Browse by author
Lookup NU author(s): Dr Giacomo BergamiORCiD, Emma Packer, Dr Kirsty ScottORCiD, Dr Silvia Del DinORCiD
This is the authors' accepted manuscript of a conference proceedings (inc. abstract) that has been published in its final definitive form by Springer Verlag, 2024.
For re-use rights please refer to the publisher's terms and conditions.
While monitoring Parkinsonian patients with wearable sensors and tracking their drug assumption patterns, we want to differentiate the behaviours distinguishing periods of relative well-being from dyskinetic events. This requires solving a novel problem, where an entire multivariate time series (MTS) has its class label varying in time, thus leading to a generalised formulation of multivariate time series classification (MTSC). To achieve explainability, we premier the composition of data trend (DT) analysis with DECLAREd, a log temporal declarative language, to derive human-readable correlations across different MTS dimensions' trends. This is mediated by a novel temporal data representation, polyadic logs, supporting both MTS raw data and concurrent activity-labelled durative activities (constituents) for representing event-based classes and concurrent DTs across MTS dimensions. Our validation over a real patient dataset shows that our MTCS algorithm, EMeriTAte, outperforms state-of-the-art MTSC for a novel patient classification task.
Author(s): Bergami G, Packer E, Scott K, Del Din S
Editor(s): Chbeir, R; Ilarri, S; Manolopoulos, Y; Revesz, PZ; Bernardino, J; Leung, CK;
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: The 28th International Database Engineered Applications Symposium
Year of Conference: 2024
Pages: 1-14
Online publication date: 28/08/2024
Acceptance date: 30/07/2024
Date deposited: 04/10/2024
Publisher: Springer Verlag
URL: https://conferences.sigappfr.org/ideas2024/program/#session_2
ePrints DOI: 10.57711/6y6g-cw67
Data Access Statement: This is not Golden OpenAccess. This was the version after the reviewers had applied the comments.
