Radar and RGB-depth sensors for fall detection: a review

This paper reviews recent works in the literature on the use of systems based on radar and RGB-Depth (RGB-D) sensors for fall detection, and discusses outstanding research challenges and trends related to this research field. Systems to detect reliably fall events and promptly alert carers and first responders have gained significant interest in the past few years in order to address the societal issue of an increasing number of elderly people living alone, with the associated risk of them falling and the consequences in terms of health treatments, reduced well-being, and costs. The interest in radar and RGB-D sensors is related to their capability to enable contactless and non-intrusive monitoring, which is an advantage for practical deployment and users’ acceptance and compliance, compared with other sensor technologies, such as video-cameras, or wearables. Furthermore, the possibility of combining and fusing information from The heterogeneous types of sensors is expected to improve the overall performance of practical fall detection systems. Researchers from different fields can benefit from multidisciplinary knowledge and awareness of the latest developments in radar and RGB-D sensors that this paper is discussing

Experiences of using a wearable camera to record activity, participation and health-related behaviours: Qualitative reflections of using the Sensecam

Objective: Upcoming technology is changing the way that we are able to collect data looking into activity, social participation and health behaviours. Wearable cameras are one form of technology that allows us to automatically record a collection of passive images, building a visual diary of the user’s day. Whilst acknowledging the usefulness of wearable cameras in research, it is also important to understand individuals’ experiences whilst using them. The aim of this study was to explore the acceptance, experience and usability of a wearable camera (Microsoft_ Sensecam) to record the day-to-day activity and social participation of older people. Methods: A total of 18 older adults, who had worn the wearable camera for seven days, took part in semi-structured interviews. Results: Four themes emerged from the findings: ‘Intrusiveness’; ‘Importance of others’; ‘Remembering the wearable camera’; and ‘Ease of use’. Conclusions: Individuals’ expectations and experiences of using the wearable camera differed considerably. Participants believed that the wearable camera would be intrusive, difficult to use and would evoke public reaction; however, these worries were not borne out in experience. Individuals typically forgot about the presence of the wearable camera during use, remembering it only sporadically. One drawback to its use is that some participants were cautious of using the camera when around others, which impacted the amount of time the camera was worn, and, therefore, the nature of the data recorded. Design issues of the Sensecam were also a problem for the older adults in the study and affected their interaction with the technology

Exploring the technical challenges of large-scale lifelogging

Ambiently and automatically maintaining a lifelog is an activity that may help individuals track their lifestyle, learning, health and productivity. In this paper we motivate and discuss the technical challenges of developing real-world lifelogging solutions, based on seven years of experience. The gathering, organisation, retrieval and presentation challenges of large-scale lifelogging are dis- cussed and we show how this can be achieved and the benefits that may accrue

Emotions in context: examining pervasive affective sensing systems, applications, and analyses

Pervasive sensing has opened up new opportunities for measuring our feelings and understanding our behavior by monitoring our affective states while mobile. This review paper surveys pervasive affect sensing by examining and considering three major elements of affective pervasive systems, namely; “sensing”, “analysis”, and “application”. Sensing investigates the different sensing modalities that are used in existing real-time affective applications, Analysis explores different approaches to emotion recognition and visualization based on different types of collected data, and Application investigates different leading areas of affective applications. For each of the three aspects, the paper includes an extensive survey of the literature and finally outlines some of challenges and future research opportunities of affective sensing in the context of pervasive computing

Advancing video research methodology to capture the processes of social interaction and multimodality

In this reflective methodological paper we focus on affordances and challenges of video data. We compare and analyze two research settings that use the latest video technology to capture classroom interactions in mathematics education, namely, The Social Unit of Learning (SUL) project of the University of Melbourne and the MathTrack project of the University of Helsinki. While using these two settings as examples, we have structured our reflections around themes pertinent to video research in general, namely, research methods, data management, and research ethics. SUL and MathTrack share an understanding of mathematics learning as social multimodal practice, and provide possibilities for zooming into the situational micro interactions that construct collaborative problem-solving learning. Both settings provide rich data for in-depth analyses of peer interactions and learning processes. The settings share special needs for technical support and data management, as well as attention to ethical aspects from the perspective of the participants' security and discretion. SUL data are especially suitable for investigating interactions on a broad scope, addressing how multiple interactional processes intertwine. MathTrack, on the other hand, enables exploration of participants' visual attention in detail and its role in learning. Both settings could provide tools for teachers' professional development by showing them aspects of classroom interactions that would otherwise remain hidden.Peer reviewe

Everyday visual demands of people with low vision:A mixed methods real-life recording study

Research has demonstrated that low vison aids (LVAs) can have a positive impact on the functional sight of those living with sight loss. Step changes in technology are now enabling new wearable LVAs with greater potential than those available previously. For these novel devices to receive increased acceptance and therefore adoption by those with sight loss, visual task demands have to be understood more clearly in order to enable better alignment between device design and user requirements. The aim of this study was to quantify these requirements. Thirty-two participants aged 18 to 87 wore a spectacle-mounted video camera to capture and narrate all everyday situations in which they would use a "perfect" sight aid during 1 week. Captured scenes were analyzed through categorization and computational image analysis. Results showed large variation in activities and lifestyles. Participants reported no available sight aid or coping strategy for 57% of the recorded activities. Reading made up 49% of all recorded tasks, the other half comprising non-textual information. Overall, 75% of captured activities were performed ad hoc (duration of 0-5 minutes), 78% occurred indoors, 58% occurred at home, 48% were lit by natural light, 68% included the object of interest within reach, and 69% required a single focus plane only. Around half of captured objects of interest had a size of 2 degrees visual angle (2.08 logarithm of the minimum angle of resolution [logMAR]) or smaller. This study highlights the need for a sight aid that can make both textual and non-textual scenes accessible while offering flexibility to accommodate individual lifestyles

Affective games:a multimodal classification system

Affective gaming is a relatively new field of research that exploits human emotions to influence gameplay for an enhanced player experience. Changes in player’s psychology reflect on their behaviour and physiology, hence recognition of such variation is a core element in affective games. Complementary sources of affect offer more reliable recognition, especially in contexts where one modality is partial or unavailable. As a multimodal recognition system, affect-aware games are subject to the practical difficulties met by traditional trained classifiers. In addition, inherited game-related challenges in terms of data collection and performance arise while attempting to sustain an acceptable level of immersion. Most existing scenarios employ sensors that offer limited freedom of movement resulting in less realistic experiences. Recent advances now offer technology that allows players to communicate more freely and naturally with the game, and furthermore, control it without the use of input devices. However, the affective game industry is still in its infancy and definitely needs to catch up with the current life-like level of adaptation provided by graphics and animation