Hardware for Recognition of Human Activities: A Review of Smart Home and AAL Related Technologies.

Activity recognition (AR) from an applied perspective of ambient assisted living (AAL) and smart homes (SH) has become a subject of great interest. Promising a better quality of life, AR applied in contexts such as health, security, and energy consumption can lead to solutions capable of reaching even the people most in need. This study was strongly motivated because levels of development, deployment, and technology of AR solutions transferred to society and industry are based on software development, but also depend on the hardware devices used.

Automatic Annotation for Human Activity Recognition in Free Living Using a Smartphone.

Data annotation is a time-consuming process posing major limitations to the development of Human Activity Recognition (HAR) systems. The availability of a large amount of labeled data is required for supervised Machine Learning (ML) approaches, especially in the case of online and personalized approaches requiring user specific datasets to be labeled. The availability of such datasets has the potential to help address common problems of smartphone-based HAR, such as inter-person variability.

The Praise and Price of Pokémon GO: A Qualitative Study of Children's and Parents' Experiences.

Background: Physical activity has multiple health benefits; however, the majority of children around the world do not attain the recommended levels of daily physical activity. Research has shown that the game Pokémon GO has increased the amount of physical activity of players and that the game has the potential to reach populations that traditionally have low levels of physical activity. Therefore, there is a need to understand which game components can promote initial and sustained physical activity.

Analyzing body movements within the Laban Effort Framework using a single accelerometer.

This article presents a study on analyzing body movements by using a single accelerometer sensor. The investigated categories of body movements belong to the Laban Effort Framework: Strong-Light, Free-Bound and Sudden-Sustained. All body movements were represented by a set of activities used for data collection.

Optimal placement of accelerometers for the detection of everyday activities.

This article describes an investigation to determine the optimal placement of accelerometers for the purpose of detecting a range of everyday activities. The paper investigates the effect of combining data from accelerometers placed at various bodily locations on the accuracy of activity detection. Eight healthy males participated within the study.

Context-aware life-logging for persons with mild dementia.

The demands of introducing technology to support independent living is increasing. This is true also for persons suffering from mild dementia who may have difficulties remembering important information, such as activities, numbers, names, objects, faces, and so on. This paper presents a context-aware life-logging system, called MemoryLane, which can support independent living and improve quality of life for persons with mild dementia.

The development of personalised cognitive prosthetics.

Persons suffering from mild dementia can benefit from a form of cognitive prosthetic which can be used to assist them with their day to day activities. Within our current work we are aiming to develop a successful user-validated cognitive prosthetic for persons with mild dementia. We have devised a three phased waterfall methodology to support our developments.

HomeCI--a visual editor for healthcare professionals in the design of home based care.

The demands of introducing a more practical means of managing and monitoring technology within the home environment to support independent living are increasing. Within this paper we present a prototype solution, referred to as HomeCI, which allows healthcare professionals to establish the conditions/rules within which technology in the home should operate. The HomeCI concept is based on the use of visual notation and has been designed for use by healthcare professionals with a non technical background.