Experience in Evaluating AAL Solutions in Living Labs

Colomer, Juan Bautista Montalvá; Salvi, Dario; Cabrera-Umpiérrez, María Fernanda; Arredondo, María Teresa; Abril, Patricia Sánchez; Jiménez-Mixco, Viveca; García-Betances, Rebeca I.; Fioravanti, Alessio; Pastorino, Matteo; Cancela, Jorge; Medrano, Alejandro

doi:10.3390/s140407277

Cited by 22 publications

(11 citation statements)

References 47 publications

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“…They present both subjective and objective evaluation techniques. Colomer et al [39] present their experience in evaluating AAL solutions in the Smart House Living Lab. They describe the evaluation methodologies used in their projects and propose a set of guidelines to conduct evaluations.…”

Section: The System In Practice—use Case and Experimental Resultsmentioning

confidence: 99%

An Easily Customized Gesture Recognizer for Assisted Living Using Commodity Mobile Devices

Mezari

2018

Journal of Healthcare Engineering

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Automatic gesture recognition is an important field in the area of human-computer interaction. Until recently, the main approach to gesture recognition was based mainly on real time video processing. The objective of this work is to propose the utilization of commodity smartwatches for such purpose. Smartwatches embed accelerometer sensors, and they are endowed with wireless communication capabilities (primarily Bluetooth), so as to connect with mobile phones on which gesture recognition algorithms may be executed. The algorithmic approach proposed in this paper accepts as the input readings from the smartwatch accelerometer sensors and processes them on the mobile phone. As a case study, the gesture recognition application was developed for Android devices and the Pebble smartwatch. This application allows the user to define the set of gestures and to train the system to recognize them. Three alternative methodologies were implemented and evaluated using a set of six 3-D natural gestures. All the reported results are quite satisfactory, while the method based on SAX (Symbolic Aggregate approXimation) was proven the most efficient.

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Section: The System In Practice—use Case and Experimental Resultsmentioning

confidence: 99%

An Easily Customized Gesture Recognizer for Assisted Living Using Commodity Mobile Devices

Mezari

2018

Journal of Healthcare Engineering

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“…Living labs allow a form of experimental governance, whereby stakeholders develop and test new technologies and ways of living to address the challenges associated with the elderly and persons with various cognitive ailments [3]. This involves staging intentional experiments in realworld settings which are then monitored and learnt from [4].…”

Section: Introductionmentioning

confidence: 99%

Connected Health Living Lab

Martín

Cleland

Nugent

et al. 2019

13th International Conference on Ubiquitous Computing and Ambient ‪Intelligence UCAmI 2019‬

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The school of computing, in collaboration with the institute of nursing and health research and the school of engineering, recently established the connected health living lab (CH:LL) at Ulster University. CH:LL offers a dedicated environment to support user and clinical engagement, access to state-of-the-art technology to assess usability and interaction with innovative technologies, in addition to being a dedicated environment to record user behaviours with new connected health solutions. The creation of such a dedicated environment offers a range of benefits to support multi-disciplinary research in the area of connected health. This paper illustrates the design, development, and implementation of CH:LL, including a description of the various technologies associated with the living lab at Ulster University. To conclude, the paper highlights how these resources have been used to date within various research projects.

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“…Their development has opened new perspectives, and has huge business potential in the area of health technologies and gerontechnology [1]. Wireless network and sensor technologies, ranging from smart homes to environment monitoring, make it possible to monitor peo-ple's homes and activities and to detect human performance 24/7 [2,3]. Modern sensors are increasingly small and energy efficient, and thus suitable for longterm use.…”

Section: Introductionmentioning

confidence: 99%

Activity typologies as a design model for the ubiquitous detection of daily routines

Leikas¹,

Launiainen

Kulju

et al. 2018

FinJeHeW

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Emerging technologies open up new visions and business potential for systems design and development in the areas of wellbeing and health. New technologies enable the detection of human performance and early changes in physical and cognitive functioning, making it possible to monitor an older person's wellbeing. This kind of technology or service sets significant requirements for design, as design concepts must be able to capture the complexity of people's daily lives in terms of activities and environments. Technology itself is "blind" unless designers can adapt it to human life. There is thus a distinct need for comprehensive design and development models that generate adequate human requirements for such design. Activity typologies described in this paper are an example of such life-based design relevant knowledge. They allow the detection of signals in daily routines that would predict a decline in the target person's functioning, and feed this data into design processes. They can be used to create a model for human requirements specification for such ubiquitous services that are grounded on the idea of detecting changes in human activity. The model presented in this paper is created in BeWell project and based on the theoretical frameworks of Life-Based Design and International Classification of Functioning, Disability and Health.

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Experience in Evaluating AAL Solutions in Living Labs

Cited by 22 publications

References 47 publications

An Easily Customized Gesture Recognizer for Assisted Living Using Commodity Mobile Devices

An Easily Customized Gesture Recognizer for Assisted Living Using Commodity Mobile Devices

Connected Health Living Lab

Activity typologies as a design model for the ubiquitous detection of daily routines

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