| dc.description.abstract | Computer technology has been widely used in the performing arts for decades. Interactive performance builds on the traditional performing arts as it includes interaction with the audience or performer. The motion-sensing technology used in dance performance enables a digital dance performance that provides more layers of artistic creation and meaning to the body. Though wearable technol- ogy has been extensively explored for motion sensing, previous research mainly focused on fitness, rehabilitation, games and education, largely with hard wear- able devices. There are a limited number of explorations and considerations for dance applications where the comfort and flexibility of the sensing parts need to be prioritised. This raises questions about how to design a soft sensing system that meets the requirements for dance applications. This research proposes an e-textile stretch sensor-based sensing garment for a digital dance performance that measures torso movements for detecting dance postures. Five studies are undertaken to systematically design, analyse, and evalu- ate the garment: 1) expert interviews to gather requirements and expectations to enrich design concepts; 2) analysis of material properties to choose suitable materials for sensor design; 3) testing of integration methods and washability to verify the sensor’s reliability; 4) exploring sensor placement to understand the sensing area on the body and inform garment design; 5) validation of the final version of the garment to evaluate the e-textile stretch sensor-based sens- ing system. Based on the findings of each study, a step-by-step development of a soft sensing garment design was guided, providing proof of concept that the textile stretch sensor can be integrated into garments to capture motion data comfortably, reliably, and unobtrusively. This has direct implications for designing soft wearable interfaces for dance applications in human-computer in- teraction. Moreover, the mixed-methods approach, including qualitative and quantitative engineering analyses and machine learning approaches adopted in this thesis, provides informative evidence to answer the research question. The main contribution of this PhD is systematically applying engineering analysis in designing a textile-based sensing system for digital art performances. Analysing sensor properties in each step of creating a textile sensing system leads to a more robust sensing system for torso movement in dance applications. | en_US |
