Literature DB >> 29439863

Towards the enhancement of body standing balance recovery by means of a wireless audio-biofeedback system.

Giovanni Costantini1, Daniele Casali1, Fabio Paolizzo2, Marco Alessandrini3, Alessandro Micarelli3, Andrea Viziano3, Giovanni Saggio4.   

Abstract

Human maintain their body balance by sensorimotor controls mainly based on information gathered from vision, proprioception and vestibular systems. When there is a lack of information, caused by pathologies, diseases or aging, the subject may fall. In this context, we developed a system to augment information gathering, providing the subject with warning audio-feedback signals related to his/her equilibrium. The system comprises an inertial measurement unit (IMU), a data processing unit, a headphone audio device and a software application. The IMU is a low-weight, small-size wireless instrument that, body-back located between the L2 and L5 lumbar vertebrae, measures the subject's trunk kinematics. The application drives the data processing unit to feeding the headphone with electric signals related to the kinematic measures. Consequently, the user is audio-alerted, via headphone, of his/her own equilibrium, hearing a pleasant sound when in a stable equilibrium, or an increasing bothering sound when in an increasing unstable condition. Tests were conducted on a group of six older subjects (59y-61y, SD = 2.09y) and a group of four young subjects (21y-26y, SD = 2.88y) to underline difference in effectiveness of the system, if any, related to the age of the users. For each subject, standing balance tests were performed in normal or altered conditions, such as, open or closed eyes, and on a solid or foam surface. The system was evaluated in terms of usability, reliability, and effectiveness in improving the subject's balance in all conditions. As a result, the system successfully helped the subjects in reducing the body swaying within 10.65%-65.90%, differences depending on subjects' age and test conditions.
Copyright © 2018 IPEM. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Bio-feedback; E-rehabilitation; IMU; Postural stability; Standing balance

Mesh:

Year:  2018        PMID: 29439863     DOI: 10.1016/j.medengphy.2018.01.008

Source DB:  PubMed          Journal:  Med Eng Phys        ISSN: 1350-4533            Impact factor:   2.242


  2 in total

1.  Sign Language Recognition Using Wearable Electronics: Implementing k-Nearest Neighbors with Dynamic Time Warping and Convolutional Neural Network Algorithms.

Authors:  Giovanni Saggio; Pietro Cavallo; Mariachiara Ricci; Vito Errico; Jonathan Zea; Marco E Benalcázar
Journal:  Sensors (Basel)       Date:  2020-07-11       Impact factor: 3.576

2.  An Embodied Sonification Model for Sit-to-Stand Transfers.

Authors:  Prithvi Kantan; Erika G Spaich; Sofia Dahl
Journal:  Front Psychol       Date:  2022-02-17
  2 in total

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