Study of chewing activity during oral processing is essential in many aspects, as in food characterisation, industry, dietary behaviour assessment, and health management. Photoplethysmography (PPG) is an alternative method based on the monitoring of blood volume changes in particular tissue that can be used to observe chewing activity. This study proposed an algorithm to extract chewing activity using PPG method followed by comparison with video and electromyography (EMG) methods. Participants were asked to consume an apple, bread, and yoghurt in randomised order while monitored by video, PPG and EMG sensors. The detected total number of chews and chewing frequency were not statistically different between video, PPG, and EMG at each product type (F4,144 = 0.21; P = 0.93 and F4,144 = 1.92; P = 0.11, respectively). The proposed PPG algorithm could achieve up to 0.6 accuracy, 0.67 precision, 0.62 recall, 0.63 F1 scores for apple and bread. These results suggest that PPG with the proposed algorithm could be practically implemented to observe chewing activity objectively.