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LabOS Closed-loop, Protocol-driven, Data Acquisition & Experiment Control
Phone: () -
Phone: (415) 561-1703
Type: Domestic Nonprofit Research Organization
DESCRIPTION (provided by applicant): Significant Aims: Biomedical research, human performance and other laboratories that work with living subjects and perform complex experiments unanticipated by software "solution" providers, must expend significant resources creating & maintaining data acquisition and control (DAQ&C) systems that are seldom useful in other labs because of their complexity or poor documentation, and quickly become obsolete because of design limitations and hardware dependencies. We have a working prototype of a DAQ&C system, called "LabOS" that  is usable at "Operator", "Experimenter" and "Programmer" levels, and provides  deterministic ("hard") closed-loop control at kilohertz rates,  high speed buffered sampling (eg, for spike profiling),  multi-thread, state machine based, data-contingent, experimental protocols, and  a modern, richly informative, realtime graphical interface for viewing & controlling ongoing experiments,  on multiple platforms, with no dependence on unusual or single-source hardware. We now propose to  segment & harden the system so that user modifiable parts are easily & safely reconfigured, and other parts are invisible,  generalize certain aspects of LabOS to support its widest possible use,  provide data export tools,  optimize platform independence  produce contextual, reference and tutorial documentation,  support a web-based component library, and  conduct a beta test program to evaluate the experiences and suggestions of initial users, in an extended development cycle. Methods: LabOS is written in "G" under LabVIEW-RT(r). The LabOS Console runs under Mac OS X, Windows or Linux. The LabOS Server & Controller run under Ardence PharLap ETS(r) on any National Instruments(TM) real-time hardware target, including PXI chassis, PCI boards, and some desktop PCs. Public Health Relevance: Acquisition of well-controlled, experimental data defines empirical science, and yet, available DAQ&C systems are incapable of supporting complex experiments, require ongoing programmer support, or support only specialized, popular paradigms. A DAQ&C system providing the power and flexibility to perform innovative biomedical experiments would be of great scientific and fiscal value.
* Information listed above is at the time of submission. *