12 documents found, page 1 of 2
Identification of Daily Activites and Environments Based on the AdaBoost Method...
Ferreira, José M.; Pires, Ivan; Marques, Gonçalo; Garcia, Nuno M.; Zdravevski, Eftim; Lameski, Petre; Flórez-Revuelta, Francisco; Spinsante, SusannaUsing the AdaBoost method may increase the accuracy and reliability of a framework for daily activities and environment recognition. Mobile devices have several types of sensors, including motion, magnetic, and location sensors, that allow accurate identification of daily activities and environment. This paper focuses on the review of the studies that use the AdaBoost method with the sensors available in mobile...
Activities of Daily Living and Environment Recognition Using Mobile Devices
Ferreira, José M.; Pires, Ivan; Marques, Gonçalo; Garcia, Nuno M.; Zdravevski, Eftim; Lameski, Petre; Flórez-Revuelta, Francisco; Spinsante, SusannaThe recognition of Activities of Daily Living (ADL) using the sensors available in off-the-shelf mobile devices with high accuracy is significant for the development of their framework. Previously, a framework that comprehends data acquisition, data processing, data cleaning, feature extraction, data fusion, and data classification was proposed. However, the results may be improved with the implementation of ot...
Mobile Applications for the Promotion and Support of Healthy Nutrition and Phys...
Villasana, María Vanessa; Pires, Ivan; Sá, Juliana; Garcia, Nuno M.; Zdravevski, Eftim; Chorbev, Ivan; Lameski, Petre; Flórez-Revuelta, FranciscoBackground: Mobile applications can be used for the monitoring of lifestyles and physical activity. It can be installed in commodity mobile devices, which are currently used by different types of people in their daily activities worlwide . Objective: This paper reviews and categorizes the mobile applications related to diet, nutrition, health, physical activity and education, showing the analysis of 73 mobile a...
Recognition of Activities of Daily Living and Environments Using Acoustic Senso...
Pires, Ivan; Marques, Gonçalo; Garcia, Nuno M.; Pombo, Nuno; Flórez-Revuelta, Francisco; Spinsante, Susanna; Teixeira, Maria CanavarroThe identification of Activities of Daily Living (ADL) is intrinsic with the user’s environment recognition. This detection can be executed through standard sensors present in every-day mobile devices. On the one hand, the main proposal is to recognize users’ environment and standing activities. On the other hand, these features are included in a framework for the ADL and environment identification. Therefore, ...
Identification of activities of daily living through data fusion on motion and ...
Pires, Ivan M.; Pombo, Nuno; Flórez-Revuelta, Francisco; Spinsante, Susanna; Teixeira, M.C.C.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 of the data acquired from motion and magnetic sensors, i.e., accelerometer, gyroscope and magnetometer sensors, for the recognition of Activities of Daily Living (ADL). Based on pattern recognition techniques, the system developed in t...
Android library for recognition of activities of daily living: implementation c...
Pires, Ivan M.; Teixeira, M.C.C.; Pombo, Nuno; Garcia, Nuno M.; Flórez-Revuelta, Francisco; Spinsante, Susanna; Goleva, Rossitza; Zdravevski, EftimOff-the-shelf-mobile devices have several sensors available onboard that may be used for the recognition of Activities of Daily Living (ADL) and the environments where they are performed. This research is focused on the development of Ambient Assisted Living (AAL) systems, using mobile devices for the acquisition of the different types of data related to the physical and physiological conditions of the subjects...
Recognition of activities of daily living and environments using acoustic senso...
Pires, Ivan M.; Marques, Gonçalo Santos; Garcia, Nuno M.; Pombo, Nuno; Flórez-Revuelta, Francisco; Spinsante, Susanna; Teixeira, M.C.C.The identification of Activities of Daily Living (ADL) is intrinsic with the user’s environment recognition. This detection can be executed through standard sensors present in every-day mobile devices. On the one hand, the main proposal is to recognize users’ environment and standing activities. On the other hand, these features are included in a framework for the ADL and environment identification. Therefore, ...
Approach for the Development of a Framework for the Identification of Activitie...
Pires, Ivan; Garcia, Nuno M.; Pombo, Nuno; Flórez-Revuelta, Francisco; Spinsante, SusannaSensors available on mobile devices allow the automatic identification of Activities of Daily Living (ADL). This paper describes an approach for the creation of a framework for the identification of ADL, taking into account several concepts, including data acquisition, data processing, data fusion, and pattern recognition. These concepts can be mapped onto different modules of the framework. The proposed framew...
Android Library for Recognition of Activities of Daily Living: Implementation C...
Pires, Ivan; Teixeira, Maria Cristina Canavarro; Pombo, Nuno; Garcia, Nuno M.; Flórez-Revuelta, Francisco; Spinsante, Susanna; Goleva, RossitzaBackground: Off-the-shelf-mobile devices have several sensors available onboard that may be used for the recognition of Activities of Daily Living (ADL) and the environments where they are performed. This research is focused on the development of Ambient Assisted Living (AAL) systems, using mobile devices for the acquisition of the different types of data related to the physical and physiological conditions of ...
Identification of activities of daily living through data fusion on motion and ...
Pires, Ivan; Garcia, Nuno M.; Pombo, Nuno; Flórez-Revuelta, Francisco; Spinsante, Susanna; Teixeira, Maria Cristina CanavarroSeveral 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 of the data acquired from motion and magnetic sensors, i.e., accelerometer, gyroscope and magnetometer sensors, for the recognition of Activities of Daily Living (ADL). Based on pattern recognition techniques, the system developed in t...