Literature DB >> 30241925

Using Smartphones to Collect Quantitative Data on Lower Limb Functionality in People Who Have Suffered a Stroke.

Jose Antonio Merchán-Baeza1, Manuel González-Sánchez2, Antonio Ignacio Cuesta-Vargas3.   

Abstract

GOAL: The main objective was to use the inertial sensor integrated into a smartphone to collect quantitative data on lower limb functioning during execution of the timed up and go test and sit to stand test by people in the acute stage of stroke. The secondary objective was to analyze whether smartphones provide reliable quantitative data on performance of these functional tests.
MATERIAL AND METHODS: Cross-sectional analytical study involving 8 elderly people (M age = 67.50 years). Both tests were performed to parametrize and analyze the functionality, balance, and strength of lower limbs using an inbuilt inertial sensor of the smartphone. Time, difference in trunk position, angular displacement, angular velocity, and angular acceleration were measured and calculated for each stage at which both functional tests were divided.
RESULTS: The obtained results highlight the similarity in the angular displacement during the 2 stages into which the sitting-standing (flexion: 38.85° and extension: 38.10°) and the standing-sitting (flexion: 36.42° and extension: 36.45°) phases were divided. Mean velocities of .59 m/s and .61 m/s were registered during outward and return walking phases. The intra- and interobserver reliability of variables recorded with the inbuilt inertial sensor ranged from .860 to .897.
CONCLUSIONS: Balance and muscle strength problems of stroke patients gave rise to the use of compensatory mechanisms when getting up from or sitting down in a chair and resulted in a reduction in walking speed that is sufficient to make walking in community contexts difficult. Smartphones has excellent reliability when used to quantify lower limb functioning in stroke patients.
Copyright © 2018. Published by Elsevier Inc.

Entities:  

Keywords:  Kinematic; balance; clinimetric; functional task; stroke survivors

Mesh:

Year:  2018        PMID: 30241925     DOI: 10.1016/j.jstrokecerebrovasdis.2018.08.012

Source DB:  PubMed          Journal:  J Stroke Cerebrovasc Dis        ISSN: 1052-3057            Impact factor:   2.136


  5 in total

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Review 2.  Psychometric analysis of the questionnaires for the assessment of upper limbs available in their Italian version: a systematic review of the structural and psychometric characteristics.

Authors:  Luca Barni; María Ruiz-Muñoz; Manuel Gonzalez-Sanchez; Antonio I Cuesta-Vargas; Jose Merchan-Baeza; Marco Freddolini
Journal:  Health Qual Life Outcomes       Date:  2021-11-22       Impact factor: 3.186

3.  Mobile phone enabled mental health monitoring to enhance diagnosis for severity assessment of behaviours: a review.

Authors:  Abinaya Gopalakrishnan; Revathi Venkataraman; Raj Gururajan; Xujuan Zhou; Rohan Genrich
Journal:  PeerJ Comput Sci       Date:  2022-08-02

4.  Inertial Sensor-Based Step Length Estimation Model by Means of Principal Component Analysis.

Authors:  Melanija Vezočnik; Roman Kamnik; Matjaz B Juric
Journal:  Sensors (Basel)       Date:  2021-05-19       Impact factor: 3.576

5.  An Experimental Study on the Validity and Reliability of a Smartphone Application to Acquire Temporal Variables during the Single Sit-to-Stand Test with Older Adults.

Authors:  Diogo Luís Marques; Henrique Pereira Neiva; Ivan Miguel Pires; Eftim Zdravevski; Martin Mihajlov; Nuno M Garcia; Juan Diego Ruiz-Cárdenas; Daniel Almeida Marinho; Mário Cardoso Marques
Journal:  Sensors (Basel)       Date:  2021-03-15       Impact factor: 3.576

  5 in total

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