Camera, smartphone sensor or wearable: which is best for measuring movement?

Why there is no universal winner

These three approaches sense fundamentally different things. A camera observes where the body is in space. An inertial sensor senses how the body is accelerating and rotating. A wearable accumulates activity over hours and days.

Asking which is best is like asking whether a ruler is better than a stopwatch. The useful question is which one answers the measurement question in front of you — and often the answer is more than one.

Camera and computer vision

Best suited to visible joint position, joint angles, range of motion and repetitions.

• Strengths — measures where limbs actually are; requires nothing attached to the person; naturally suited to joint angles and range of motion; the video itself can be reviewed.
• Limits — depends on camera position, lighting and an unobstructed view; single-camera analysis struggles with out-of-plane movement; agreement with laboratory measurement is movement-specific.
• Use it when the question is about a joint: how far it moves, through what arc, how many times, how consistently.

MoveLab’s 2024 peer-reviewed validation of markerless joint-angle and range-of-motion measurement illustrates both sides: strong agreement for clearly visible single-plane movements, weak agreement where the joint was obscured or the movement less cleanly planar.

Smartphone inertial sensors

Best suited to gait and temporal or spatiotemporal movement measurement.

• Strengths — the sensor is already in the person’s pocket; unaffected by lighting or camera framing; excellent at detecting the timing of repeating movement events; cheap to repeat often.
• Limits — senses movement of the phone rather than position of the limbs; accuracy is parameter-specific; a single waist-positioned phone cannot readily separate left from right; sensor behaviour varies between handsets.
• Use it when the question is about walking: how fast, how many steps per minute, how long each phase of the gait cycle takes.

MoveLab’s 2025 peer-reviewed validation found temporal gait measures agreed most closely with marker-based motion capture, while double-support measures were markedly weaker.

Wearable activity data

Best suited to contextual and longitudinal activity information.

• Strengths — continuous over days and weeks; captures what the person actually does rather than what they can do on demand; already worn by many people; good at trends.
• Limits — not a precise measure of movement quality; devices and algorithms differ in how they count and estimate; data quality depends on the person wearing and charging it.
• Use it when the question is about behaviour and change over time: is this person doing more, moving more consistently, recovering?

Side by side

Choosing by question rather than by technology

1. 1State the measurement question precisely — “has knee range of motion improved?” is a different question from “is she walking faster?”
2. 2Identify which modality directly senses the quantity in that question.
3. 3Check what evidence exists for that specific measure, in a comparable population and setting.
4. 4Consider what the person can realistically complete unsupervised and repeatedly.
5. 5Decide what constitutes a meaningful change before you start measuring.
6. 6Combine modalities only where each is answering a distinct part of the question.

How MoveLab uses different modalities

MoveLab’s approach is to select the modality according to the measurement task rather than commit to a single sensing method.

• Camera-based analysis for joint angles and range of motion, where seeing limb position is what matters.
• Smartphone inertial sensing for gait and functional mobility, where the timing of movement events is what matters.
• Wearable activity data as longitudinal context, showing what happens between assessments.

The measures sit alongside each other for the same person over time, so a clinician can see an assessed change and the activity context around it together.