  We describe an approach to online analysis of micro-rheology data using a
multi-scale time-correlation method. The method is particularly suited to
process high-volume data streams and compress the relevant information in real
time. Using this, we can obtain complex moduli of visco-elastic media without
suffering from the high-frequency artefacts that are associated with the
truncation errors in the most widely used versions of micro-rheology. Moreover,
the present approach obviates the need to choose the time interval for data
acquisition beforehand. We test our approach first on an artificial data set
and then on experimental data obtained both for an optically trapped colloidal
probe in water and a similar probe in poly-ethylene glycol solutions at various
concentrations. In all cases, we obtain good agreement with the bulk rheology
data in the region of overlap. We compare our method with the conventional
Kramers-Kronig transform approach and find that the two methods agree over most
of the frequency regime. For the same data set, the present approach is
superior to Kramers-Kronig at high frequencies and can be made to perform at
least comparable at low frequencies.
