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Maximizing Data Quality in Life Science Data Acquisition and Analysis

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During this webinar, Brandon Bucher 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 and those interested in the following signals:

Human Physiology: Autonomic, Cardiovascular, Exercise Physiology, Neurophysiology, Cognitive Psychophysiology, Respiratory, Sleep Studies, Tissue and Circulation

Animal Physiology: Autonomic, Tissue and Circulation, Telemetry, Behavior, Sleep and Neuroscience, Cardiovascular Function and 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

Published in: Science
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Maximizing Data Quality in Life Science Data Acquisition and Analysis

  1. 1. 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.
  2. 2. Brandon Bucher Head of Research, ADInstruments Dunedin, New Zealand Maximizing Data Quality in Life Science Data Acquisition and Analysis
  3. 3. InsideScientific is an online educational environment designed for life science researchers. Our goal is to aid in the sharing and distribution of scientific information regarding innovative technologies, protocols, research tools and laboratory services
  4. 4. To access webinar content, Q&A reports, FAQ documents, and information on lab workshops, subscribe to our mail list
  5. 5. Maximizing Data Quality in Life Science Data Acquisition and Analysis Brandon Bucher, Head of Research
  6. 6. You said this is your biggest challenge to high quality data…
  7. 7. Today, we will focus on what is most important Data Acquisition Basics Dealing with Noise ✓ Data Qualification ✓ Artifact Rejection ✓ Repeatability and Reliability ✓ Automation Being Prepared for:
  8. 8. Data Acquisition Basics
  9. 9. Sampling Rate Compare the effects of low and high sampling rates on a signal: Original analog signal If the sampling rate is too low: - Information will be irreversibly lost -The original signal will not be represented correctly If the sampling rate is too high: - No information is lost, but the excess data increases processing time, may give excessive noise in the signal or result in unnecessarily large disk files
  10. 10. Sampling Rate – How do I choose? Compare the effects of low and high sampling rates on a signal: Original analog signal If the sampling rate is too low: - Information will be irreversibly lost -The original signal will not be represented correctly If the sampling rate is too high: - No information is lost, but the excess data increases processing time, may give excessive noise in the signal or result in unnecessarily large disk files • Nyquist Frequency is the minimum • 5-10 times the highest expected frequency is recommended • May also be dependent on calculations and analysis considerations Optimal Sampling Rate:
  11. 11. Amplification, Resolution, and Range
  12. 12. • Try to match your recording range to 2x your highest expected signal amplitude • Keep in mind the resulting resolution Optimal Amplification and Range Amplification, Resolution, and Range - How do I choose?
  13. 13. Filter Settings Original Waveform Note the presence of both high and low frequencies in the signal. Low Pass Filter A low-pass filter allows signal frequencies below the low cut- off frequency to pass, and blocks frequencies above the cut-off frequency. It is commonly used to help reduce environmental noise and provide a smoother signal. High Pass Filter A high-pass filter allows frequencies higher than the cut- off frequencies to pass through and removes any steady direct current (DC) component or slow fluctuations from the signal. Such filters are often used to stabilize the baseline of a signal (i.e. minimize the baseline drift in an ECG signal). Smoothing Processing Original Data Window New Single Data Point
  14. 14. Insert AD Research Education Products Heroes Support Blog Events Company Contact
  15. 15. Data Acquisition Basics - Demonstration
  16. 16. Noise
  17. 17. Noise Tip #1 - Turn it all off, get organized! By 247homerescue [CC0], from Wikimedia Commons Potential Sources of Noise ✓ Computers ✓ Power Supplies ✓ Mobile Phones ✓ Refrigerators ✓ Other Laboratory Instruments
  18. 18. Potential Solutions: ✓ Faraday Cages ✓ Grounding Instrumentation (but avoid loops) ✓ Headstages/Near Subject Amplification ✓ Shielded Cabling ✓ Insulating Cables ✓ Cable/Clutter Reduction Noise Tip #2 - If necessary, protect your instrumentation from interference By Tkgd2007 [CC BY 3.0 (https://creativecommons.org/licenses/by/3.0)], from Wikimedia Commons By UofA RFV [CC BY-SA 3.0 (https://creativecommons.org/licens es/by-sa/3.0)], from Wikimedia Commons
  19. 19. Noise Tip #3 - Choose appropriate filters • Filters can be enabled in your hardware or digitally (post acquisition) • Hardware filters have some major advantages, but are critical to set correctly • Software filters can be enabled at any time, and are editable, but are potentially less effective • Active filters can help with persistent mains noise • Be consistent: don’t just use a filter when you have to, use it on every file if there may be an issue • Smoothing may be appropriate instead of filtering • When it is hard to discern the difference between your signal and noise via frequency • Intermittent “artifact”
  20. 20. Being prepared for data qualification, artifact rejection, repetition, and automated analysis • Use Annotations and Comments liberally • Play by your own rules, but make sure you have some, and that they are consistent • Make Consistent Repeatable Selections for analysis and image export • Use calculations and scripting where possible • Run a sample experiment, find the best approach to your analysis, work back to your protocol, save a settings file
  21. 21. Being Prepared: Demonstration
  22. 22. Brandon Bucher Head of Research, ADInstruments Dunedin, New Zealand info@adinstruments.com www.adinstruments.com/events Twitter: @Adinstruments Connect with ADI #LifeScienceWebinar #ISCxADI Thank You For additional information on the products and applications presented during this webinar please visit www.adinstruments.com

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