Theses and Dissertations
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- Creators: Turaga, Pavan
Human activity recognition is the task of identifying a person’s movement from sensors in a wearable device, such as a smartphone, smartwatch, or a medical-grade device. A great method for this task is machine learning, which is the study of algorithms that learn and improve on their own with the help of massive amounts of useful data. These classification models can accurately classify activities with the time-series data from accelerometers and gyroscopes. A significant way to improve the accuracy of these machine learning models is preprocessing the data, essentially augmenting data to make the identification of each activity, or class, easier for the model. <br/>On this topic, this paper explains the design of SigNorm, a new web application which lets users conveniently transform time-series data and view the effects of those transformations in a code-free, browser-based user interface. The second and final section explains my take on a human activity recognition problem, which involves comparing a preprocessed dataset to an un-augmented one, and comparing the differences in accuracy using a one-dimensional convolutional neural network to make classifications.
This dissertation aims to expand the current scope of Open Design within human-computer interaction (HCI) research through a long-term exploration of Open Design’s socio-technical processes. I examine Open Design from three perspectives: the functional—materials, tools, and platforms that enable crowd-driven open hardware production, the critical—materially-oriented engagements within open design as a site for sociotechnical discourse, and the speculative—crowd-driven critical envisioning of future hardware.
More specifically, this dissertation first explores the growing global scene of Open Design through a long-term ethnographic study of the open science hardware (OScH) movement, a genre of Open Design. This long-term study of OScH provides a focal point for HCI to deeply understand Open Design's growing global landscape. Second, it examines the application of Critical Making within Open Design through an OScH workshop with designers, engineers, artists and makers from local communities. This work foregrounds the role of HCI researchers as facilitators of collaborative critical engagements within Open Design. Third, this dissertation introduces the concept of crowd-driven Design Fiction through the development of a publicly accessible online Design Fiction platform named Dream Drones. Through a six month long development and a study with drone related practitioners, it offers several pragmatic insights into the challenges and opportunities for crowd-driven Design Fiction. Through these explorations, I highlight the broader implications and novel research pathways for HCI to shape and be shaped by the global Open Design movement.