HYPOalert: Designing Mobile Technology for Hypoglycemic Detection and Monitoring--Based on Human Breath
dc.contributor.author | Faiola, Anthony | |
dc.contributor.author | Vatani, Haleh | |
dc.contributor.author | Greenhill, Kate | |
dc.contributor.author | Bhuma, Manjula | |
dc.contributor.author | Agarwal, Mangilal | |
dc.contributor.department | Mechanical and Energy Engineering, School of Engineering and Technology | en_US |
dc.date.accessioned | 2019-06-27T18:04:34Z | |
dc.date.available | 2019-06-27T18:04:34Z | |
dc.date.issued | 2018-05 | |
dc.description.abstract | Hypoglycemia (HYPO) is characterized by low blood glucose (BG)--leading to complications such as sweating, weakness, passing-out, coma, and even death. Effective HYPO management is required to avoid complications and to increase quality of life. Recently, a noninvasive smart breathing sensor was developed for detection of HYPO in human breath (HYPOalert). The device has the ability to deliver data (via Bluetooth) to a mobile application--with the intent to support Type 1 and 2 diabetics with the self-management of their hypoglycemia. This paper presents the first two (prototype) design iterations of research and testing of HYPOalert. Twelve Type 1 and 2 diabetics were interviewed to deduce user requirements and to understand their perception and level of interest in the proposed mobile system. Outcomes informed a human-centered design process of the interactive prototype, currently under final testing. Results were positive--showing that users were very interested in HYPOalert's use of visualization, as well as its HYPO monitoring and alert system that supports diabetes patients' healthy lifestyle management. | en_US |
dc.eprint.version | Author's manuscript | en_US |
dc.identifier.citation | Faiola, A., Vatani, H., Greenhill, K., Bhuma, M., & Agarwal, M. (2018). HYPOalert: Designing Mobile Technology for Hypoglycemic Detection and Monitoring–Based on Human Breath. Proceedings of the 12th EAI International Conference on Pervasive Computing Technologies for Healthcare, 402–406. https://doi.org/10.1145/3240925.3240975 | en_US |
dc.identifier.uri | https://hdl.handle.net/1805/19718 | |
dc.language.iso | en | en_US |
dc.publisher | ACM | en_US |
dc.relation.isversionof | 10.1145/3240925.3240975 | en_US |
dc.relation.journal | Proceedings of the 12th EAI International Conference on Pervasive Computing Technologies for Healthcare | en_US |
dc.rights | Publisher Policy | en_US |
dc.source | Author | en_US |
dc.subject | hypoglycemia | en_US |
dc.subject | diabetes | en_US |
dc.subject | breathing sensor | en_US |
dc.title | HYPOalert: Designing Mobile Technology for Hypoglycemic Detection and Monitoring--Based on Human Breath | en_US |
dc.type | Article | en_US |