Analysis of Public Datasets for Wearable Fall Detection Systems

• Published in: Sensors (Basel, Switzerland) Vol. 17; no. 7; p. 1513
• Main Authors: Casilari, Eduardo, Santoyo-Ramón, José-Antonio, Cano-García, José-Manuel
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 27.06.2017; MDPI
• Subjects: accelerometer; Accidental Falls; Activities of Daily Living; Algorithms; dataset; Datasets; fall detection; Humans; mHealth; Monitoring, Ambulatory; Reproducibility of Results; Sensors; smartphone; wearable; Wearable Electronic Devices; mHealth; wearable; smartphone; dataset; fall detection; accelerometer
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s17071513

Due to the boom of wireless handheld devices such as smartwatches and smartphones, wearable Fall Detection Systems (FDSs) have become a major focus of attention among the research community during the last years. The effectiveness of a wearable FDS must be contrasted against a wide variety of measur...