The document proposes using biofeedback methods to facilitate knowledge transfer by quantifying tacit knowledge. It hypothesizes that 1) tacit knowledge is partially externalizable by observing reactions, 2) mental and affective processes are coupled in the brain and subtle physiological changes reflect learning, and 3) personal discovery occurs through social comparison. The approach involves biomonitoring participants during tasks to build a database of physiological "fingerprints" of behavior across demographics. Data synthesis would integrate signals into models to extract representative parameters of tacit knowledge.

1. Bio-feedback methods for enhancing
knowledge transfer
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2. Proposal
The Knowledge Based Society defines HUMANS as the
source of creation. Knowledge becomes the main
asset. Management and creation of knowledge
become an important drive for development.
Tools and methods to facilitate knowledge transfer;
focus on tacit knowledge
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3. Hypothesis 1
Tacit knowledge is only partially externalizable: the
person is often unaware of it, or cannot explain it;
This knowledge is attained through personal
experience, therefore is connected to the person’s
history.
To access it, one has to observe the subject’s reaction
to tasks and situations, and be able to quantify or
objectify it.
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4. Hypothesis 2
There is a strong Mental/Affective coupling in the brain;
Through hormonal release, mental and affective
processes influence physiology throughout the body!
Subtle changes in these signals, or specific
patterns thereof, can be associated with
learning and personal development, reflecting a
“re-organization” of brain processes.
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5. Hypothesis 3
Personal discovery occurs through comparison with
others; quantifying differences in perception, abilities,
and attitude between people can vastly improve
mutual understanding, knowledge transfer, career
management, etc…
Database of signal parameters for different
ages, cultures, etc.
Not a model, but a heuristic
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6. Approach: biomonitoring and biofeedback
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7. Parameter space
”fingerprint”
of behavior
Behavior
Parameters
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8. Parameter space
Results of 4
different
physical
exercises
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9. Data Synthesis
Subject 1
Testing Integration
(e.g., PCA + neural nets)
Subject 2 Signal
Database
Vectorization
Subject n A representative set
of signal estimators
Modeling &
Signal processing
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10. Database
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