Opin vísindi

 

Nýlega bætt við

Verk
Estimation of the Knee Joint with Single-Camera Smartphone
(2026-04) Russo, Michela; Ricciardi, Carlo; Romano, Maria; Santoriello, Vittorio; Ponsiglione, Alfonso Maria; Amato, Francesco; Spadea, Maria Francesca; Department of Engineering
(1) Background: Gait analysis provides quantitative information on walking patterns and has proven invaluable for assessing motor function in rehabilitation programmes. A markerless motion capture system combining computer vision techniques provides low-cost, real-time, portable gait analysis. (2) Methods: The kinematics of the knee and ankle of twenty-seven healthy volunteers were assessed using a single smartphone camera combined with the MediaPipe human pose estimation framework. The system was validated using the OPAL wearable sensor system by APDM Wearable Technologies. (3) Results: Findings showed close correspondence between the two systems for knee kinematics showing a mean absolute error of 4.10° ± 2.32° and 3.15° ± 3.10° for right and left knee flexion, respectively, and a mean absolute error of 2.30° ± 2.01° and 3.12° ± 2.63° for right and left knee extension, respectively. The mean absolute error for right and left knee range of motion was found to be 4.55° ± 3.12° and 4.15° ± 3.01°, respectively. Moreover, Bland–Altman plots indicated minimal bias (average 0.6 for flexion, average 0.47 for the extension, and 0.30 for the range of motion) and excellent correlation for knee flexion bilaterally (0.916 and 0.845 for the right and left side, respectively), with slightly lower but still satisfactory agreement for knee extension (0.862 and 0.845 for the right and left side, respectively). Conversely, ankle measurements revealed poor concordance: dorsiflexion and range of motion presented significant differences and systematic errors, while plantarflexion showed no statistical difference but weak correlation. (4) Conclusions: This study demonstrated that combining a smartphone camera with a human pose estimation framework allows for low-cost, real-time, portable gait analysis, particularly of the knee joint.
Verk
Early-Stabilizing Counting
(Association for Computing Machinery, 2026-07-01) Lenzen, Christoph; Loss, Julian; Department of Computer Science
Synchronous Counting is the task of reaching agreement on a common round counter in a synchronous system of n nodes with up to t Byzantine faults in a self-stabilizing manner. That is, after transient faults may have arbitrarily corrupted the system state and ceased, the at least n - t non-faulty nodes need to (re-)establish that (i) their local outputs are identical and (ii) increase by 1 modulo C in each round. An overhead-free reduction from consensus shows that all known lower bounds and impossibilities for consensus carry over to the counting problem. In the other direction, prior work has established that a consensus algorithm A can be turned into a counting algorithm at small overhead relative to the running time and bit complexity of A, without losing resilience.Taking inspiration from early-stopping consensus protocols, in this work we introduce the concept of early stabilization. That is, if there are 0 ≤ f ≤ t (persistent) faults in an execution, the algorithm should stabilize in a number of rounds that depends on f only. Likewise, we seek to achieve an amortized bit complexity that is adaptive in the number of actual faults f. By developing a number of modular building blocks suitable to these goals, we develop a C-counting algorithm that stabilizes within asymptotically optimal O(f + 1) rounds, has message size O(log2 n + log C), and has amortized bit complexity O(n(f log C + log2 n)).
Verk
Disclosing depressive symptoms : perceived sensitivity of PHQ-9 items in a general population sample
(2026-12) Kristófersdóttir, Kristín Hulda; Vésteinsdóttir, Vaka; Kristjánsdóttir, Hafrún; Karlsson, Thorlakur; Thorsdottir, Fanney; Department of Sport Science; Department of Psychology
Background: The Patient Health Questionnaire-9 (PHQ-9) is one of the most widely used tools for screening and assessing depression. However, previous research has yielded inconsistent results regarding its factor structure, with studies suggesting either a one- or two-factor model. One possible explanation is socially desirable responding (SDR), which may arise if some items are perceived as more sensitive than others. This study examines whether such differences in perceived sensitivity exist and how they correspond to patterns reported in prior factor-analytic research. Methods: A total of 273 participants completed 36 paired comparisons of the PHQ-9 items, indicating which symptoms they would find more uncomfortable to disclose. Additionally, absolute judgments were collected, where participants rated each item as either uncomfortable or not uncomfortable to disclose. Data were analyzed using a paired comparisons model rooted in Thurstone’s law of comparative judgment to estimate the relative sensitivity of each item and whether they were more or less likely to be judged as (not) uncomfortable to disclose. Kendall’s coefficients of consistence and agreement were calculated to evaluate the internal consistency of participants’ responses and the level of agreement between them. Results: Results showed that cognitive/affective symptoms, such as feelings of worthlessness and depressed mood were perceived as more sensitive than somatic symptoms like fatigue and sleep disturbances. Notably, the sensitivity estimates obtained in this study align closely with prior factor analytic findings that have supported a two-factor model distinguishing cognitive/affective and somatic symptoms. Conclusions: These findings suggest that social desirability may contribute to the underreporting of certain depression symptoms, potentially helping to explain inconsistencies in the PHQ-9’s factor structure. Researchers and clinicians should consider the impact of SDR when interpreting PHQ-9 scores to enable more accurate assessments of depression symptom severity.
Verk
Crossing the Academia-Practice Divide in Interaction Design
(Association for Computing Machinery, 2026-04-13) Nocera, José Abdelnour; Churchill, Elizabeth F.; Clemmensen, Torkil; Lárusdóttir, Marta Kristín; Macchia, Teresa; Rey, Marta; Russell-Rose, Tony; Smits, Aletta; Oliver, Nuria; Shamma, David A.; Candello, Heloisa; Cesar, Pablo; Lopes, Pedro; Artizzu, Valentino; Draxler, Fiona; Lopez, Gustavo; Reinschluessel, Anke V.; Tong, Xin; Toups Dugas, Phoebe O.; Department of Computer Science
The divide between academic research and professional practice in interaction design continues to challenge how methods, ethics, and innovation are understood and applied. This CHI 2026 meet-up creates a forum where academics, practitioners, and industry leaders can reflect together, share experiences, and explore collaborations. Structured activities will help participants map shared concerns (such as ethics in AI, sustainability, usability in context, and evolving educational practices) while also strengthening cross-sector connections and identifying opportunities for action. The aim is to cultivate a practice-aware, inclusive community that ensures HCI research remains connected, relevant, and impactful. The meet-up capitalizes on the conversations and relationships sparked at ARPPID 2025 (Academic Research and Professional Practice in Interaction Design), a working conference that brought these issues to the fore, extending them into the CHI community and charting directions for future collaboration.
Verk
Consent banners, dark patterns, and GDPR infringements in online gambling : Evidence from a systematic audit and online experiment
(2026-08) McGarrigle, Jack; Torrance, Jamie; Quigley, Martyn; Dymond, Simon; Department of Psychology
Online gambling operators collect vast amounts of consumer data to track behaviour and personalise inducements. Under the General Data Protection Regulation (GDPR), access to these data requires user consent, obtained via pop-up consent banners. However, such banners tend to exhibit “dark patterns” or designs which nudge users towards accepting data sharing. To date, little is known about the extent of such dark patterns in online gambling. Here, we investigated the format of consent banners used on UK gambling websites and assessed how they may influence behaviour. Study 1 reports an audit of all UK-licensed gambling sites ( n = 624). We found that 86% of banners exhibited at least one dark pattern, while GDPR infringements were also identified: 24% of sites offered no option to reject tracking and over two-thirds (67%) processed personally identifiable data prior to obtaining consent. Only 1 in 7 or 14% of sites were GDPR compliant. In Study 2, an online randomised experiment was conducted, whereby participants ( n = 615) were assigned to different consent banners within a simulated gambling platform. The most common banner identified in Study 1 significantly increased acceptance of tracking and produced significantly lower alignment between user choices and preferences. No association between banner decisions and self-reported gambling harm severity was detected. Overall, our findings reveal widespread dark patterns and non-compliance of GDPR requirements on UK online gambling sites, influencing users towards unintended data sharing. These findings highlight the need for stronger regulatory enforcement and stricter consent banner design standards to protect consumers.

Flokkar í Opnum vísindum

Veldu flokk til að skoða.

Niðurstöður 1 - 9 af 9

Öll gögn í Opnum vísindum eru vernduð af ákvæðum höfundalaga og með öllum réttindum áskildum, nema annað sé tekið fram.