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Record W3202451637 · doi:10.1080/07853890.2021.1897439

Proximity-aware interactive displays for rehabilitation centres

2021· article· en· W3202451637 on OpenAlexaboutno aff
Afonso Faria, Stéphane Duarte, Daniel Simões Lopes, Hugo Nicolau

Bibliographic record

VenueAnnals of Medicine · 2021
Typearticle
Languageen
FieldComputer Science
TopicContext-Aware Activity Recognition Systems
Canadian institutionsnot available
Fundersnot available
KeywordsProxemicsContext (archaeology)Computer scienceHuman–computer interactionRehabilitationUbiquitous computingMultimediaWorld Wide WebMedicine

Abstract

fetched live from OpenAlex

Introduction In clinical practice, physiotherapists often support 3–5 patients, simultaneously. They are frequently roaming throughout the room, switching between patients, taking notes, planning, demonstrating, coordinating, and monitoring multiple exercises. In such demanding environments, it is common for important events to go unnoticed. In light of this, context-aware computing – the ability to recognise people/activities and present timely information – can support rehabilitation practices for both clinicians and patients. Previous research proposed augmenting everyday objects to aid medical professionals [1 Segura D, Favela J, Tentori M. 2009. Sentient displays in support of hospital work. 3rd Symposium of Ubiquitous Computing and Ambient Intelligence; 2008. p. 103–111.[Crossref] , [Google Scholar]] or using large interactive whiteboards that show situational information in operating rooms [2 Bardram JE, Hansen TR, Soegaard M. 2006. AwareMedia: a shared interactive display supporting social, temporal, and spatial. Proceedings of the 2006 ACM Conference on Computer Supported Cooperative Work, CSCW 2006, Banff, Alberta, Canada, November 4–8, 2006. [Google Scholar]]. Nevertheless, the potential of context-aware computing remains largely unexplored in rehabilitation spaces as technologies fail to support the dynamic nature of clinical settings. In this work, we propose ARCADE, a proximity-aware system that leverages motion tracking and interactive displays to support patients’ rehabilitation and provide meaningful and timely information to physiotherapists. The design of the system is grounded on the theory of proxemics [3 Hall ET, Birdwhistell RL, Bock B, et al. Proxemics. Curr Anthropol. 1968;9(2/3):83–108.[Crossref], [Web of Science ®] , [Google Scholar]]; particularly, we leveraged the concept of interpersonal distance (i.e. relative distance between two people) to adjust the information being displayed to both patient and professional. ARCADE is sensitive to 3 interpersonal distances: intimate (<0.5 m), personal (0.5–1.5m), and social (>1.5 m). When therapists are attending other patients (social), the information displayed can be adequately be seen from a distance, showing progress and whether the patient is performing the exercises correctly. When therapists move towards the patient (personal), the display changes smoothly to show critical performance information. Furthermore, therapists can use their hand as a virtual stethoscope to display detailed measures about a specific body segment/joint (intimate). The information being displayed at each interpersonal distance emerged from field studies with physiotherapists from local rehabilitation institutions. The user study aimed to answer two main research questions: (1) is ARCADE effective in illustrating the patients’ performance in unsupervised exercises? and (2) are proxemic interactions useful in rehabilitation environments?Materials and methods We conducted an evaluation with 9 physiotherapists, using both quantitative and qualitative methods to understand the system’s potential to be used in clinical settings. The study had two stages. First, we demonstrated ARCADE to participants and used a think-aloud protocol to elicit feedback about its usefulness in clinical settings. We then conducted a thematic analysis to all qualitative data. In the second stage, we simulated a situation where patients perform an exercise while unsupervised. We compared therapists’ performance in scoring the quality of movement using ARCADE’s visualisations against real-time video performance of patients. ARCADE’s visualisations used a human body representation with 20 joints and included measures such as task completion rate, joint angles, body segment paths, number of compensatory movements, and common compensations. The visualisations illustrated patients’ unsupervised performance based on the video recordings.Results Therapists responded positively to the visual measures displayed by ARCADE, and how information changed based on proximity. Interestingly, they were able to combine multiple measures to assess patients’ performance and uncover hidden information that is not visible by the human eye (e.g. joint angles and compensation movements). Results from stage 2 showed that post-assessment of patients’ performance using ARCADE was similar to physiotherapists’ real-time observations in terms of movement speed, amplitude, precision and overall movement quality.Discussion and conclusions We present ARCADE, a novel proximity-aware system that displays meaningful and timely information to patients and physiotherapists. ARCADE demonstrated potential to be used as a rehabilitation tool and enable professionals to assess the performance of multiple patients, simultaneously, without individual performance loss.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.956
Threshold uncertainty score0.368

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.067
GPT teacher head0.359
Teacher spread0.291 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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