Fall detection system for elderly people : a neural network approach
In this work a new approach for a fall detection system is proposed. The device integrates a 3-axis accelerometer and a 3-axis gyroscope to measure linear acceleration and angular velocities, respectively. Information from both sensors is used to characterize movements through selected features extr...
| Autor principal: | |
|---|---|
| Outros Autores: | , |
| Formato: | conferenceObject |
| Idioma: | eng |
| Publicado em: |
2014
|
| Texto completo: | http://hdl.handle.net/10198/10426 |
| País: | Portugal |
| Oai: | oai:bibliotecadigital.ipb.pt:10198/10426 |
| Resumo: | In this work a new approach for a fall detection system is proposed. The device integrates a 3-axis accelerometer and a 3-axis gyroscope to measure linear acceleration and angular velocities, respectively. Information from both sensors is used to characterize movements through selected features extracted from raw data. A classification system based on a Feedforward Backpropagation Neural Network is then trained, based on the extracted features. The performed tests present low false positives and low false negatives rates with good specificity and sensitivity values. |
|---|