Ambulatory health monitoring has been demonstrated to provide significant benefits to patients in a number of studies. The biggest promise for improved results for patients lies in the long-term, ambulatory monitoring of patients with chronic illnesses to help doctors and patients identify health issues before they reach a crisis stage. This project pursues the design of garments for ambulatory health monitoring that have the look and feel of every day clothing, together with an approach to monitoring that removes some of the barriers to patient compliance by automatically annotating physiological data with activities and motions, collecting data only during specific conditions, and having minimal impact on daily routine. The intellectual merits lie in the algorithms, design methodologies, and evaluation methodologies that enable wear-and-forget garments for ambulatory health monitoring. The approach developed by this project uses a computationally intensive pose estimation algorithm that automatically adapts a more computationally efficient algorithm for activity classification. This project addresses the challenges of providing garments that look and feel like everyday clothing by developing design and evaluation methodologies for incorporating fiber-based sensors into garments. These have significant advantages over discrete sensors by being woven or sewn into the fabric, covering much larger areas of a garment, and draping naturally. The broader impacts of the research lie in the potential to remove barriers that prevent the effective use of ambulatory health monitoring to improve the quality of life for patients and their families.
Berglund, Mary Ellen, James Coughlin, Guido Gioberto, and Lucy E. Dunne. "Washability of e-textile stretch sensors and sensor insultation." In Proceedings of the 2014 ACM International Symposium on Wearable Computers, pp. 127-128. ACM, 2014.
Dunne, Lucy E., Richard Tynan, Gregory MP O'Hare, Barry Smyth, Sarah Brady, and Dermot Diamon. "Coarse sensing of upper arm position using body-garment interactions." In Proceedings of the 2nd International Forum on Applied Wearable Computing, pp. 138-141. 2005
Dunne, Lucy E., Barry Smyth, and Brian Caulfield. "Evaluating the impact of garment structure on wearable sensor performance." In 2007 11th IEEE International Symposium on Wearable Computers, pp. 123-124. IEEE, 2007
Gioberto, Guido, James Coughlin, Kaila Bibeau, and Lucy E. Dunne. "Detecting bends and fabric folds using stitched sensors." In Proceedings of the 2013 International Symposium on Wearable Computers, pp. 53-56. ACM, 2013.
Gioberto, Guido. "Garment-integrated wearable sensing for knee joint monitoring." In Proceedings of the 2014 ACM International Symposium on Wearable Computers: Adjunct Program, pp. 113-118. ACM, 2014.
Gioberto, Guido, Cheol-Hong Min, Crystal Compton, and Lucy E. Dunne. "Lower-limb goniometry using stitched sensors: effects of manufacturing and wear variables." In Proceedings of the 2014 ACM International Symposium on Wearable Computers, pp. 131-132. ACM, 2014.
Gioberto, Guido. "Measuring joint movement through garment-integrated wearable sensing." In Proceedings of the 2013 ACM conferencec on Pervasive and ubiquitous computing adjunct publication, pp. 331-336. ACM, 2013
Gioberto, Guido, and Lucy E. Dunne. "Theory and characterization of a top-thread coverstitched stretch sensor." In 2012 IEEE International Conference On Systems, Man, and Cybernetics (SMC), pp. 3275-3280. IEEE, 2012.
Min, Cheol-Hong, Crystal Compton, and Lucy E. Dunne. "Sensing Lower Body Lifting Posture through Disposable Sensing Coveralls." (2015). International Textile and Apparel Association (ITAA) Annual Conference Proceedings. 89.
Pettys-Baker, Robert, Crystal Compton, Sophia Utset-Ward, Marc Tompkins, Brad Holschuh, and Lucy E. Dunne. "Design and Development of Valgus-Sensing Leggings." In 2017 Design of Medical Devices Conference. American Society of Mechanical Engineers, 2017.
Funded by National Science Foundation (grants IIS-1116719, SCH-1722738)
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