Abstract

The paper presents a preliminary study on the feasibility of a pre-impact fall detector, able to evaluate the risk of fall real-time, allowing the fast adoption of properly strategies of intervention for reducing injuries (e.g. By activating an impact reduction system). A wearable, wireless and minimally invasive surface Electromyography-based system (EMG) has been used to measure four lower-limb muscles activities. This work deals with the identification of highly discriminative features extracted within the EMG signals for the automatic detection of people instability. The framework prototype uses a threshold-based approach assuring real-time functioning and allowing the detection of a typical imbalance condition about 200ms after the stimulus perturbation, in simulated and controlled fall conditions.

Autore Pugliese

• Leone Alessandro , Rescio Gabriele

Tutti gli autori

• Leone A.; Rescio G.; Caroppo A.; Siciliano P.

Titolo volume/Rivista

Non Disponibile

Anno di pubblicazione

2015

ISSN

Non Disponibile

ISBN

9781479982028

Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

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Numero di citazioni Scopus

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Ultimo Aggiornamento Citazioni

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Settori ERC

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Codici ASJC

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