On a very basic level it was important to create and provide an extendable setup.  Furthermore a non-deterministic system, which is open in the way, that it can react differently to various situations by changing the processes in it selves.

Raw sensor data enters a processing unit, which consists of a number of different sub-units. The processing unit has the function of generating “meaningful” symbols. A symbol is constructed from sensor input that is transferred to a uni-modal dataset. Several uni-modal sets together form a multi-modal dataset. Then via clustering, a kind of pattern recognition, a new symbol is created according to similar features. A symbol contains all dimensions, which we sense for a certain amount of time but compressed to clusters, which can be processed further. In this process it is not only about each information channel which comes in, further more they are highly dependent on each other. In the last step the symbol is evaluated based on certain rules and sent to the actuator unit. All available sensor data at a given time is stored as a multi-modal dataset or snapshot, like a single frame in a video. As the amount of gathered snapshots increases, patterns emerge of which one pattern that is strong enough will eventually be stored as a symbol. The person wearing the device supports this process by identifying meaningful symbols in adding subjective evaluations to the dataset via the user input channel. Once a symbol is established and sufficiently appreciated by the wearer, the device will become a guide that communicates the presence of a symbol via its output functions, thus amplifying, highlighting, and emphasizing what originally has been assigned as subjectively valuable to the carrier. In the end we have coded and abstract information (symbols), which describes a multiplicity of conditions.

In addition to the sensors, we have actuators, programmed to vibrate in different frequencies. Furthermore there are two speakers emitting sound at a different frequency. To make a decision about what specific symbol and which values within it will inform which actuator, we invented a kind of pattern recognition system. It is based on the idea that each of the actuators (output channels) is sensible for a certain range of values transmitted by single symbols. Through the algorithm we gain a multi-dimensional output that has the ability to describe an abstract symbol in such way that it may be experienced in physical manner. This process of translation has the advantage of compressing very complex information perceptible.

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