activity
20172020
most citedPattern Recognition Techniques for the Identification of Activities of Daily Living using Mobile Device Accelerometer

1 citations · 1 across the 5 of their papers we have counts for

collaborators

7 papers

eess.SP2020

An Efficient Data Imputation Technique for Human Activity Recognition

Ivan Miguel Pires, Faisal Hussain, Nuno M. Garcia +1

The tremendous applications of human activity recognition are surging its span from health monitoring systems to virtual reality applications. Thus, the automatic recognition of da…

cs.NI2020

Identifying Packet Loss and Reordering Packets in Keyed UDP Transmissions

Fábio Machado Gil, Nuno M. Garcia, Bárbara Matos +3

The User Datagram Protocol (UDP) and other similar protocols send the application data from the source machine to the destination machine inside segments, without foreseeing nor al…

eess.IV2020

Reduction of Surgical Risk Through the Evaluation of Medical Imaging Diagnostics

Marco A. V. M. Grinet, Nuno M. Garcia, Ana I. R. Gouveia +2

Computer aided diagnosis (CAD) of Breast Cancer (BRCA) images has been an active area of research in recent years. The main goals of this research is to develop reliable automatic…

cs.LG2019

An Efficient Machine Learning-based Elderly Fall Detection Algorithm

Faisal Hussain, Muhammad Basit Umair, Muhammad Ehatisham-ul-Haq +4

Falling is a commonly occurring mishap with elderly people, which may cause serious injuries. Thus, rapid fall detection is very important in order to mitigate the severe effects o…

cs.CY2017

Data Fusion on Motion and Magnetic Sensors embedded on Mobile Devices for the Identification of Activities of Daily Living

Ivan Miguel Pires, Nuno M. Garcia, Nuno Pombo +2

Several types of sensors have been available in off-the-shelf mobile devices, including motion, magnetic, vision, acoustic, and location sensors. This paper focuses on the fusion o…

cs.SD2017

User Environment Detection with Acoustic Sensors Embedded on Mobile Devices for the Recognition of Activities of Daily Living

Ivan Miguel Pires, Nuno M. Garcia, Nuno Pombo +1

The detection of the environment where user is located, is of extreme use for the identification of Activities of Daily Living (ADL). ADL can be identified by use of the sensors av…