Title: Biofeedback methods for enhancing knowledge transfer
1Bio-feedback methods for enhancing knowledge
transfer
Florin Munteanu, Center for Complexity Studies,
Romania
2Complicated vs. complex
- A complicated system can be modeled and
controlled its setup is predetermined its
behavior is predictable it obeys clear causality
and operation rules.
A complex system is not represented by a single,
stationary model it is plastic it evolves
within its environment it can self-organize its
internal structure it switches from one
operation mode to another depending on stresses
in the environment (phase transitions) it
shows a loose cause-effect connection.
3Consequences
- Approaching and harnessing Complexity requires a
fundamentally different approach - Identifying patterns of behavior fingerprints
of each state - Identifying behavior discontinuities, clues for
re-organization - New approaches to data processing, which
explicitly account for non-linearity, memory,
scale-dependence, etc - New experimental protocols
4Proposal
- 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
5Hypothesis 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 persons history.
6Hypothesis 2
- There is a strong Mental/Affective coupling in
the brain - Through hormonal release, mental and affective
processes influence physiology throughout the
body!
7Hypothesis 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
8Approach biomonitoring and biofeedback
9Parameter space
fingerprint of behavior
Behavior Parameters
10Parameter space
Results of 4 different physical exercises
11Data Synthesis
Subject 1
Integration (e.g., PCA neural nets)
Testing
SignalDatabase
Subject 2
Vectorization A representative set of signal
estimators
Subject n
Modeling Signal processing
12Database