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Garry Allison
04-10-1997, 05:51 PM
We are currently assesing the rate of decay / relaxation of EMG signal
amplitude as a result of a perturbation to the body.

We have attempted to identify the 'damping' constant for the data using an
exponential best fit algorithm. From our modelling data we have found that
the damping constant from the best fit is accurate when the data are
truncated and there is a smaller tail of randomised baseline noise.
Similarly from our modelling of data (exponential curve with random noise)
the number of data points required to obtain an accurate fit is influenced
by the signal to noise ratio, and the dampening coefficient & sample
frequency.

We believe that it seems logical to truncate the data when the signal
returns to say (twice) the power (RMS) of the pre-stimulus EMG signal
amplitude. However we open this issue to discussion (with appropriate
summary).

Another option is to attempt smooth the data and calculate the duration
between the paek and half of the amplitude - half relaxation duration. I
believe the filtering will be problematic since the frequency domain is
likely to be similar however, two questions arise, i). should the half
relaxation rate be calculated from the filtered, exponential best fit or
polynomial best fit data, ii). are there other methods of assessing rates
of decay / half relaxation rates etc etc.

Cheers
Garry.


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Garry T Allison PhD. Lecturer,
School of Physiotherapy, email:iallison@info.curtin.edu.au
Curtin University of Technology, Tel. +61 9 351 3648
Selby Street, Shenton Park, Fax. +61 9 351 3636
Western Australia 6008

Tel. +61 8 9266 3648 (after 5/May/97)
Fax. +61 8 9266 3636 (after 5/May/97)
http://www.curtin.edu.au/curtin/dept/physio/pt/staff/allison/
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