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.
