Revista: Sensors

Título: Extracting Daily Routines from Raw RSSI Data

Autores: Raúl Montoliu, Emilio Sansano-Sansano, Marina Martínez-García, Sergio Lluva-Plaza, Ana Jiménez-Martín, José M. Villadangos-Carrizo, Juan Jesús García-Domínguez 

Número: Volume: 25 

Resumen: Detecting behavioral routines is an important research area with many implications in various practical applications. One such application involves studying the behavior of older adults residing in care homes. This paper proposes a comprehensive methodology for extracting and analyzing the daily routines of older adults in care homes. The methodology utilizes raw data comprising signal strength measurements obtained from smartwatches worn by six volunteers over five months. To establish the basis for estimating daily activities, fingerprint-based localization techniques are employed to track the minute-by-minute location of each volunteer. Subsequently, the activity performed by each volunteer is estimated for each day. Finally, the study estimates the probability of a user undertaking each one of the studied activities on a given weekday.

Enlace del artículo: https://doi.org/10.3390/s25092745 

Universidad de Alcalá DEPECA


El Proyecto de investigación FraialAlert (SBPLY/21/180501/000216) está financiado por la Unión Europea a través del FEDER y por la JCCM a través de INNOCAM

Cofinanciado UE Ministerio Hacienda Fondos Europeos Castilla-La Mancha INNOCAM