkoutSession stores a data_json column: a complete JSON snapshot of all exercises and completed series from that session. This snapshot is the source for future progression hints. 
[
  {
    "name": "Press de banca",
    "series": [
      { "numSerie": 1, "kilos": 60, "reps": 10 },
      { "numSerie": 2, "kilos": 62.5, "reps": 8 },
      { "numSerie": 3, "kilos": 60, "reps": 9 }
    ]
  }
]
Storing the full snapshot rather than individual series rows means the historical record is immutable. Editing a routine later does not corrupt past session data, and the API can always reconstruct an accurate picture of what was done in any given session.
Session data is write-once. There is no endpoint to edit or delete a past WorkoutSession. If you accidentally finish a session early, the partial data will still be stored and used for progression hints.

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