Abstract

Fall detection for elder people is a very challenging task that has not been solved yet. In this population, fall detection devices must not introduce extra constraints, like carrying with a belt fixed device or a mobile phone. This paper describes one fall detection approach accomplishing with these constraints. Afterwards, a discussion on some model decisions concerning the computational restrictions according to where the data processing and classification are performed is also included.

Keywords:
Computer science Task (project management) Cloud computing Mobile phone Population Mobile device Phone Battery (electricity) Real-time computing Artificial intelligence Engineering Power (physics) Telecommunications Operating system

Metrics

1
Cited By
0.14
FWCI (Field Weighted Citation Impact)
27
Refs
0.43
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Context-Aware Activity Recognition Systems
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Anomaly Detection Techniques and Applications
Physical Sciences →  Computer Science →  Artificial Intelligence
Non-Invasive Vital Sign Monitoring
Physical Sciences →  Engineering →  Biomedical Engineering
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