Abstract
Synchronizing multimodal physiological data streams is a critical and growing challenge in biomedical engineering, particularly when data is collected from multiple devices. This review analyzes the recent state of the art in this field, based on a comprehensive search across five bibliographic databases that yielded 1176 publications. Of these, 60 were selected for in-depth analysis. Our review emphasizes the increasing importance of robust synchronization methodologies in multimodal physiological data analysis. We focused on several key aspects: the types of physiological data streams, the devices used for data collection, methods for measuring alignment latency, the synchronization techniques employed by researchers, and the technological readiness level (TRL) of each technique. Despite the valuable insights from the analyzed studies, a significant gap was identified: 58% of publications that used multiple devices did not assess synchronization latency. This omission is crucial, as latency measurement serves as a key performance indicator for benchmarking different approaches. This finding highlights the critical need for this systematic review and underscores the challenges ahead, as well as the urgent need for further research and development of synchronization techniques in these scenarios. We highlight the need for improvements in synchronization methods and emphasize the importance of accurate latency verification to enhance data acquisition, analysis, and the overall quality of research on multimodal physiology data streams.