SLAA843A August   2018  – March 2019 MSP430FR2512 , MSP430FR2512 , MSP430FR2522 , MSP430FR2522 , MSP430FR2532 , MSP430FR2532 , MSP430FR2533 , MSP430FR2533 , MSP430FR2632 , MSP430FR2632 , MSP430FR2633 , MSP430FR2633

 

  1.   Sensitivity, SNR, and design margin in capacitive touch applications
    1.     Trademarks
    2. 1 Overview
      1. 1.1 Design Objectives
        1. 1.1.1 Reliability
        2. 1.1.2 Robustness
      2. 1.2 The Designer's Dilemma
    3. 2 Recommended Actions for Developers
      1. 2.1 Run SNR and Design Margin Tests
    4. 3 Terminology
      1. 3.1 Signal (S)
      2. 3.2 Noise (N)
      3. 3.3 Threshold (Sensitivity) (Th)
      4. 3.4 Design Margin
        1. 3.4.1 False Detection Margin (Min)
        2. 3.4.2 Detection Margin (Mout)
      5. 3.5 Signal-to-Noise Ratio (SNR)
      6. 3.6 Advice
    5. 4 CapTIvate Device Performance
      1. 4.1 Minimum Recommended Values
      2. 4.2 CapTIvate Device SNR
    6. 5 Interpreting the Results
      1. 5.1 Interpreting the Advice
      2. 5.2 Check Other Results
    7. 6 Application of Terms
      1. 6.1 Count and Percent Change Analysis With 7.5-mm Overlay, Advice = POOR
      2. 6.2 Count and Percent Change Analysis With 1.5-mm Overlay, Advice = GOOD
      3. 6.3 Count and Percent Change Analysis (1.5-mm Overlay vs 7.5-mm Overlay)
      4. 6.4 Effect of Post-Processing and Sampling Rate
    8. 7 Summary
  2.   Revision History

Design Margin

While SNR is a good indicator of the signal level with respect to the noise level, it is not the only metric to consider when designing for reliability and robustness. This is where design margin analysis comes in. Design margin, borrowed from threshold-based digital logic noise margin analysis, is very useful for threshold based systems, as it addresses the main limitations of SNR. Design margin analysis takes the detection threshold into account and analyzes the margin of the OFF state and the ON state. The following sections describe both parameters and their importance. Unlike SNR, the design margin parameters are very repeatable across multiple measurements.