The dynamic, accurate measurement of pupil size is extremely valuable for studying a large number of neuronal functions and dysfunctions. Despite tremendous and well-documented progress in image processing techniques for estimating pupil parameters, comparatively little work has been reported on practical hardware issues involved in designing image acquisition systems for pupil analysis. Here, we describe and validate the basic features of such a system which is based on a relatively compact, off-the-shelf, low-cost FireWire digital camera. We successfully implemented two configurable modes of video record: a continuous mode and an event-triggered mode. The interoperability of the whole system is guaranteed by a set of modular software components hosted on a personal computer and written in Labview. An offline analysis suite of image processing algorithms for automatically estimating pupillary and eyelid parameters were assessed using data obtained in human subjects. Our benchmark results show that such measurements can be done in a temporally precise way at a sampling frequency of up to 120 Hz and with an estimated maximum spatial resolution of 0.03 mm. Our software is made available free of charge to the scientific community, allowing end users to either use the software as is or modify it to suit their own needs.
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