Literature DB >> 26685258

Home-Based Risk of Falling Assessment Test Using a Closed-Loop Balance Model.

Johannes C Ayena, Helmi Zaibi, Martin J-D Otis, Bob-Antoine J Menelas.   

Abstract

The aim of this study is to improve and facilitate the methods used to assess risk of falling at home among older people through the computation of a risk of falling in real time in daily activities. In order to increase a real time computation of the risk of falling, a closed-loop balance model is proposed and compared with One-Leg Standing Test (OLST). This balance model allows studying the postural response of a person having an unpredictable perturbation. Twenty-nine volunteers participated in this study for evaluating the effectiveness of the proposed system which includes seventeen elder participants: ten healthy elderly ( 68.4 ±5.5 years), seven Parkinson's disease (PD) subjects ( 66.28 ±8.9 years), and twelve healthy young adults ( 28.27 ±3.74 years). Our work suggests that there is a relationship between OLST score and the risk of falling based on center of pressure measurement with four low cost force sensors located inside an instrumented insole, which could be predicted using our suggested closed-loop balance model. For long term monitoring at home, this system could be included in a medical electronic record and could be useful as a diagnostic aid tool.

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Year:  2015        PMID: 26685258     DOI: 10.1109/TNSRE.2015.2508960

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  7 in total

1.  Linearity and repeatability of postural responses in relation to peak force and impulse of manually delivered perturbations: a preliminary study.

Authors:  Zeevi Dvir; Maria Paterna; Martina Quargnenti; Carlo De Benedictis; Daniela Maffiodo; Walter Franco; Carlo Ferraresi; Andrea Manca; Franca Deriu; Silvestro Roatta
Journal:  Eur J Appl Physiol       Date:  2020-04-15       Impact factor: 3.078

2.  Impact of Parkinson's Disease on Functional Mobility at Different Stages.

Authors:  Sara Mollà-Casanova; Jose Pedrero-Sánchez; Marta Inglés; Juan López-Pascual; Elena Muñoz-Gómez; Marta Aguilar-Rodríguez; Nuria Sempere-Rubio; Pilar Serra-Añó
Journal:  Front Aging Neurosci       Date:  2022-06-15       Impact factor: 5.702

3.  Investigation of Anticipatory Postural Adjustments during One-Leg Stance Using Inertial Sensors: Evidence from Subjects with Parkinsonism.

Authors:  Gianluca Bonora; Martina Mancini; Ilaria Carpinella; Lorenzo Chiari; Maurizio Ferrarin; John G Nutt; Fay B Horak
Journal:  Front Neurol       Date:  2017-07-25       Impact factor: 4.003

Review 4.  Freezing of gait and fall detection in Parkinson's disease using wearable sensors: a systematic review.

Authors:  Ana Lígia Silva de Lima; Luc J W Evers; Tim Hahn; Lauren Bataille; Jamie L Hamilton; Max A Little; Yasuyuki Okuma; Bastiaan R Bloem; Marjan J Faber
Journal:  J Neurol       Date:  2017-03-01       Impact factor: 4.849

5.  Predicting reactive stepping in response to perturbations by using a classification approach.

Authors:  Amber R Emmens; Edwin H F van Asseldonk; Vera Prinsen; Herman van der Kooij
Journal:  J Neuroeng Rehabil       Date:  2020-07-02       Impact factor: 4.262

6.  Feasibility of Sensor Technology for Balance Assessment in Home Rehabilitation Settings.

Authors:  Daniel Kelly; Karla Muñoz Esquivel; James Gillespie; Joan Condell; Richard Davies; Shvan Karim; Elina Nevala; Antti Alamäki; Juha Jalovaara; John Barton; Salvatore Tedesco; Anna Nordström
Journal:  Sensors (Basel)       Date:  2021-06-28       Impact factor: 3.576

7.  Response Time to a Vibrotactile Stimulus Presented on the Foot at Rest and During Walking on Different Surfaces.

Authors:  Landry Delphin Chapwouo Tchakouté; Louis Tremblay; Bob-Antoine J Menelas
Journal:  Sensors (Basel)       Date:  2018-06-29       Impact factor: 3.576

  7 in total

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