Simulation-based validation of activity logger data for animal behavior studies

• Main Authors: Jiawei Chen, Geoffrey Brown, Adam Fudickar
• Format: Article
• Language: English
• Published: BMC 2021-09-01
• Series: Animal Biotelemetry
• Subjects: Simulation; Validation; Activity; Detection; Logger; Video
• Online Access: https://doi.org/10.1186/s40317-021-00254-y

Abstract Bio-loggers are widely used for studying the movement and behavior of animals. However, some sensors provide more data than is practical to store given experiment or bio-logger design constraints. One approach for overcoming this limitation is to utilize data collection strategies, such as non-continuous recording or data summarization that may record data more efficiently, but need to be validated for correctness. In this paper we address two fundamental questions—how can researchers determine suitable parameters and behaviors for bio-logger sensors, and how do they validate their choices? We present a methodology that uses software-based simulation of bio-loggers to validate various data collection strategies using recorded data and synchronized, annotated video. The use of simulation allows for fast and repeatable tests, which facilitates the validation of data collection methods as well as the configuration of bio-loggers in preparation for experiments. We demonstrate this methodology using accelerometer loggers for recording the activity of the small songbird Junco hyemalis hyemalis.