The conventional noninvasive biological current detection such as electrocardiogram, electroencephalography and surface electromyography can provide electrical reference for diseases diagnosis. Because the bioelectrical signals are the mixed result of the common discharge of sell populations, the spatial resolution of the above bioelectrical detection is relatively limited. In recent years, the acoustoelectric imaging (AEI) has been introduced to spatially code biological current through noninvasive focused ultrasound. Then the electrical signal with precise focus position can be obtained. It can achieve noninvasive detection of biological electrical signals with millimeter-level spatial resolution and millisecond-level temporal resolution which is expected to develop into a new imaging technology for accurately detecting deep electrical activities of living organisms. We firstly describe AEI principle, including acoustoelectric effect and the derivation of acoustoelectric signal equation. Then we briefly introduce characteristics of acoustoelectric signal. It can be seen from the equation of acoustoelectric signal that the acoustoelectric signal depends on the current field and the ultrasonic field. Furtherly, the typical studies of AEI are introduced including acoustoelectric coupling mechanism, AEI methods, acoustoelectric brain imaging (ABI) and acoustoelectric cardiac imaging (ACI). In terms of the acoustoelectric coupling mechanism, the researchers found that the acoustoelectric effect of electrolyte solution is caused by the change of ion molar concentration, ion migration rate and ion viscosity with pressure and temperature, and the acoustoelectric effect coefficient of normal saline is accurate to (0.034±0.003)% MPa^–1. In terms of AEI methods, researchers improved the detection sensitivity, spatial resolution, signal to noise ratio and other performance indicators by improving AEI methods and optimizing AEI systems. In terms of ABI, it can utilize the acoustoelectric coupling mechanism to endow the target area with spatial features of ultrasound, and achieve noninvasive high resolution EEG detection. We review the important research achievements and significance layer by layer from the perspectives of feasibility verification, method system optimization, and clinical application exploration in acoustoelectric imaging. In terms of ACI, it can be used to quantitatively evaluate the spatial distribution and dynamic changes of cardiac current field, providing a new idea for real-time monitoring of cardiac electrophysiological state before and after surgery. We summarize and review the important research achievements and significance of ACI at each stage: in phantom, in vitro and in vivo. Finally, we discuss the future research direction by focusing on the challenges faced by key technical links such as focused ultrasound targeting, ultrasonic spatial coding and decoding, acoustoelectric sensing detection, and imaging system integration, in order to provide basis and inspiration for AEI technology system and clinical transformation.