Maximizing Data Quality in Life Science Data Acquisition and Analysis

Maximizing Data Quality in Life Science Data Acquisition and Analysis

Brandon Bucher, Head of Research at ADInstruments, shares best practices, technical considerations and expert advice on how to avoid common data acquisition system and data analysis mistakes in order to produce higher quality data.

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There are many variables to consider when designing a preclinical research experiment, and while scientists plan their studies to a high degree, the critical function of digital data acquisition and analysis systems is often overlooked. The technical nature of this subject can be daunting, demanding time and head-space from extremely busy investigators; however, understanding the essential elements of digital data acquisition and analysis is fundamental to ensure high quality experimentation translates to high quality results.

In this webinar, Brandon Bucher, Head of Research at ADInstruments, lifts the veil on common, costly and harmful data acquisition and analysis errors, showing how to avoid them in order to produce optimal data and quality results. He covers key concepts such as setting up your data acquisition system correctly, proper signal conditioning, artifact rejection and preparing data for analysis, exporting data and how elements of your experimental protocol may impact decisions made at each stage.

Content covered in this webinar is most relevant to scientists in the following research fields, studying various signals and physiologic measurements:

Human Physiology

  • Autonomic
  • Cardiovascular
  • Exercise Physiology
  • Neuro
  • Psychophysiology
  • Respiratory
  • Sleep Studies
  • Tissue and Circulation

Animal Physiology

  • Autonomic
  • Tissue and Circulation
  • Telemetry
  • Behavior, Sleep and Neuroscience
  • Cardiovascular Function
  • Cardiac Electrophysiology
  • In vitro Pharmacology
  • Isolated Tissue and Organ Electrophysiology

Signals / Measurements

  • Angles
  • Dissolved Gasses
  • dP/dT
  • ECG
  • EEG
  • Electrical Stimulation
  • EMG
  • EOG
  • Extracellular Recordings
  • Fluid Flow
  • Force
  • Glucose
  • GSR
  • Heart Rate
  • Intracellular Recordings
  • NIBP
  • pH
  • Pressure
  • Pulse
  • RER
  • Respiratory Flow
  • Respiratory Gas Analysis
  • Sounds
  • SpO2
  • Temperature
  • Tissue Perfusion
  • Video
  • Volume

Whether you are a technician tasked with running experiments that utilize a time-based data acquisition system, or you are responsible for designing and executing a data analysis workflow, this webinar will provide a solid foundation and a deeper understanding of the key factors to consider regarding your instrumentation and digital tools.

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Brandon Bucher

Head of Research,
ADInstruments
Dunedin, New Zealand

Brandon Bucher has spent the last 11 years working alongside life science researchers at ADInstruments, leveraging that experience to advise investigators on how to get the most out of their scientific instrumentation and achieve high-quality results in their data acquisition software. Brandon earned a BS in Bioengineering from Washington State University in 2006, and began his career at ADInstruments as a Biomedical Sales Engineer in 2007. Since that time, Brandon has gained experience in scientific sales, support, product management and development; allowing him to gather a wide range of application knowledge in life science research. Since becoming Head of Research at ADInstruments, Brandon has lead the research development and product management teams, connecting the needs of customers to ADInstruments product development.