Activities of Daily Living Monitoring via a WearableCamera: Toward Real-World Applications

Activity recognition from wearable photo-cameras is crucial for lifestyle characterization and health monitoring. However, to enable its wide-spreading use in real-world applications, a high level of generalization needs to be ensured on unseen users. Currently, state-of-the-art methods have been tested only on relatively small datasets consisting of data collected by a few users that are partially seen during training. In this paper, we built a new egocentric dataset acquired by 15 people through a wearable photo-camera and used it to test the generalization capabilities of several state-of-the-art methods for egocentric activity recognition on unseen users and daily image sequences. In addition, we propose several variants to state-of-the-art deep learning architectures, and we show that it is possible to achieve 79.87% accuracy on users unseen during training. Furthermore, to show that the proposed dataset and approach can be useful in real-world applications, where data can be acquired by different wearable cameras and labeled data are scarcely available, we employed a domain adaptation strategy on two egocentric activity recognition benchmark datasets. These experiments show that the model learned with our dataset, can easily be transferred to other domains with a very small amount of labeled data. Taken together, those results show that activity recognition from wearable photo-cameras is mature enough to be tested in real-world applications

The relationship between the home environment and children’s physical activity and sedentary behaviour at home

Increasing children’s physical activity (PA) and reducing their sedentary behaviour are considered important preventative measures for obesity and several other health risk factors in children. Given children spend significant time at home, an improved understanding of these behaviours in the home environment would provide invaluable insight for interventions. Therefore, the overarching aim of this thesis was to provide new insight into how the home environment is related to children’s home-based PA and sedentary behaviour. Study 1 investigated the relationship between sufficient moderate-to-vigorous physical activity (MVPA) (≥60 min·day–1) and excessive screen-time (≥2 h·day–1) with lifestyle factors in children, and found they were associated with healthy and unhealthy factors, respectively. This study highlighted the importance of meeting PA and screen-time recommendations in relation to important health-related lifestyle factors, which is of concern, as few children were shown to meet such recommendations. Identifying the correlates of children’s behaviours is an important stage in intervention development, therefore studies 2-5 focussed on improving understanding of children’s PA and sedentary behaviour at home. Study 2 demonstrated the validity and reliability of HomeSPACE-II, a novel instrument for measuring physical factors that influence children’s home-based PA and sedentary behaviour. Using HomeSPACE-II, study 3 showed that the physical home environment is related to children’s home-based PA and sedentary behaviour. Given the established influence of social and individual factors on children’s behaviour and their confounding effects in study 3, study 4 investigated the influence of social and individual factors on: (i) children’s home-based PA and sedentary behaviour, and; (ii) the home physical environment. Study 4 revealed that parental and child activity preferences and priorities, as well as parental rules were associated with children’s home-based PA and sedentary behaviour and the physical home environment. Study 5 found clusters of social and physical factors at home, which were associated with children’s home-based PA and sedentary behaviour as well as background characteristics in the expected directions