The recording determines the measurement
Everything after this is arithmetic. What is not in the recording does not come out of it. Tape this page up beside the treadmill.
First and most important: slow motion on
Sixty frames per second minimum, 120 or more preferred. An ordinary 30 fps clip is not enough: initial contact and toe-off then fall between frames, and a contact time of two hundred milliseconds is built from six frames. One frame out is already sixteen per cent.
Any phone from the last few years does 120 frames per second; it usually sits under a separate mode called slow motion or slo-mo. Check it once and then leave it. The app measures the frame rate itself and warns before computing if it is too low.
The camera
- 1
Still
On a tripod. Not handheld, not following: the background then moves and the scaling stops holding. Image stabilisation that shifts the frame can go off too.
- 2
Square on
Directly from the side or directly from behind, not at an angle. At ten degrees off, angles are already measurably flattened by the projection. The app detects an oblique view and reports it, but it cannot correct it.
- 3
At hip height
Roughly level with the iliac crest. Filming from above or from floor level gives a perspective in which either the upper body or the foot is systematically distorted.
- 4
Far enough away
Three to four metres, with the whole person in frame including the feet and some room above the head. Zooming from further back beats standing close: it reduces distortion at the edges.
The runner
- Close-fitting clothing, or at least trousers that do not flap around the leg
- Bare ankles or a low sock: the model looks for the heel, and it has to be visible
- The shoes the patient normally wears, and at re-measurement the same ones
- Warm up first. For the first thirty seconds on a treadmill people do not run the way they run
- A steady, sustainable speed; note it down, because cadence and step length depend on it
The room
- Even light, and rather too much than too little: in low light the shutter opens longer and a moving leg blurs
- No backlight and no window behind the runner
- A calm background helps; a busy one is usually not a problem
- Other people out of frame: detection tracks the right person, but why take the risk
Two views where possible
From the side come the sagittal measures: foot strike angle, knee flexion, hip extension, trunk lean, overstride. From behind come the frontal ones: pelvic drop, hip adduction, knee valgus, the foot crossing the midline.
They are two separate recordings and two separate analyses. The app recognises which view it has and reports only what that view supports. An oblique recording yields some of both and enough of neither.
Duration
Twenty seconds is ample. At 120 frames per second that is two thousand four hundred frames and around twenty-five stride cycles per leg, enough to average over and to quote a spread that means something.
Longer is possible but costs compute time without adding much. Shorter than ten seconds gets awkward: the report then notes there were too few cycles, and the average is an average of few.
Frequently asked
- Do I have to enter the person’s height?
- For measures in centimetres and metres, yes: those are scaled on the height of the person in frame. Leave it blank and angles and times still hold, they need no scale: and the distance measures drop out.
- Does a portrait recording work?
- Not ideally for a side view: the forward movement then falls out of frame. For a rear view on a treadmill it is fine, because the person stays roughly in place.
- Can the treadmill have handrails?
- A rail crossing in front of the pelvis can occlude the pelvic point, which shows up as warnings about missing points. Film so that the iliac crest is clear, or use a treadmill without a rail on the camera side.
- What do I do when the app says the recording is no good?
- Read what it says and record again. That costs two minutes. Using a measurement the app says is wrong costs more later.
Record one and load it in
The app measures the frame rate itself and says whether the view and framing are sound, before the computing starts.
Get startedRead further
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What camera-based analysis can and cannot do against IMU sensors, a gait lab and assessment by eye. Including the places where the others win.
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