Browsing by Author "Pires, Gabriel"
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- Recognition of human activity based on sparse data collected from smartphone sensorsPublication . Gordalina, Goncalo; Correia, Pedro; Pires, Gabriel; Oliveira, Luis; Figueiredo, Maria João; Martinho, Ricardo; Rijo, Rui, Rui Pedro Charters Lopes; Assunção, Pedro; Seco, Maria Alexandra Abreu Henriques; Fonseca-Pinto, RuiThis paper proposes a method of human activity monitoring based on the regular use of sparse acceleration data and GPS positioning collected during smartphone daily utilization. The application addresses, in particular, the elderly population with regular activity patterns associated with daily routines. The approach is based on the clustering of acceleration and GPS data to characterize the user’s pattern activity and localization for a given period. The current activity pattern is compared to the one obtained by the learned data patterns, generating alarms of abnormal activity and unusual location. The obtained results allow to consider that the usage of the proposed method in real environments can be beneficial for activity monitoring without using complex sensor networks.
- Tracking human routines towards adaptive monitoring: the MOVIDA.domus platformPublication . Gordalina, Gonçalo; Figueiredo, João; Martinho, Ricardo; Rijo, Rui; Correia, Pedro; Assunção, Pedro A. Amado; Seco, Alexandra; Pires, Gabriel; Oliveira, Luís; Fonseca-Pinto, RuiAccording to estimates by the World Health Organization, the average life expectancy will continue to rise. This indicator, being a measure of success in terms of healthcare, is not synonymous with quality of life and will increase healthcare costs. Associated with this problem are also the changes in terms of the organization of society, which has not been able to solve these constraints of functional limitations, dementia, social isolation, and loneliness. This paper presents the concept of adaptive surveillance based on mobile technology and artificial intelligence, presented in the context of a global physical activity monitoring program (MOVIDA), in his domus dimension designed to the elderly people with some functional limitation or dementia. The proposed solution for an adaptive surveillance is thus to conduct direct supervision programs, to enroll persons who live alone or in nursing homes who need supervision without limiting their individual autonomy. The preliminary results show that it is possible to use the data obtained from a mobile smartphone to identify routines and use this information to identify daily patterns. Changes to these routine patterns can be used to generate alarms for caregivers.