Time for an Explanation: A Mini-Review of Explainable Physio-Behavioural Time-Series Classification

Time-series classification is seeing growing importance as device proliferation has lead to the collection of an abundance of sensor data. Although black-box models, whose internal workings are difficult to understand, are a common choice for this task, their use in safety-critical domains has raised calls for greater transparency. In response, researchers have begun employing explainable artificial intelligence together with physio-behavioural signals in the context of real-world problems. Hence, this paper examines the current literature in this area and contributes principles for future research to overcome the limitations of the reviewed works.