How to Record Squat Videos for AI‑Powered Analysis

The squat is a cornerstone of athletic training and rehabilitation. Whether you're aiming to build strength, improve mobility, or recover from injury, how you perform this essential movement matters. Thanks to artificial intelligence, we can now move beyond visual guesswork and analyze squat mechanics with precision — as long as the video is captured correctly.

In this guide, you’ll learn how to record high‑quality squat footage so the AiKYNETIX Web Platform (or iOS app) can deliver meaningful, data‑driven insights into your movement.

---

Why Analyze Squats with AI?

Squats involve coordinated movements across the ankles, knees, hips, pelvis, spine, and shoulders. Subtle misalignments or compensations can reduce performance or lead to injury. AI‑based analysis like AiKYNETIX calculates joint angles, movement symmetry, range of motion, and deviations in real time, then translates them into clear reports and actionable recommendations.

AI‑Powered Squat Breakdown

---

Step 1 | Set Up the Recording Environment

✔ Choose the Right Space

• Flat, non‑reflective surface — avoid carpets or uneven terrain.

• Open area with no moving people or pets in the background.

• No mirrors or windows that could create glare or duplicate your image.

✔ Optimize Lighting

• Use natural light or diffuse LED lighting from multiple angles.

• Eliminate harsh shadows.

• Don’t film in front of windows or under direct spotlights.

✔ Wear the Right Gear

• Form‑fitting clothing (compression shorts, leggings, tanks).

• Solid, contrasting colors to help the AI distinguish limbs.

Recommended Recording Environment

---

Step 2 | Camera Setup for Optimal Capture

✔ Use a Stable Setup

• Mount your phone or camera on a tripod at hip‑to‑waist level (~1 m / 3 ft).

• Hand‑held is possible, but shaky footage can ruin tracking quality.

✔ Record from Multiple Angles Capture three views in a single session:

1. Front (facing the camera)

2. Left side

3. Right side

• Keep your entire body — head to toes — in frame at all times.

• Record at 1080 p / 30 fps or higher.

Capturing Three Views

---

Step 3 | Perform a Controlled Overhead Squat

The overhead squat is a gold‑standard diagnostic movement.

✔ Execution Checklist

• Stand tall, feet shoulder‑width apart, arms raised overhead.

• Squat slowly and with control, keeping arms upright.

• Avoid bouncing or rushing the descent and ascent.

• Perform one full squat per camera angle.

Overhead Squat Position

---

Step 4 | Upload to the AiKYNETIX Platform

1. Go to the AiKYNETIX Web Platform or open the iOS app.

2. Select “Mobility Assessment.”

3. Follow the upload prompts and submit your video.

4. Within minutes you’ll receive a Session Summary with:

   • Mobility & Technique scores

   • Joint angles (hip, knee, ankle, spine, shoulders)

   • Symmetry analysis

   • Personalized recommendations

Uploading to AiKYNETIX

---

Step 5 | Interpret and Apply Your Results

Your report may include:

• Joint Flexion Angles (e.g., hip 83°, knee 84°)

• Asymmetry Reports (e.g., right hip abduction weaker than left)

• Recommended Exercises (e.g., side‑lying clamshells 3 × 15 reps)

• Progress Tracking over time

For athletes, this exposes weak links limiting performance. For therapists, it provides objective baselines to guide rehab.

---

Benefits of AI‑Based Squat Analysis

✅ Early detection of imbalances and dysfunctions ✅ Evidence‑based training adjustments ✅ Objective rehab progress monitoring ✅ Accessible anywhere — no expensive lab equipment ✅ Motivating — visible improvement over time

Performance Progress Graph

---

Final Thoughts

Incorporating AI‑powered video analysis into your training or rehab workflow is a game‑changer. With the right setup and a reliable tool like AiKYNETIX, you gain biomechanics‑lab quality insights at home or in the gym.

Better data → Better decisions → Better outcomes → Better movement.

---

Further Resources

• AiKYNETIX Web Platform — advanced features for professionals

• Run AiK • Jump AiK • Lift AiK — on‑the‑go analysis apps

---