Advanced pedometer for smartphone-based activity tracking

HEALTHINF 2012 - Proceedings of the International Conference on Health Informatics

Volumn , Issue , 2012, Pages 401-404

  Tomlein, Michal ^a   Bielik, Pavol ^a   Krátky, Peter ^a   Mitrík, Štefan ^a   Barla, Michal ^a   Bieliková, Mária ^a  

^a SLOVAK UNIVERSITY OF TECHNOLOGY   (Slovakia)

Author keywords

Activity tracking; Advanced pedometer; Cheating detection; Neural networks

Indexed keywords

ADVANCED PEDOMETER; CHEATING DETECTION; INNOVATIVE APPROACHES; PHYSICAL ACTIVITY;

NEURAL NETWORKS; SMARTPHONES;

DESIGN;

EID: 84861982438     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (6)

1. nd ACM SIGHIT Int. Health Informatics Symposium. Accepted.
2. Bielik, P. (2011). Personalized training plan recommendation and activity tracking for a healthier lifestyle. Bulletin of the ACM Slovakia, 3(4).
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4. Iwane, M., e. a. (2000). Walking 10,000 steps/day or more reduces blood pressure and sympathetic nerve activity in mild essential hypertension. Hypertens Res, 23(6):573-580.
5. Lee, I. and Buchner, D. M. (2008). The importance of walking to public health. Medicine & Science in Sports & Exercise, 40(7).
6. Marschollek, M. et al. (2008). A performance comparison of accelerometry-based step detection algorithms on a large, non-laboratory sample of healthy and mobility-impaired persons. In Engineering in Medicine and Biology Society, EMBS 2008, pages 1319-1322. IEEE.