In this paper we propose a novel approach for online fall-risk assessment based on concurrent EEG and EMG monitoring. The fall-risk evaluation is based on: i) clinical condition of the individual, ii) environment, iii) EMG agonistantagonist co-contraction analysis and iv) Movement Related Potentials and event related desynchronizations occurrence/absence. The fall-risk assessment evaluation algorithm has been implemented on a FPGA (Altera Cyclone V SE 5CSEMA5F31C6N) in order to realize an autonomous and stand-alone fall prevention tool. The experimental results (based on a dataset of 10 individuals) are described and demonstrate the validity of the algorithm and its FPGA implementation, which responds in 41ms, well within the 300ms time limit according to a study on 45 fallers and 80 non-fallers (with 74 years average age).

Fall-Risk Assessment by Combined Movement Related Potentials and Co-contraction Index Monitoring / Annese, V; DE VENUTO, Daniela. - (2015). (Intervento presentato al convegno Biomedical Circuits and Systems Conference, BioCAS 2015 tenutosi a Atlanta, USA nel October 22-24, 2015) [10.1109/BioCAS.2015.7348366].

Fall-Risk Assessment by Combined Movement Related Potentials and Co-contraction Index Monitoring

DE VENUTO, Daniela
2015-01-01

Abstract

In this paper we propose a novel approach for online fall-risk assessment based on concurrent EEG and EMG monitoring. The fall-risk evaluation is based on: i) clinical condition of the individual, ii) environment, iii) EMG agonistantagonist co-contraction analysis and iv) Movement Related Potentials and event related desynchronizations occurrence/absence. The fall-risk assessment evaluation algorithm has been implemented on a FPGA (Altera Cyclone V SE 5CSEMA5F31C6N) in order to realize an autonomous and stand-alone fall prevention tool. The experimental results (based on a dataset of 10 individuals) are described and demonstrate the validity of the algorithm and its FPGA implementation, which responds in 41ms, well within the 300ms time limit according to a study on 45 fallers and 80 non-fallers (with 74 years average age).
2015
Biomedical Circuits and Systems Conference, BioCAS 2015
978-1-4799-7234-0
Fall-Risk Assessment by Combined Movement Related Potentials and Co-contraction Index Monitoring / Annese, V; DE VENUTO, Daniela. - (2015). (Intervento presentato al convegno Biomedical Circuits and Systems Conference, BioCAS 2015 tenutosi a Atlanta, USA nel October 22-24, 2015) [10.1109/BioCAS.2015.7348366].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/20228
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