Searching events in AFM force-extension curves: A wavelet approach

Area of Science:

• Atomic Force Microscopy (AFM)
• Spectroscopy
• Signal Processing

Background:

• Atomic force microscopy (AFM) force spectroscopy generates force-extension curves to study molecular interactions.
• Detecting discrete events, such as tethers, in these curves is crucial but challenging.
• Signal discontinuities characterize these important events.

Purpose of the Study:

• To introduce a novel algorithm for automatic event detection in AFM force spectroscopy.
• To leverage wavelet scalogram energy for identifying signal discontinuities.
• To apply the algorithm to tether analysis in AFM force-extension curves.

Main Methods:

• The algorithm is based on analyzing the energy decay rates of the wavelet scalogram.
• Faster decay rates indicate regular signal regions, while slower rates pinpoint singular points (discontinuities).
• Peaks in the scalogram energy plot correspond to event locations.

Main Results:

• Wavelet scalogram energy exhibits distinct decay patterns at regular versus singular signal points.
• These differences generate detectable peaks in the scalogram energy, marking event locations.
• The algorithm successfully detected events in AFM force-extension curves during tether analysis.

Conclusions:

• The wavelet scalogram energy-based algorithm provides an effective method for automatic event detection in AFM force spectroscopy.
• This approach reliably identifies signal discontinuities, improving the analysis of force-extension curves.
• The algorithm is particularly useful for detecting tethers and similar events in AFM experiments.