Selectable signal conditioning—filter or transform data as it is being collected
The RSP100C is designed for direct physical measurement of respiratory effort. Each RSP100C amplifier requires one TSD201 respiration transducer.
The RSP100C works with the TSD201 transducer to measure abdominal or thoracic expansion and contraction while breathing. The RSP100C permits DC coupling to the TSD201 for the recording of respiratory effort signals of arbitrarily low frequency. Front panel controls allow selection of absolute or relative expansion/contraction measurements.
The RSP100C is part of a complete research system, interfacing with the MP160 data acquisition and analysis platform and AcqKnowledge software, allowing advanced analysis for multiple applications and supporting acquisition of a broad range of signals and measurements.
Amplifiers snap together for easy system configuration and re-configuration.
Powerful automated analysis. Instantly & easily view, measure, analyze, transform, and report data.
Flexible, proven modular data acquisition and analysis system for life science research.
New Automation Tool Saves Time and Improves Data Consistency
Workflow’s drag-and-drop interface allows you to automate and repeat the signal-conditioning and processing steps your protocol requires in an easy-to-use process without programming or scripting.
– Batch process multiple files with confidence that they’re all processed using the same procedure.
– Expedite signal conditioning and preparation for analysis with a standardized and automated approach.
– Extract measurements, analyze data and get results faster, for meaningful scientific insights.
– Save and share workflows with others in your team to help reduce training time and increase collaboration.
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Register NowAcqKnowledge is an interactive, versatile software program that allows you to manage data in real time. Perform complex data acquisition, stimulation, triggering and analyses using intuitive navigation. Here are some recent AcqKnowledge citations… The nature of vicarious embarrassment. Journal of Business Research, 153, 355-364. Ziegler, A. H., Allen, A. M., Peloza, J., & Norris, J. I. (2022). […]
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