Ca2+ Sparks Detection and Classification using Gaussian-Mexican Hat Wavelet

It is evidenced that Ca²⁺ plays a critical role in cell activities. Understanding and analysis of a Ca²⁺ sparks event can provide critical information in cell communications. It is known that a Ca²⁺ spark spatial spread in a local area can be modeled by a Gaussian distribution. There are some available methods in Ca²⁺ spark detection, but little research has been done to quantitatively analyze and classify the Ca²⁺ sparks into single or multiple release events. In this paper, a new method based on Gaussian-Mexican Hat Wavelet is proposed to automatically classify Ca²⁺ sparks into single release events or multiple releases events. Then Ca²⁺ sparks from single release events are further categorized into different energy levels. The experiment results using mouse skeletal muscle fiber cells show this method is promising.