Gastric motility is in part coordinated by bio-electrical slow waves. The wavefront orientation of the slow wave contains vital physiological information about the motility condition of the gastrointestinal system. Dysmotility was shown to be associated with dysrhythmic propagation of the slow wave. The most commonly used method to detect wavefront orientation is computationally expensive because of the involvement of activation time identification. The information of local directionality contained in bipolar slow wave recordings could be used to detect the wavefront orientation. An algorithm called bipolar direction detection was developed to utilize the information contained in the bipolar slow wave recordings. Bipolar recordings were constructed by subtracting the unipolar in vivo recordings of directional electrode pairs. Then, time delay information was used to detect the wavefront direction. The algorithm was verified using synthetic data and validated using experimental data. Ten high-resolution in vivo slow wave signals from 5 pigs were recorded for a duration of 2 minutes. The performance was compared against the semi-automated approach, resulting in an average angle error of 20° for the experimental data. The algorithm was able to detect slow wave wavefront orientation with minimal errors rapidly.Clinical relevance-The ability to rapidly detect slow wave propagation direction will enable effective analysis of large data sets, through which we can obtain a better understanding of functional motility disorders and help with diagnosis and treatment.