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Everything the room is doing, once a second.

Every readout on this page comes from the same model. Nothing here is sold to a hospital today, and the work so far has run against a public dataset of simulated surgery on a phantom. No clinical footage yet.

  1. Capture

    Ceiling-mounted cameras cover the scrub field, the instrument table, the gowning zone and the door. Ordinary cameras only, with no depth sensor in the room.

  2. State

    Once a second, Gray-1 answers who is in the room, in what role, who is scrubbed, and what is close to what. That answer carries across the whole case, so people who turn away from a camera are not lost.

  3. Readouts

    Phase, sterile technique, traffic and care-bundle events are all read off that one answer, which is why they cannot contradict each other.

  4. Record

    Only anonymised event records leave the device: a timestamp, an event type, and what it referred to. Raw video stays in the room.

The five readouts, and what each one is read from

Surgical phase

00:14 of 00:50

Decided once a second

The room is isolating Surgical phase.

Surgical phase

under development

Where the case is, decided while the case is running. Anaesthesia prep, surgical prep, surgery, wrap-up.

Phase is the spine of every other readout. Turnover intervals, sterile-phase traffic and care-bundle timing all depend on the team agreeing where the case started and stopped.

The decision is made live and never revised, which is harder than labelling a recording afterwards and is the only version that is useful to a team in the room.

Decided once per second while the case runs, and developed against a public dataset of simulated surgery on a phantom. No clinical footage yet.

Sterile technique

open research

Contact between sterile and non-sterile: gown and glove breaches, field contact, instrument handling, gowning sequence.

This is the hardest of the five and we are not claiming it works yet. A better model of the room does not automatically catch more breaches, and our own testing has not shown that it does.

A monitor that flags constantly is worse than no monitor, so we count false alarms with the same weight as misses.

A breach and the phase it happened in come from the same description of the room, so the two can never contradict each other.

Traffic and turnover

open research

Door events and person counts during sterile phases, and the interval between one case closing and the next opening.

Turnover is the number theatre managers already fight over, and it only means anything if the end of one case and the start of the next are called the same way every time.

Nothing counts people separately. The same description of the room that gives you phase gives you who was in it.

Every additional entry during a sterile phase degrades operating-room air, which is the documented mechanism linking traffic to infection risk.

Care-bundle events

open research

The prevention checklist as timestamped events: skin prep, gowning and gloving, timeout, count, sterile-field discipline.

Prevention bundles are checklists that hospitals are audited on and that nobody can actually measure. Making them measurable is the reason the company exists.

The events are read from video. Nothing is typed in by a member of staff, and nothing is reconstructed from the notes afterwards.

The checklist comes from our own clinical team and follows the prevention bundle a theatre already works to. No outcome data yet, on any site.

Metric 3D twin

open research

A metric reconstruction of the room from multi-view RGB alone, in which every point carries an entity label.

Most sterile-technique rules are really questions about distance: how close, how far, did it touch. Those cannot be answered from flat video.

It also means a ceiling camera and no other hardware. Depth sensors in a working theatre are a procurement and sterilisation problem before they are a technical one.

Cameras only, with no depth sensor in the room. Distances are checked against a laser measurement of the same scene.

Fifty seconds of simulated knee surgery on a phantom, from a public dataset, reconstructed by our own model from ordinary cameras. Each path is the floor position of one labelled role, once per frame. Held at one second. Rendered in your browser.