2026-05-28T13:47:34Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/190132026-02-03T12:29:52Zcom_10630_2254col_10630_37959

00925njm 22002777a 4500 dc Ayala-Viñas, Inmaculada author Fuentes-Fernández, Lidia author Amor-Pinilla, María Mercedes author Caro-Romero, Juan author Ballesteros-Gómez, Joaquín author 2019-12-11 Nowadays, more than one billion people are in need of one or more assistive technologies, and this number is expected to increase beyond two billion by 2050. The majority of assistive technologies are supported by battery-operated devices like smartphones and wearables. This means that battery weight is an important concern in such assistive devices because it may affect negatively its ergonomics. Saving power in these assistive devices is of utmost importance for its potential twofold benefits: extend the device life and reduce the global warming aggravated by billion of these devices. Dynamic Software Product Lines (DSPLs) are a suitable technology that supports system adaptation, in this case, to reduce energy consumption at runtime, considering contextual information and the current state of the device. However, a reduction in battery consumption could negatively affect other quality of service parameters, like response time. Therefore, it is important to trade-off battery saving and these other concerns. This work illustrates how to approach the self-adaptation of smart assistive devices by means of a DSPL-based strategy that optimizes battery consumption taking into account other QoS parameters at the same time. We illustrate our proposal with a real case study: a Smart Cane that is integrated with a DSPL platform, Tanit. Experimentation shows that it is possible to make a trade-off between different quality concerns (energy consumption and relative error). The results of the experiments allow us to conclude that the Tanit approach elongates battery duration of the Smart Cane in one day (an increase of a 6% with a relative error of 1%), so we improve the user quality of experience and reduce the energy footprint with a reasonable relative error. https://hdl.handle.net/10630/19013 Salud Self-Adaptation of mHealth Devices: The Case of the Smart Cane Platform