The Video Form-Review Workflow Checklist
Run AI-assisted form review without losing the client. 5 sections, 30 items: set your auto-flag rules, triage the queue, run the QC gate that catches confidently-wrong passes, and use 4 ready-to-send client scripts that turn a machine flag into a coached moment. Automate the detection; own the coaching.
Automate the detection. Own the coaching.
Single-camera markerless pose estimation carries roughly a 5.8° joint-angle error — its own reviewers call it a "screening aid, not a measurement instrument." This checklist operationalizes two frameworks so you run AI-assisted review at volume without commoditizing your judgment or losing the client.
The two frameworks at a glance
| Layer | Owner | What happens |
|---|---|---|
| DETECT | The machine (automate) | Rep count, tempo, ROM/depth, bar path, gross joint-angle deviation. Objective, repeatable, high-volume. |
| INTERPRET | You (human) | Is that knee cave mobility, fatigue, fear, a cue misunderstanding, or a loading error? Read the person. |
| DECIDE | You (human) | Does this need a cue, a load change, a regression, a referral, or nothing at all — for this client? |
| DELIVER | You (human) | Say it so the client trusts it, acts on it, and stays. A verdict informs; a coach changes behavior. |
- 1Set auto-flag rules (Section 1) — define what the AI layer screens for. Clean passes; flagged rises.
- 2Triage the queue (Section 2) — the clean ~80% get a fast confirm; the flagged ~20% get your full attention.
- 3Human-review the flagged set + a random sample (Sections 2–3) — always eyeball every flag and a random slice of the passes, because confidently-wrong failures hide in the passes.
- 4Close the loop with the client (Section 4) — deliver the interpretation as coaching, tied to what you track over time.
Automate DETECT. Own the rest.
What the camera can and cannot do (keep this honest)
Counting reps, tracking tempo, measuring range of motion and squat depth, tracing bar path, and flagging gross joint-angle deviation on well-lit, well-documented compound lifts (squat, bench, deadlift). It never gets tired on the 40th video, it is consistent, and it is instant.
Distinguishing pain from mobility from fatigue from fear from a cue misunderstanding; reading load, muscle co-activation, or control (it reads position, not loading); handling occlusion, depth ambiguity, and out-of-plane rotation; and judging novel, heavily loaded, or client-specific movements. Single-camera markerless systems land around 5.8° joint-angle error (SensAI, 2026), corroborated near 2.31° ± 4.00° in systematic review (MDPI, 2025) — good enough to screen, not to judge.
Treat every vendor accuracy claim (AiKYNETIX "80%/95%", Ray AI "82–90%") as vendor-claimed, not independently validated.
What’s inside
- 1Setup — Configure Your Auto-Flag Rules7 items · DETECT
- 2Triage — Working the Review Queue6 items · TRIAGE
- 3Interpret & Decide — The Human Judgment Gates6 items · INTERPRET + DECIDE
- 4Deliver — Client-Communication Scripts6 items · DELIVER
- 5Guardrails — Liability & Duty of Care5 items · DUTY OF CARE
Run AI-Assisted Form Review Without Losing the Client
Drop your email to unlock the full 30-item workflow — the auto-flag thresholds you copy into your vendor tool, the human judgment gates, the 4 fill-in-the-blank client scripts with copy-to-clipboard, and the liability guardrails. Your on-screen progress is auto-saved either way.
- All 30 items across 5 sections — Setup, Triage, Interpret & Decide, Deliver, Guardrails
- The exact rep/tempo/ROM/bar-path/joint-angle flag thresholds to configure
- 4 fill-in-the-blank client scripts with one-tap copy
- Refer-out triggers + documentation + vendor/ToS liability questions
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