home environments
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AbstractMobility is one of the key performance indicators of the health condition of older adults. One important parameter is the gait speed. The mobility is usually assessed under the supervision of a professional by standardised geriatric assessments. Using sensors in smart home environments for continuous monitoring of the gait speed enables physicians to detect early stages of functional decline and to initiate appropriate interventions. This in combination with a floor plan smart home sensors were used to calculate the distance that a person walked in the apartment and the inertial measurement unit data for estimating the actual walking time. A Gaussian kernel density estimator was applied to the computed values and the maximum of the kernel density estimator was considered as the gait speed. The proposed method was evaluated on a real-world dataset and the estimations of the gait speed had a deviation smaller than $$0.10 \, \frac{\mathrm{m}}{\mathrm{s}}$$ 0.10 m s , which is smaller than the minimal clinically important difference, compared to a baseline from a standardised geriatrics assessment.

Social life is full of multiple manifestations that will evidence the structures that sustain it; given the dynamics of a globalized world, it is necessary to direct efforts to culture as one of the essential nuclei in the evolution of societies. Due to the above, the population has generated proposals such as cultural collectives, which try to be the space where such production is generated, protected and motivated. Directed by the methodology of action research, the Cocotón Children's Collective project was born, a space where children from the city of Tehuacán and its region are apprentices, producers and cultural managers, allowing them to interact, express themselves and take on new roles in their development environments. The first stage of the project's implementation was achieved thanks to the interest and active participation of the children's population, using the resources and capital of their home environments.

Abstract To live in a good mood is not only a key consideration for future age-friendly communities, but also a critical necessity for positive ageing. Despite growing evidence of correlations between contact with nature and stress reduction, little is known about the effect of nature integration in indoor environments. Thus, this study aimed to answer the following research questions: (a) How do biophilic characteristics of home environments correlate with older adults’ experience of the multiple levels of the theory of gerotranscendence? and (b) What is the relationship between these experiences and the mood states of these older adults? The study was based on a comparative analysis to scrutinise the impact of the COVID-19 pandemic on these questions. The data were gathered through questionnaires with 450 older adults aged between 65 and 95 years, and stratified by the biophilic characteristics of their living environments: indoor biophilic, outdoor biophilic and non-biophilic. Two sets of data were collected with the same participants, respectively, before the COVID-19 pandemic (June to October 2018) and during the COVID-19 pandemic (June to October 2020). It found that the biophilic characteristics of home environments are correlated dynamically with older adults’ ageing experience and mood states. The study indicates that outdoor biophilic features facilitate the recovery of tension mood effects of the COVID-19 pandemic, whereas indoor biophilic features facilitate recovery from depression and anger.

The wide availability of consumer-oriented virtual reality (VR) equipment has enabled researchers to recruit existing VR owners to participate remotely using their own equipment. Yet, there are many differences between lab environments and home environments, as well as differences between participant samples recruited for lab studies and remote studies. This paper replicates a lab-based experiment on VR locomotion interfaces using a remote sample. Participants completed a triangle-completion task (travel two path legs, then point to the path origin) using their own VR equipment in a remote, unsupervised setting. Locomotion was accomplished using two versions of the teleporting interface varying in availability of rotational self-motion cues. The size of the traveled path and the size of the surrounding virtual environment were also manipulated. Results from remote participants largely mirrored lab results, with overall better performance when rotational self-motion cues were available. Some differences also occurred, including a tendency for remote participants to rely less on nearby landmarks, perhaps due to increased competence with using the teleporting interface to update self-location. This replication study provides insight for VR researchers on aspects of lab studies that may or may not replicate remotely.

Abstract Background The home environment is thought to influence children’s weight trajectories. However, few studies utilise composite measures of the home environment to examine associations with energy balance behaviours and weight. The present study aimed to adapt and update a comprehensive measure of the obesogenic home environment previously developed for pre-schoolers, and explore associations with school-aged children’s energy balance behaviours and weight. Methods Families from the Gemini cohort (n = 149) completed the Home Environment Interview (HEI) via telephone when their children were 12 years old. The HEI comprises four composite scores: one for each domain (food, activity and media) of the environment, as well as a score for the overall obesogenic home environment. The primary caregiver also reported each child’s height and weight (using standard scales and height charts), diet, physical activity and sedentary screen-based behaviours. A test-retest sample (n = 20) of caregivers completed the HEI a second time, 7–14 days after the initial interview, to establish test-retest reliability. Results Children (n = 298) living in ‘higher-risk’ home environments (a 1 unit increase in the HEI obesogenic risk score) were less likely to consume fruits (OR; 95% CI = 0.40; 0.26–0.61, p < 0.001), and vegetables (0.30; 0.18–0.52, p < 0.001), and more likely to consume energy-dense snack foods (1.71; 1.08–2.69, p = 0.022), convenience foods (2.58; 1.64–4.05, p < 0.001), and fast foods (3.09; 1.90–5.04, p < 0.001). Children living in more obesogenic home environments also engaged in more screen-time (β (SE) = 4.55 (0.78), p < 0.001), spent more time playing video games (β (SE) = 1.56 (0.43), p < 0.001), and were less physically active (OR; 95% CI = 0.57; 0.40–0.80, p < 0.01). Additionally, there was a positive association between higher-risk overall home environment composite score and higher BMI-SDS (β (SE) = 0.23 (0.09), p < 0.01). This finding was mirrored for the home media composite (β (SE) = 0.12 (0.03), p < 0.001). The individual home food and activity composite scores were not associated with BMI-SDS. Conclusion Findings reveal associations between the overall obesogenic home environment and dietary intake, activity levels and screen-based sedentary behaviours, as well as BMI in 12 year olds. These findings suggest that the home environment, and in particular the home media environment, may be an important target for obesity prevention strategies.

The purpose of the study on which this paper is based was to explore how self-identified female African university students understand the influence of their home environments on their experiences of online education. The study took place during the COVID-19 pandemic when universities in South Africa and elsewhere introduced online teaching and learning. Using a qualitative approach to a single case study design within a critical feminist paradigm, we carried out an inductive thematic analysis of the data from seven in-depth, open-ended questionnaires and metaphors. We found that home environments play an important role in the education of female African students, particularly in a context characterised by gender inequalities exacerbated by inequities in material resources. However, a sense of agency, displayed by some participants, indicated their determination to rise above the many forms of marginalisation and discrimination they experienced.

Back pain is a common form of disability worldwide, and one condition that causes chronic back pain is axial spondyloarthritis (axSpA) which primarily affects spinal joints resulting in pain and joint stiffness. Markerless human motion analysis uses a computer-vision (CV) aided system to automate human movement from videos. In this protocol, the study will aim to estimate criterion validity and reliability of functional movement measurement using a CV-aided system by comparing it to a standard clinical measurement; secondarily, to assess the feasibility of the CV-aided system in the lab and home environments. An index of tests of functional movement, range of motion and posture will be captured on video and measured using the CV-aided system in the lab and home environments. The index of tests will be compared to measurement performed by an experienced physiotherapist. Bland-Altman plots will be used to determine agreement between the methods, and reliability and completion rates will be used to determine the feasibility of the CV-aided system.

The ability to monitor Sprained Ankle Rehabilitation Exercises (SPAREs) in home environments can help therapists ascertain if exercises have been performed as prescribed. Whilst wearable devices have been shown to provide advantages such as high accuracy and precision during monitoring activities, disadvantages such as limited battery life and users’ inability to remember to charge and wear the devices are often the challenges for their usage. In addition, video cameras, which are notable for high frame rates and granularity, are not privacy-friendly. Therefore, this paper proposes the use and fusion of privacy-friendly and Unobtrusive Sensing Solutions (USSs) for data collection and processing during SPAREs in home environments. The present work aims to monitor SPAREs such as dorsiflexion, plantarflexion, inversion, and eversion using radar and thermal sensors. The main contributions of this paper include (i) privacy-friendly monitoring of SPAREs in a home environment, (ii) fusion of SPAREs data from homogeneous and heterogeneous USSs, and (iii) analysis and comparison of results from single, homogeneous, and heterogeneous USSs. Experimental results indicated the advantages of using heterogeneous USSs and data fusion. Cluster-based analysis of data gleaned from the sensors indicated an average classification accuracy of 96.9% with Neural Network, AdaBoost, and Support Vector Machine, amongst others.