Activity In Home Environment Research Articles

Pedagogical design of “inverted” learning resources for home study

Introduction. Self-education is becoming increasingly important in terms of the concept of lifelong learning. The changes in the ways of perceiving information, along with the new tendencies in the formation of “engaging” Internet content, cause a necessity to find new methods of presenting educational material aimed at efficient learning and meeting differing requirements of end users. The new demands of today’s young people on the self-education process actualise the need to describe the pedagogical design of “inverted” resource-transformers oriented towards productive self-learning in home environment. The purpose of the research is to substantiate the elements of pedagogical design of “inverted” learning resources based on subject-area topology of the question-task knowledge tree, that ensure due account of the learners’ cognitive preferences and heighten satisfaction and motivation towards independent learning activity. Research methodology. Pedagogical design of digital learning resources is considered from the perspective of mental approach. The core idea of the work is the development of mental question-task knowledge trees that allow for creation of discrete digital learning elements of referential and repetitive nature, which have a pedagogical design taking into account the learner’s “clip style of thinking” and secure personalisation, visualised self-management and self-control of learning activities in home environment. Research findings. “Inverted” transformed educational resources represent an innovative means of learning in digital space. The creation of such resources, with regard for the principles of pedagogical design, ensures the formation of engaging content and account of learners’ cognitive features, considering that the latter are representatives of the digital generation. The questioning involving the students of Krasnoyarsk State Pedagogical University named after V.P. Astafyev showed that 98% of the respondents (out of 127 participants) believed that this format of presenting educational content would prove to be in demand and be interesting for students. A total of 100% of the involved Krasnoyarsk teachers as well as the pedagogues of Krasnoyarsk State Pedagogical University named after V.P. Astafyev (102 respondents), after taking part in the expert evaluation of “inverted” teaching resources, note that the presented resources meet the modern requirements for structuring and visualising the educational material as well as the principles of micro-learning. They also note high quality of realisation of the students’ practical activities (97%), due controlling elements of the learning process (98%), ease of navigation (98%), the possibility of designing an individual learning route (99%), high prospects of enhancing the efficiency of schoolchildren’s self-education (99%). Conclusion. The considered requirements for the pedagogical content design of “inverted” resources enable their developers to purposefully improve the parameters facilitating readability, perception and understanding of the content of e-format educational texts. Currently, the software developers (at the authors’ request) are developing an instrumental environment in the form of cloud application, which will make it possible to create inverted electronic resources on the basis of a topological question-task knowledge tree.

Towards the development of an intuitive teleoperation system for human support robot using a VR device

This paper presents our development of an intuitive teleoperation system for Toyota's Human Support Robot. While this robot has been widely used as an autonomous agent in the field of service robotics, we explore a possibility of this robot for the use of remote assistance of daily activities in home environments. For rapid prototyping an affordable teleoperation system, we adopt a commercially available VR device as a user interface and develop a Robot Operating System (ROS)-based control framework building on the software application programming interfaces (APIs). In particular, we implement a singularity robust inverse kinematics algorithm to achieve a coordinated whole-body motion of the robot for safe and intuitive operation. We empirically evaluate the practical feasibility of the proposed teleoperation system through various test tasks. We discuss the potential and limitations of the current development for its future improvement.

Data Mining and Fusion of Unobtrusive Sensing Solutions for Indoor Activity Recognition.

This paper proposes the fusion of data from unobtrusive sensing solutions for the recognition and classification of activities in home environments. The ability to recognize and classify activities can help in the objective monitoring of health and wellness trends in ageing adults. While the use of video and stereo cameras for monitoring activities provides an adequate insight, the privacy of users is not fully protected (i.e., users can easily be recognized from the images). Another concern is that widely used wearable sensors, such as accelerometers, have some disadvantages, such as limited battery life, adoption issues and wearability. This study investigates the use of low-cost thermal sensing solutions capable of generating distinct thermal blobs with timestamps to recognize the activities of study participants. More than 11,000 thermal blobs were recorded from 10 healthy participants with two thermal sensors placed in a laboratory kitchen: (i) one mounted on the ceiling, and (ii) the other positioned on a mini tripod stand in the corner of the room. Furthermore, data from the ceiling thermal sensor were fused with data gleaned from the lateral thermal sensor. Contact sensors were used at each stage as the gold standard for timestamp approximation during data acquisition, which allowed the attainment of: (i) the time at which each activity took place, (ii) the type of activity performed, and (iii) the location of each participant. Experimental results demonstrated successful cluster-based activity recognition and classification with an average regression co-efficient of 0.95 for tested clusters and features. Also, an average accuracy of 95% was obtained for data mining models such as k-nearest neighbor, logistic regression, neural network and random forest on Evaluation Test.Clinical Relevance-This study presents an unobtrusive (i.e., privacy-friendly) solution for activity recognition and classification, for the purposes of profiling trends in health and wellbeing.

Collaborative Fall Detection Using Smart Phone and Kinect

Humanfall detection has attracted broad attentions as sensors and mobile devices are increasingly adopted in real-life scenarios such as smart homes. The complexity of activities in home environments pose severe challenges to the fall detection research with respect to the detection accuracy. We propose a collaborative detection platform that combines two subsystems: a threshold-based fall detection subsystem using mobile phones and a support vector machine (SVM)-based fall detection subsystem using Kinects. Both subsystems have their respective confidence models and the platform detects falls by fusing the data of both subsystems using two methods: the logical rules-based and D-S evidence fusion theory-based methods. We have validated the two confidence models based on mobile phone and Kinect, which achieve the accuracy of 84.17% and 97.08%, respectively. Our collaborative fall detection approach achieves the best accuracy of 100%.

Functional change in the pattern of swallowing through the performance of orofacial exercises.

The objective was to determine if there was functional improvement of swallowing pattern in subjects identified with risk of oropharyngeal dysphagia after four weeks of specific oropharyngeal exercises. These exercises have pre-determined intensity and duration. It is a longitudinal study of functional effect, determined by initial and final comparative measures. Participants were adults and elderly, selected in a period of 24 months. A total of 68 participants were included. All subjects had a clinical evaluation of swallowing, and an initial measure in a functional scale. The individuals were split into two groups, according to the initial levelling of ASHA NOMS scale. In Group 1 (G1) - ASHA NOMS, initial of levels 1 and 2; Group 2 (G2) - ASHA NOMS, initial of levels 3, 4 and 5. All subjects executed an exercise protocol performed for four weeks. The protocol includes sessions with a speech therapist, and continuity of activities in home environment. Finally, new measurement of swallowing performance was held. For G2 group there was statistically significant improvement. For G1, the relation was insignificant, despite the intense change in ASHA NOMS scale, however, in this group there was a reduced number of individuals due to the profile severity. The program was effective because after four exercise sessions, there was significant improvement in swallowing pattern, demonstrated by functional scale.

Situating the “music of” households and firemen in semi-open spaces: contribution to the analysis of collective activity’s spatio-temporal dynamics

Examining different team dynamics and understanding collective activities in home environments are two important challenges for ergonomics and its related fields. This article focuses on collective activities within home/building conceived as semi-open spaces (opening up opportunities whilst at the same time imposing more or less radical limits to collective activity) and discusses how orchestral formats (radically separating conceptual/physical and temporal axes) provide alternative perspectives for qualitative research. To do so, we leverage on the creation and use of MUltI-SCOre Format (for MUSICOF) in two previous in-depth studies of households and firemen. Drawing on a reflective analysis of our research practices, we describe how MUSICOF provides benefits when the researcher/practitioner has to cover a large conceptual/physical space, synchronise each basic unit of the collective activity, analyse activity at different levels (cognitive, social and spatio-temporal), characterise spatio-temporal arrangements and zoom in/out different degrees of abstraction of the analysis. It allows one to articulate multiple data and categories on a unique temporal axis, to formalise any type of arrangement of collective activity within space and time, to access all the required data on a single document where all the basic units are synchronised and to create either detailed empirical or synthetic formative models. After the demonstration of these benefits and some challenges, we discuss the perspectives and limits of this paper in order to equip studies of collective activity's dynamics more consequentially regarding semi-open spaces, situated/distributed cognition, cognitive work analysis and scenario-based design.

Logical Activity Recognition Model for Smart Home Environment

Recently, studies that interact with human and things through motion recognition are increasing due to the expansion of IoT(Internet of Things). This paper proposed the system that recognizes the user’s logical activity in home environment by attaching some sensors to various objects. We employ Arduino sensors and appreciate the logical activity by using the physical activitymodel that we processed in the previous researches. In this System, we can cognize the activities such as watching TV, listening music, talking, eating, cooking, sleeping and using computer. After we produce experimental data through setting virtual scenario, then the average result of recognition rate was 95% but depending on experiment sensor situation and physical activity errors the consequence could be changed. To provide the recognized results to user, we visualized diverse graphs.

Interpreting Fear of Falling in the Elderly: What Do We Need to Consider?

Fear of falling (FF) is a serious problem in elderly. Available scales quantify FF by generating an aggregate total FF score disregarding the environment in which fear is expressed. This study examined the differences in psychosocial and physical characteristics and global functional capabilities between the elderly who experienced FF exclusively for activities usually performed in community environments and those who reported FF only for home-based activities. Older participants (age > or = 65, n = 1155) enrolled in the InCHIANTI study completed the evaluation of FF, personal mastery, depression, cognition, social support, lower limb strength, grip strength, balance, timed repeated sit-to-stand performance, visual acuity, and contrast sensitivity. Functional capacity measures included walking speed, ADL and IADL disability, self-reported difficulty climbing steps without support and difficulty walking at least 400m. Only those who reported FF exclusively for activities usually performed in the community environment (n = 232) or in home environment (n = 110) were included in the analysis. Multivariate analysis of variance revealed that those who reported FF exclusively for home-based activities were significantly worse in psychosocial and physical characteristics measured (F(1,339) = 4.27; p < 0.01) and were also less able in all global functional capacity measures (p = 0.04 to < 0.01). There are significant characteristic and functional differences between the older persons who have FF performing community environment activities and those who express FF in home environment activities. The results strongly indicate the need to classify FF according to the environment or alternatively, to derive an aggregate score by appropriately weighting according to the environment, for valid interpretation of FF.