Temporal Abstractions for Interpreting Diabetic Patients Monitoring Data

Article type: Research Article

Authors: Bellazzi, R.^{; *} | Larizza, C.^{; 1} | Riva, A.^{; 2}

Affiliations: Dipartimento di Informatica e Sistemistica, Università di Paviavia Ferrata 1, 27100 Pavia, Italy

Correspondence: [*] Corresponding author. E-mail: [email protected].

Note: [1] E-mail: [email protected].

Note: [2] E-mail: [email protected].

Abstract: In this article we present a new approach for the intelligent analysis of longitudinal data coming from chronic patients home monitoring. This approach exploits temporal abstractions to pre-process the raw data and to obtain a new time series of abstract episodes, whose features are then interpreted through statistical and probabilistic techniques. We describe in detail an application of the presented technique to the analysis of diabetic patients' data, showing some results obtained on a real case monitored for six months.

Keywords: Temporal abstractions, Data interpretation, Time series, Patient monitoring, Diabetes

DOI: 10.3233/IDA-1998-2204

Journal: Intelligent Data Analysis, vol. 2, no. 2, pp. 97-122, 1998