BRIDGING HUMANS
AND MACHINES
BIOMATICA IS FIRST TO FUSE
COMPLEX HUMAN METRICS WITH DEVICE DATA WITH ULTRA-HIGH EFFICACY.
​​​This allows deep analyses and detailed simulations wherever humans and machines come together.
Sample applications include creating better medical devices, studying pilots in aircraft, designing more effective equipment, etc.
CASE STUDY:
PILOTS AND PLANES
U.S. Navy
01
THE
CHALLENGE
The U.S. Navy had a few problems.
They needed to utilize human data in a holistic way. They had anthropometric, psychological, physiological and other metrics, but not a single model that could track all this in one 'manikin'.
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Then, the Navy needed to combine this manikin with machine data from vehicles, equipment, and new designs. This would allow them to study how human performance, safety, and comfort can be optimized.
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A glaring need for this concept was the PE (physiological episode) issue. Navy planes kept dropping out of the sky, and no one could figure out why. The answer was somewhere in the empty space between pilot and plane data.​​
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Of course, there were standard engineering challenges like importing data from multiple systems, and exporting data to Navy CAD and analysis tools.
02
THE DIGITAL
TWINS
We reorganized the way Navy viewed its data. In order to facilitate unlabored sophistication, the data would have to mirror the real world in a clear way. We fused Navy datasets and open source knowledge to create Digital Twins.
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The Human 'manikin' Digital Twin was composed of three subordinate Digital Twins - Anthropometric, Physiological, and Psychological.
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We created a Digital Twin for human anthropometry. This was created by enriching the ANSUR U.S. Army Anthropometric Survey data.
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Human Physiology was the next Digital Twin. The heard of this Twin was created using a Semantic model modeling relevant characteristics like oxygenation, vision, exertion, etc. This Digital Twin was populated with private Navy datasets and open source knowledge (e.g. medical research papers).
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The last Digital Twin modeled human psychology. This too was created with a Semantic model as the framework, and populated with Navy datasets and open source knowledge.
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The final Digital Twin was for the Aircraft. This was a simpler Twin created using Navy provided datasets.
03
THE DIGITAL
THREAD
Human and machine models are cannot be fused directly. They may be part of the same environment, but research-grade knowledge is needed to understand how they affect each other.
Biomatica Digital Thread was was configured with domain knowledge (e.g. research papers on how pilot eyesight is affected by hypoxia) and datasets (e.g. hypoxia at different altitudes).
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Biomatica threaded all Digital Twins to create the larger interlinked picture. It negotiated the inherent uncertainty in the Twins. For example, anthropometrics always had multiple options and you could select one, while physiological effects were always distributed in a range.
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Biomatica AI was able to assimilate the knowledge in the Twins, and in-between the Twins, to create a global simulation.
04
NEW CAPABILITIES
Biomatica took the Navy from not being able to combine datasets, to a sophisticated simulation that could organize all data in a seamless way.​​
​We created a reusable human Digital Twin with physiological and psychological dimensions. This twin can be interact with any machine, equipment, or environment in the Digital Thread. The Digital Thread can run simulations showing these interactions. All these data and outcomes can be piped to other systems via standard integrations.​
​The big surprise came when our Knowledge Generation AI actually produced new knowledge that was not present in any of its inputs.
Biomatica AI generated new knowledge that is publishable in medical journals.
This is the power of threading diverse knowledge and data - the gaps get filled in.