Study of the interaction of older adults with touchscreen

Utiliser une tablette ou un smartphone est désormais courant. Cependant, les effets de l'âge sur les capacités motrices nécessaires pour l'exécution des gestes d'interaction tactile n'ont pas été suffisamment pris en compte lors de la conception et de l'évaluation des systèmes interactifs, une des raisons qui a empêché l'inclusion numérique de ce groupe d'utilisateurs. L'objectif de cette thèse est d'étudier l'interaction des personnes âgées avec les écrans tactiles afin d'identifier des problèmes d'utilisabilité sur des supports variés (smartphone et tablette, doigt et stylet). Pour cette étude, nous avons conçu un système interactif constitué de jeux de type puzzle numérique tactiles, où le geste d'interaction drag-and-drop (glisser-déposer) est employé pour positionner les cibles. Dans ce contexte, une attention particulière a été portée à l'analyse des mouvements de l'utilisateur. L'analyse des postures du poignet durant l'interaction a permis d'élucider la relation entre les caractéristiques des mouvements des personnes âgées avec leurs performances, à savoir, des temps plus longs et une augmentation du nombre d'erreurs par rapport aux utilisateurs adultes plus jeunes. Prendre en compte la variabilité des capacités motrices des utilisateurs lors des phases de conception et évaluation des systèmes interactifs est nécessaire pour comprendre leurs difficultés et améliorer l'ergonomie et utilisabilité de l'interaction tactile.Tablets and smartphones have become mainstream technologies. However, the aging effects on the motor skills implied on tactile interaction haven't been enough considered during the design and evaluation of tactile interactive systems, what prevent this group of older adult users to be digitally included successfully. This thesis aims to study the interaction of older adults with touchscreens in order to identify usability issues on different devices and input modalities (smartphone and tablet, finger and stylus). To this study, we designed an interactive system consisted of tactile puzzle games and using drag-and-drop interaction for positioning the puzzle pieces into their corresponding targets. In this framework, a special attention was given to the analysis of the movements of the user. The analysis of the postures of the users' wrists during interaction allowed to elucidate the relationship between the characteristics of the movements of older adults and their performances, particularly concerning the longer times needed for executing the gestures of interaction as well as the increased error rates of this group of users when compared to younger adults. Taking into account the variability of users' motor skills during the design and evaluation of interactive systems is necessary to better understand their difficulties as well as to improve the ergonomics and the usability levels of tactile interaction

Design of a social game for older adults using touchscreen devices and observations from an exploratory study

International audiencePrevious studies about tactile interaction by older adults show some important design considerations that should be applied in order to create more usable and accessible applications. The related results have been applied during the development of a serious game destined to support a social activity with older adults using touchscreen devices. An exploratory study investigates the use of touchscreen mobile devices by 17 older adults and 5 children. The results of an empirical observation allow a description of the participants' appreciation of touchscreen devices, a typology of common errors, the gesture strategies of tactile interaction and design proposals to support interaction

How Many Steps to Represent Individual Gait?

The 12th ACM SIGCHI Symposium on Engineering Interactive Computer Systems, Sophia-Antipolis, France, 23-26 June 2020Assessing and reproducing user's mobility has multiple purposes for interactive systems. In particular, the quantification of gait parameters has been used for user modelling, virtual environments, and augmented reality. While many technologies can be used to assess gait, measuring spatio-temporal parameters and their fluctuations, it is important to evaluate how many steps are necessary to represent the gait pattern of an individual, in order to provide better feedback to the user and improve user experience. In this preliminary study, we evaluate the intra-session reliability of spatio-temporal gait parameters for 24 healthy adults walking two trials of 15m in a corridor. Angular velocity data were acquired from body-worn inertial measurement units attached to participants' right and left shanks. An adaptive algorithm was applied for gait event detection, and gait parameters were analyzed according to pre-defined numbers of steps extracted from the full length of the trial. The main contribution of the present analysis is to present a method of gait event detection, segmentation and analysis that can be used for adjusting interactive systems to individual users.Science Foundation IrelandInsight Research Centr

Short bouts of gait data and inertial sensors can provide reliable measures of spatiotemporal gait parameters from bilateral gait data of participants with multiple sclerosis

Background: Wearable devices equipped with inertial sensors enable objective gait assessment for persons with multiple sclerosis (MS), with potential use in ambulatory care or home and community-based assessments. However, gaitdata collected in non-controlled settings is often fragmented and may not provide enough information forreliable measures. We evaluate a novel approach, extracting pre-defined numbers of gait cycles from the fulllength of a walking task, and their effects on the reliability of spatiotemporal gait parameters. Methods: The present study evaluates intra-session reliability of spatiotemporal gait parameters for short bouts of gaitdata extracted from the full length of the walking tasks to 1) determine the effects of the length of the walkingtask on the reliability of calculated measures and 2) identify spatiotemporal gait parameters that can providereliable measures for gait assessments and reference data in different settings. Thirty-seven participants (37) diagnosed with relapsing-remitting MS (EDSS rage 0 to 4.5) executed two trials,walking 20m each, with inertial sensors attached to their right and left shanks. Previously published algorithms were applied to identify gait events from the medio-lateral angular velocity. Short bouts of gait data wereextracted from each trial, with lengths varying from 3 to 9 gait cycles. Twenty-one measures of spatiotemporalgait parameters were calculated. Intraclass correlation coefficients (ICCs) were calculated to evaluate how the degree of agreement between the two trials of each participant varied with the number of gait cycles included inthe analysis. Results: Spatiotemporal gait parameters calculated as the mean across included gait cycles reach excellent reliabilityfrom three gait cycles. Stride time variability and asymmetry, as well as stride velocity variability and asymmetry, reach good reliability from six gait cycles and should be further explored for persons with MS, whilestride time asymmetry and step time asymmetry do not seem to provide reliable measures and should bereported carefully. Conclusion: Short bouts of gait data, including at least six gait cycles of bilateral data, can provide reliable gait measurements for persons with MS, opening new perspectives for gait assessment using wearable devices in non-controlled environments, to support monitoring of symptoms of persons with neurological diseases.European Commission Horizon 2020Science Foundation Ireland -- replaceInsight Research Centr

Unsupervised assessment of balance and falls risk using a smartphone and machine learning

Assessment of health and physical function using smartphones (mHealth) has enormous potential due to the ubiquity of smartphones and their potential to provide low cost, scalable access to care as well as frequent, objective measurements, outside of clinical environments. Validation of the algorithms and outcome measures used by mHealth apps is of paramount importance, as poorly validated apps have been found to be harmful to patients. Falls are a complex, common and costly problem in the older adult population. Deficits in balance and postural control are strongly associated with falls risk. Assessment of balance and falls risk using a validated smartphone app may lessen the need for clinical assessments which can be expensive, requiring non-portable equipment and specialist expertise. This study reports results for the real-world deployment of a smartphone app for self-directed, unsupervised assessment of balance and falls risk. The app relies on a previously validated algorithm for assessment of balance and falls risk; the outcome measures employed were trained prior to deployment on an independent data set. Results for a sample of 594 smartphone assessments from 147 unique phones show a strong association between self-reported falls history and the falls risk and balance impairment scores produced by the app, suggesting they may be clinically useful outcome measures. In addition, analysis of the quantitative balance features produced seems to suggest that unsupervised, self-directed assessment of balance in the home is feasible

Characterizing Finger Pitch and Roll Orientation During Atomic Touch Actions

International audienceAtomic interactions in touch interfaces, like tap, drag, and flick, are well understood in terms of interaction design, but less is known about their physical performance characteristics. We carried out a study to gather baseline data about finger pitch and roll orientation during atomic touch input actions. Our results show differences in orientation and range for different fingers, hands, and actions, and we analyse the effect of tablet angle. Our data provides designers and researchers with a new resource to better understand what interactions are possible in different settings (e.g. when using the left or right hand), to design novel interaction techniques that use orientation as input (e.g. using finger tilt as an implicit mode), and to determine whether new sensing techniques are feasible (e.g. using fingerprints for identifying specific finger touches)

HCI Challenges in Human Movement Analysis

International audienceAssessing human bodies’ postures and positions enables to design new interaction techniques, to understand users’ performances and to evaluate ergonomics of devices. In addition to the applications for improving Human-Computer Interaction, human movement analysis is at the heart of other types of usages including sports, rehabilitation, gesture recognition, etc. This workshop aims at providing a platform for researchers and designers to discuss the challenges related to the processing (e.g., data collection, treatment, interpretation, recognition) of human movement (e.g., motor skills, amplitude of movements, limitations). We expect to identify the main challenges to be addressed and come up with a research agenda to give HCI new perspectives and suggest promising directions