Visual Data Exploration for Balance Quantification in Real-Time During Exergaming

Unintentional injuries are among the ten leading causes of death in older adults; falls cause 60% of these deaths. Despite their effectiveness to improve balance and reduce the risk of falls, balance training programs have several drawbacks in practice, such as lack of engaging elements, boring exercises, and the effort and cost of travelling, ultimately resulting in low adherence. Exergames, that is, digital games controlled by body movements, have been proposed as an alternative to improve balance. One of the main challenges for exergames is to automatically quantify balance during game-play in order to adapt the game difficulty according to the skills of the player. Here we perform a multidimensional exploratory data analysis, using visualization techniques, to find useful measures for quantifying balance in real-time. First, we visualize exergaming data, derived from 400 force plate recordings of 40 participants from 20 to 79 years and 10 trials per participant, as heat maps and violin plots to get quick insight into the nature of the data. Second, we extract known and new features from the data, such as instantaneous speed, measures of dispersion, turbulence measures derived from speed, and curvature values. Finally, we analyze and visualize these features using several visualizations such as a heat map, overlapping violin plots, a parallel coordinate plot, a projection of the two first principal components, and a scatter plot matrix. Our visualizations and findings suggest that heat maps and violin plots can provide quick insight and directions for further data exploration. The most promising measures to quantify balance in real-time are speed, curvature and a turbulence measure, because these measures show age-related changes in balance performance. The next step is to apply the present techniques to data of whole body movements as recorded by devices such as Kinect

Assessing Dynamic Balance Performance during Exergaming based on Speed and Curvature of Body Movements

Improving balance performance among the elderly is of utmost importance because of the increasing number of injuries and fatalities caused by fall incidences. Digital games controlled by body movements (exergames) have been proposed as a way to improve balance among older people. However, the assessment of balance performance in real-time during exergaming remains a challenging task. This assessment could be used to provide instantaneous feedback and automatically adjust the exergame difficulty. Such features could potentially increase the motivation of the player, thus augmenting the effectiveness of exergames. As clear differences in balance performance have been identified between older and younger people, distinguishing between older and younger adults can help identifying measures of balance performance. We used generalized linear models to investigate whether the assessment of balance performance based on movement speed can be improved by incorporating curvature of the movement trajectory into the analysis. Indeed, our results indicated that curvature improves the performance of the models. Five-fold cross validation indicated that our method is promising for the assessment of balance performance in real-time by showing more than 90% classification accuracy. Finally, this method could be valuable not only for exergaming but also for real-time assessment of body movements in sports, rehabilitation and medicine

Efficacy of a Mobile Application for Improving Gait Performance in Community-Dwelling Older Adults

The United States is a rapidly aging nation. Older adults have higher rates of falls than any other age group. One in four older adults fall each year. Many of these falls are associated with sedentary lifestyles and decreased muscular strength effecting balance and gait performance. Physical activity (exercise) can reduce the risk of falls among older adults, yet adherence remains low. Exergames can increase adherence to interventions that promote health and physical activity. Social engagement can increase self-efficacy and motivation to exercise. By design, the Bingocize® health promotion mobile application (app) increases social engagement, while providing a multi-factorial fall prevention intervention. The purpose of this investigation was to evaluate the efficacy of the app to improve gait in community-dwelling older adults (N=38; mean age 72.42 years +12.58). Participants were clustered and randomly assigned to (a) experimental (n=20; using app with bingo game, health education and exercise) or (b) control (n=18; using app with bingo game, health education without exercise) condition. Each group completed a tenweek intervention that consisted of two- 45-60 minute sessions per week. Pre and post gait analysis, at self-selected (SS) and fast-walking speeds, measured using the GAITRite® Electronic Walkway (GWS). Gait analysis included parameters of velocity, cadence, step time, step length and width, and single and double support time. A mixedmodel ANOVA (p \u3c .05) was used for statistical analysis. There were no main effects observed. Significant interactions (group x time) were observed at fast speed and SS speed compared to the control group. Significant interactions were observed at fast speed included velocity (λ = .886, F (1, 36) = 4.61, p = .039, = .114); and step length (λ = .864, F (1, 36) = 5.64, p = .023, = .136); and were observed at SS speed for single support time (λ = .887, F (1, 36) = 4.59, p = .039, = .113). Post hoc analyses using paired and independent samples t-tests were conducted on gait variables with observed significant interactions. The independent samples t-test for Single Support Time (SS) post was significant (t (36) = 2.454, p = .019, two-tailed). None of the remaining post hoc analyses were significant. There was a meaningful detectable change (MDC) in mean velocity (\u3e5 cm/s) over time, for both SS and fast walking speeds, within the experimental condition. MDC in gait speed ranges from 5 cm/s (small) to 10 cm/s (large). As for clinical significance, this should be considered a small, yet meaningful detectable change. It is the conclusion of the investigators, that the app, with the exercise intervention, can effectively produce a meaningful change in gait speed (5 cm/s), which has the potential for reducing the risk of falls in older adults. This investigation was funded by The Retirement Research Foundation

Assessing dynamic postural control during exergaming in older adults:A probabilistic approach

Digital games controlled by body movements (exergames) have been proposed as a way to improve postural control among older adults. Exergames are meant to be played at home in an unsupervised way. However, only few studies have investigated the effect of unsupervised home-exergaming on postural control. Moreover, suitable methods to dynamically assess postural control during exergaming are still scarce. Dynamic postural control (DPC) assessment could be used to provide both meaningful feedback and automatic adjustment of exergame difficulty. These features could potentially foster unsupervised exergaming at home and improve the effectiveness of exergames as tools to improve balance control. The main aim of this study is to investigate the effect of six weeks of unsupervised home-exergaming on DPC as assessed by a recently developed probabilistic model. High probability values suggest 'deteriorated' postural control, whereas low probability values suggest 'good' postural control. In a pilot study, ten healthy older adults (average 77.9, SD 7.2 years) played an iceskating exergame at home half an hour per day, three times a week during six weeks. The intervention effect on DPC was assessed using exergaming trials recorded by Kinect at baseline and every other week. Visualization of the results suggests that the probabilistic model is suitable for real-time DPC assessment. Moreover, linear mixed model analysis and parametric bootstrapping suggest a significant intervention effect on DPC. In conclusion, these results suggest that unsupervised exergaming for improving DPC among older adults is indeed feasible and that probabilistic models could be a new approach to assess DPC

The efficacy of exergaming in people with major neurocognitive disorder residing in long-term care facilities: a pilot randomized controlled trial

Background: It is currently unknown whether exergaming is efficacious in people with major neurocognitive disorder (MNCD) residing in long-term care facilities. This pilot randomized controlled trial (RCT) explored the efficacy of a stepping exergame program on gait speed, balance, mobility, reaction time, cognitive and neuropsychiatric outcomes, quality of life, and daily life functioning in people with MNCD residing in long-term care facilities. Methods: Participants were randomly assigned to 8 weeks, three times weekly, 15 min of exergaming versus watching preferred music videos. The exergame device consisted of a pressure-sensitive step training platform on which participants performed stepping movements to play the games. The device automatically adapted the training level to the participants’ capabilities. The Short Physical Performance Battery (SPPB), step reaction time test (SRTT), Montréal Cognitive Assessment (MoCA), Neuropsychiatric Inventory (NPI), Cornell Scale for Depression in Dementia (CSDD), Dementia Quality of Life (DQoL), and Katz Activities of Daily Living (Katz ADL) were assessed at baseline and post-intervention. A Quade’s non-parametric ANCOVA controlling for baseline values with post hoc Bonferroni correction (p < 0.00625) was used to analyze pre- and post-differences between the groups. Partial eta-squared (η2p) effect sizes were calculated. Results: Forty-five of 55 randomized inpatients with mild to moderate MNCD (Mini-Mental State Examination score = 17.2 ± 4.5; aged 70–91; 35 women) completed the study. The exergame group (n = 23) demonstrated improvements in gait speed (p < 0.001, η2p = 0.41), total SPPB (p < 0.001, η2p = 0.64), SRTT (p<0.001, η2p = 0.51), MoCA (p<0.001, η2p = 0.38), and reductions in CSDD (p<0.001, η2p = 0.43) compared to the control group (n = 22). There were no differences in NPI (p = 0.165, η2p = 0.05), DQoL (p = 0.012, η2p = 0.16), and ADL (p = 0.008, η2p = 0.16) post-intervention scores between the experimental and control group, albeit DQol and ADL measures showed large effect sizes in the exergame group. The mean attendance rate was 82.9% in the exergame group and 73.7% in the music control group. There were no study-related adverse events reported by the participants, nor observed by the research team. Conclusions: The findings of this pilot RCT suggest that an individually adapted exergame training improves lower extremity functioning, cognitive functioning and step reaction time and symptoms of depression in inpatients with MNCD residing in long-term care facilities

MASELTOV Deliverable D7.1.1: Incidental Learning Framework

This is the first steps towards creating an ‘Incidental learning framework’, and it is a work in progress. It is intended that the Incidental learning framework will facilitate the creation of technology rich learning opportunities for immigrants within cities. The framework will be a descriptive mechanism that permits analysis, a generative tool to support software system design, and it will facilitate the communication of learning design ideas both visually and textually. The framework focuses on incidental learning i.e. learning that is spontaneous and unplanned, in the knowledge domains of interest to the MASELTOV project including health care, culture, and language and information access. However, it provides links and triggers to structured and reflective learning to back up and deepen learning that happens incidentally. This document describes the initial version of the Incidental Learning Framework, presents a few examples of its use, and describes some conclusions and recommendations for work towards the next version of the framework including • Using the framework to develop it, • Extending the literature review, • Gathering evidence about immigrants day-to-day lives, • Running design workshop(s) using the framework