Psychometric properties of wearable technologies to assess post-stroke gait parameters: A systematic review

Raiff Simplicio da Silva; Stephano Tomaz da Silva; Daiane Carla Rodrigues Cardoso; Maria Amanda Ferreira Quirino; Maria Heloiza Araújo Silva; Larissa Araujo Gomes; Jefferson Doolan Fernandes; Raul Alexandre Nunes da Silva Oliveira; Aline Braga Galvão Silveira Fernandes; Tatiana Souza Ribeiro

doi:10.1016/j.gaitpost.2024.08.004

Psychometric properties of wearable technologies to assess post-stroke gait parameters: A systematic review

Gait Posture. 2024 Sep:113:543-552. doi: 10.1016/j.gaitpost.2024.08.004. Epub 2024 Aug 8.

Affiliations

¹ Postgraduate Program in Physical Therapy, Department of Physical Therapy, Federal University of Rio Grande do Norte, 3000 Av. Senador Salgado Filho, Post office box: 1524, Natal, RN 59072-970, Brazil. Electronic address: [email protected].
² Postgraduate Program in Physical Therapy, Department of Physical Therapy, Federal University of Rio Grande do Norte, 3000 Av. Senador Salgado Filho, Post office box: 1524, Natal, RN 59072-970, Brazil. Electronic address: [email protected].
³ Postgraduate Program in Physical Therapy, Department of Physical Therapy, Federal University of Rio Grande do Norte, 3000 Av. Senador Salgado Filho, Post office box: 1524, Natal, RN 59072-970, Brazil. Electronic address: [email protected].
⁴ Graduation Program in Physical Therapy, Department of Physical Therapy, Federal University of Rio Grande do Norte, 3000 Av. Senador Salgado Filho, Post office box: 1524, Natal, RN 59072-970, Brazil. Electronic address: [email protected].
⁵ Postgraduate Program in Physical Therapy, Department of Physical Therapy, Federal University of Rio Grande do Norte, 3000 Av. Senador Salgado Filho, Post office box: 1524, Natal, RN 59072-970, Brazil. Electronic address: [email protected].
⁶ Graduation Program in Physical Therapy, Department of Physical Therapy, Federal University of Rio Grande do Norte, 3000 Av. Senador Salgado Filho, Post office box: 1524, Natal, RN 59072-970, Brazil. Electronic address: [email protected].
⁷ Federal Institute of Science and Technology of Rio Grande do Norte, Natal, Rio Grande do Norte 59015-000, Brazil. Electronic address: [email protected].
⁸ Neuromuscular Research Lab, Faculty of Human Kinetic, University of Lisbon, Estrada da Costa, Cruz Quebrada, Dafundo 1499-002, Portugal. Electronic address: [email protected].
⁹ Postgraduate Program in Physical Therapy, Faculty of Health Sciences of Trairi, Federal University of Rio Grande do Norte, Rua Vila Trairi, Santa Cruz, RN 59200-000, Brazil. Electronic address: [email protected].
¹⁰ Postgraduate Program in Physical Therapy, Department of Physical Therapy, Federal University of Rio Grande do Norte, 3000 Av. Senador Salgado Filho, Post office box: 1524, Natal, RN 59072-970, Brazil. Electronic address: [email protected].

PMID: 39178597
DOI: 10.1016/j.gaitpost.2024.08.004

Abstract

Background: Wearable technologies using inertial sensors are an alternative for gait assessment. However, their psychometric properties in evaluating post-stroke patients are still being determined. This systematic review aimed to evaluate the psychometric properties of wearable technologies used to assess post-stroke gait and analyze their reliability and measurement error. The review also investigated which wearable technologies have been used to assess angular changes in post-stroke gait.

Methods: The present review included studies in English with no publication date restrictions that evaluated the psychometric properties (e.g., validity, reliability, responsiveness, and measurement error) of wearable technologies used to assess post-stroke gait. Searches were conducted from February to March 2023 in the following databases: Cochrane Central Registry of Controlled Trials (CENTRAL), Medline/PubMed, EMBASE Ovid, CINAHL EBSCO, PsycINFO Ovid, IEEE Xplore Digital Library (IEEE), and Physiotherapy Evidence Database (PEDro); the gray literature was also verified. The Consensus-based Standards for the Selection of Health Measurement Instruments (COSMIN) risk-of-bias tool was used to assess the quality of the studies that analyzed reliability and measurement error.

Results: Forty-two studies investigating validity (37 studies), reliability (16 studies), and measurement error (6 studies) of wearable technologies were included. Devices presented good reliability in measuring gait speed and step count; however, the quality of the evidence supporting this was low. The evidence of measurement error in step counts was indeterminate. Moreover, only two studies obtained angular results using wearable technology.

Significance: Wearable technologies have demonstrated reliability in analyzing gait parameters (gait speed and step count) among post-stroke patients. However, higher-quality studies should be conducted to improve the quality of evidence and to address the measurement error assessment. Also, few studies used wearable technology to analyze angular changes during post-stroke gait.

Keywords: Measurement error; Post-stroke gait; Psychometric evaluation; Reliability; Validity; Wearable devices.

Publication types

Systematic Review

MeSH terms

Gait / physiology
Gait Analysis* / instrumentation
Gait Disorders, Neurologic* / diagnosis
Gait Disorders, Neurologic* / etiology
Gait Disorders, Neurologic* / physiopathology
Gait Disorders, Neurologic* / rehabilitation
Humans
Psychometrics* / instrumentation
Reproducibility of Results
Stroke / complications
Stroke / physiopathology
Stroke Rehabilitation / methods
Wearable Electronic Devices*