VALIDATION OF A THREE-DIMENSIONAL FILM ANALYSIS TECHNIQUE

Biomechanical studies have moved into more flexible film analysis techniques with the onset of computer technology. A number of these techniques have allowed for the analysis of sport movements in three dimensions instead of the more restricted two-dimensional setting (Anderson, 1970; Bergemann. 1974; Martin & Pongratz, 1974; Miller & Petak, 1973; and VanGheluwe, 1974). Methods have been developed that use three-dimensional film analysis but require special metric cameras (Ayoub, Ayoub, & Bamsey, 1970; Bullock, 1974; Bullock & Harley, 1972; Lippert, Hussain, & Veress. 1974). A technique that utilizes nonmetric cameras was developed by Abdel-Aziz and Karara (1971) for still cameras, and later adapted for use with high speed cameras. This method is referred to as direct linear transfornation (DLT). The DLT process allows for data collected from two different cameras to be merged into three-dimensional output (Shapiro, 1980). A computer program written by Marzan and Karara (1975) performs the complicated mathematical equations associated with DLT. Verification of this program was necessary because of program changes made when adapting it from one computer system to another

Understanding factors of successful engagement around energy consumption between and among households.

ABSTRACT An increasing number of researchers are using social engagement techniques such as neighborhood comparison and competition to encourage energy conservation, yet community reception and experience with such systems have not been well studied. We also find that researchers have not thoroughly investigated how different households use these systems and how their uses differ from one another. We explore these questions in a 4-10 month field deployment of a social-energy monitoring application across 15 households, in two distinct locations. We contribute results that describe conditions under which these techniques were effective and ineffective. Our results imply that understanding factors such as a building, or community's layout, context knowledge of community members, accountability and adherence to social norms, trust, and length of residence are key for future design of social-energy applications

The Global Care Ecosystems of 3D Printed Assistive Devices

The popularity of 3D printed assistive technology has led to the emergence of new ecosystems of care, where multiple stakeholders (makers, clinicians, and recipients with disabilities) work toward creating new upper limb prosthetic devices. However, despite the increasing growth, we currently know little about the differences between these care ecosystems. Medical regulations and the prevailing culture have greatly impacted how ecosystems are structured and stakeholders work together, including whether clinicians and makers collaborate. To better understand these care ecosystems, we interviewed a range of stakeholders from multiple countries, including Brazil, Chile, Costa Rica, France, India, Mexico, and the U.S. Our broad analysis allowed us to uncover different working examples of how multiple stakeholders collaborate within these care ecosystems and the main challenges they face. Through our study, we were able to uncover that the ecosystems with multi-stakeholder collaborations exist (something prior work had not seen), and these ecosystems showed increased success and impact. We also identified some of the key follow-up practices to reduce device abandonment. Of particular importance are to have ecosystems put in place follow up practices that integrate formal agreements and compensations for participation (which do not need to be just monetary). We identified that these features helped to ensure multi-stakeholder involvement and ecosystem sustainability. We finished the paper with socio-technical recommendations to create vibrant care ecosystems that include multiple stakeholders in the production of 3D printed assistive devices

A Framework for Designing Fair Ubiquitous Computing Systems

Over the past few decades, ubiquitous sensors and systems have been an integral part of humans' everyday life. They augment human capabilities and provide personalized experiences across diverse contexts such as healthcare, education, and transportation. However, the widespread adoption of ubiquitous computing has also brought forth concerns regarding fairness and equitable treatment. As these systems can make automated decisions that impact individuals, it is essential to ensure that they do not perpetuate biases or discriminate against specific groups. While fairness in ubiquitous computing has been an acknowledged concern since the 1990s, it remains understudied within the field. To bridge this gap, we propose a framework that incorporates fairness considerations into system design, including prioritizing stakeholder perspectives, inclusive data collection, fairness-aware algorithms, appropriate evaluation criteria, enhancing human engagement while addressing privacy concerns, and interactive improvement and regular monitoring. Our framework aims to guide the development of fair and unbiased ubiquitous computing systems, ensuring equal treatment and positive societal impact.Comment: 8 pages, 1 figure, published in 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computin

Evaluating HCI research beyond usability

Evaluating research artefacts is an important step to showcase the validity of a chosen approach. The CHI community has developed and agreed upon a large variety of evaluation methods for HCI research; however, sometimes those methods are not applicable or not sufficient. This is especially the case when the contribution lies within the context of the application area, such as for research in sustainable HCI, HCI for development, or design fiction and futures studies. In this SIG, we invite the CHI community to share their insights from projects that encountered problems in evaluating research and aim to discuss solutions for this difficult topic. We invite researchers from all areas of HCI research who are interested to engage in a debate of issues in the process of validating research artefacts

GymCam

Worn sensors are popular for automatically tracking exercises. However, a wearable is usually attached to one part of the body, tracks only that location, and thus is inadequate for capturing a wide range of exercises, especially when other limbs are involved. Cameras, on the other hand, can fully track a user's body, but suffer from noise and occlusion. We present GymCam, a camera-based system for automatically detecting, recognizing and tracking multiple people and exercises simultaneously in unconstrained environments without any user intervention. We collected data in a varsity gym, correctly segmenting exercises from other activities with an accuracy of 84.6%, recognizing the type of exercise at 93.6% accuracy, and counting the number of repetitions to within ± 1.7 on average. GymCam advances the field of real-time exercise tracking by filling some crucial gaps, such as tracking whole body motion, handling occlusion, and enabling single-point sensing for a multitude of users.</jats:p