March 2018
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25 Reads
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March 2018
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25 Reads
September 2017
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17 Reads
Building a deployable PhysiComp that merges form and function typically involves a significant investment of time and skill in digital electronics, 3D modeling and mechanical design. We aim to help designers quickly create prototypes by removing technical barriers in that process. Other methods for constructing PhysiComp prototypes either lack fidelity in representing shape and function or are confined to use in the studio next to a workstation, camera or projector system. Software 3D CAD tools can be used to design the shape but do not provide immediate tactile feedback on fit and feel. In this work, sculpting around 3D printed replicas of electronics combines electronics and form in a fluid design environment. The sculptures are scanned, modified for assembly and then printed on a 3D printer. Using this process, functional prototypes can be created with about 4 hours of focused effort over a day and a half with most of that time spent waiting for the 3D printer. The process lends itself to concurrent exploration of several designs and to rapid iteration. This allows the design process to converge quickly to a PhysiComp that is comfortable and useful.
September 2017
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27 Reads
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13 Citations
Mobile and wearable computing has great potential to support alpine outdoor sport activities. This includes, but is not limited to, rock climbing, hiking, mountain biking, paragliding, and skiing. Interestingly, technology for tracking, monitoring and supporting sport activities is broadly used in sports like running or cycling, but has not reached the top of the mountains yet. Nevertheless, such technologies could support people in many mountain scenarios such as activity tracking, navigation, or emergency support. Technologies and applications for mountaineers can learn from ubiquitous computing research in many ways to provide more joyful, motivating and safer outdoor experiences. This workshop is building on the ideas and findings of the successful UbiMount '16 workshop and aims to further explore the newly established research direction of ubiquitous computing in the mountains. During this one day workshop the participants will present their positions and research, followed by a demo session and group exercises.
September 2017
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40 Reads
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2 Citations
The 2016 Ubicomp Ubiquitous Computing in the Mountains (UbiMount) Workshop was held in Heidelberg, Germany on September 12 and 13. An excursion on the second day of the workshop included hiking on trails and rock climbing on the Riesenstein in the Konigstuhl hill of the Odenwald Mountains adjacent to Heidelberg. We recorded accelerometer data and video of hiking and climbing during the excursion. We collected the data and video in order to better understand how to generate labeled events in accelerometer data for us in machine learning of event recognizers for activities done in the mountains. In this paper, we make that data available to the UbiMount community, explain how it was collected and discuss the data collection experience in the mountains.
May 2017
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14 Reads
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5 Citations
Interactive computing has impacted how people experience outdoor recreation. Nevertheless, the role of interactive computing in outdoor recreation can be complicated. Some people engage in outdoor recreation precisely to avoid distractions associated with pervasive interactive computing. Others use interactive computing to create, enhance or share outdoor recreation experiences. In this SIG, participants will discuss research questions and foundational theories that might guide future work related to interactive computing in outdoor recreation. The discussion will range from engineering issues to research methods. Attendees will have opportunities to stay connected after the SIG.
September 2016
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149 Reads
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16 Citations
We experiment with using sensors and a machine learning algorithm to detect and label turns in alpine skiing. Previous work in this area involves data from more sensors and turns are detected using either a physics-based model or custom signal processing algorithm. We recorded accelerometer and gyroscope data using a single sensor placed on a skier's knee. Left and right turns in the data were labeled for use in machine learner. Although skiing data proved to be difficult to label precisely, a classifier trained on 37 labelled examples correctly label all 13 examples from a different test data set with 2 false positives. This method allows for the use of a single sensor and may be generalizable to other applications.
... The efficacy and precision of human annotators, whether employing video, data, or both for annotating events across four human activity recognition (HAR) tasks [28] observed that annotators were more accurate in classifying kinds of events when employing video alone on all four tasks and more effective while using data alone on three of the four assignments. The annotations of event boundaries based on data alone were more accurate. ...
August 2022
... Such apps have developed a variety of functionalities from personalized training plans, weight loss tracking, to measuring steps and distance covered, estimating calories loss, etc., and some apps also explore social interactions in this context. Hakkila and Rovaniemi [7] and Anderson and Jones [1] argue that mobile technology has the potential to support activities in nature in ways that can be regarded as calming, relaxing and purifying, provided that the systems developed support users in an unobtrusive manner. For example, the Hobbit app [17] explores the concept of an asocial hiking app, in which users can generate routes that avoid meeting other people. ...
October 2020
... Self-reflection empowers athletes to draw upon their prior experiences, effectively leveraging them to improve future performances in pursuit of their goals [63]. Previous studies have explored the use of various tools to support self-reflection on running data, including dashboards [38], applications on smartwatches, smartphones, and smart devices [23,26,36], physicalization of data [1,32], and integrated displays on running shoes [60]. While these reflection tools have different objectives, they share the common goal of enhancing self-knowledge, self-modelling, and goal tracking to help with promoting positive running behaviour, motor learning [14,51], and self-development in sports [22]. ...
January 2020
... Many of the most recent published papers in the field of machine learning and Activity Recognition (AR) rely heavily on labeled data sets. For this reason, the synchronization approach using visual key and synchronization using real-time clocks were made to label the obtained data [32]. ...
November 2019
... Note that only one data logger and one video stream are captured. This approach has been used in data collection for Alpine skiing [4], hiking [3], and rock climbing [3]. Synchronization in this process involves capturing, on video, a red flash emitted by the data logger ten seconds after the data logger is turned on. ...
September 2017
... Up to now various movement related workshops have taken place, e.g. [8,37,39,54]. We want to highlight the workshop "Move to be Moved" [20], that focused on discussing the emerging landscape that is formed by movement-based design, establishing an academic community in IxD and HCI. ...
September 2017
... Community building efforts have also been undertaken in this area, such as with NatureCHI [4,5], UbiMount [1], and the CHI Outside SIG at CHI 2017 [7]. But many are still unaware of others working in this area and of the work they are doing. ...
May 2017
... IMU suits are a popular sensing modality in studies that focus on vibration [16] or turn detection [17]. Other studies investigated skier turn detection algorithms for alpine skiing and utilized a small number of IMUs across various locations on the skier body such as the knee [18] or boot cuff [19,20]. Ref. [6] had a similar sensing setup and used in-field data to classify specific skiing maneuver types. ...
September 2016