7 research outputs found

    Gait characterization using wearable inertial sensors in healthy and pathological populations

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    Gait analysis is emerging as an effective tool to detect an incipient neurodegenerative disease or to monitor its progression. It has been shown that gait disturbances are an early indicator for cognitive impairments and can predict progression to neurodegenerative diseases. Furthermore, gait performance is a predictor of fall status, morbidity and mortality. Instrumented gait analysis provides quantitative measures to support the investigation of gait pathologies and the definition of targeted rehabilitation programs. In this framework, technologies such as inertial sensors are well accepted, and increasingly employed, as tools to characterize locomotion patterns and their variability in research settings. The general aim of this thesis is the evaluation, comparison and refinement of methods for gait characterization using magneto-inertial measurement units (MIMUs), in order to contribute to the migration of instrumented gait analysis from state of the art to state of the science (i.e.: from research towards its application in standard clinical practice). At first, methods for the estimation of spatio-temporal parameters during straight gait were investigated. Such parameters are in fact generally recognized as key metrics for an objective evaluation of gait and a quantitative assessment of clinical outcomes. Although several methods for their estimate have been proposed, few provided a thorough validation. Therefore an error analysis across different pathologies, multiple clinical centers and large sample size was conducted to further validate a previously presented method (TEADRIP). Results confirmed the applicability and robustness of the TEADRIP method. The combination of good performance, reliability and range of usage indicate that the TEADRIP method can be effectively adopted for gait spatio-temporal parameter estimation in the routine clinical practice. However, while traditionally gait analysis is applied to straight walking, several clinical motor tests include turns between straight gait segments. Furthermore, turning is used to evaluate subjects’ motor ability in more challenging circumstances. The second part of the research therefore headed towards the application of gait analysis on turning, both to segment it (i.e.: distinguish turns and straight walking bouts) and to specifically characterize it. Methods for turn identification based on a single MIMU attached to the trunk were implemented and their performance across pathological populations was evaluated. Focusing on Parkinson’s Disease (PD) subjects, turn characterization was also addressed in terms of onset and duration, using MIMUs positioned both on the trunk and on the ankles. Results showed that in PD population turn characterization with the sensors at the ankles lacks of precision, but that a single MIMU positioned on the low back is functional for turn identification. The development and validation of the methods considered in these works allowed for their application to clinical studies, in particular supporting the spatio-temporal parameters analysis in a PD treatment assessment and the investigation of turning characteristic in PD subjects with Freezing of Gait. In the first application, comparing the pre and post parameters it was possible to objectively determine the effectiveness of a rehabilitation treatment. In the second application, quantitative measures confirmed that in PD subjects with Freezing of Gait turning 360° in place is further compromised (and requires additional cognitive effort) compared to turning 180° while walking

    Assessment of gait spatio-temporal parameters in neurological disorders using wearable inertial sensors

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    Movement analysis carried out in laboratory settings is a powerful, but costly solution since it requires dedicated instrumentation, space and personnel. Recently, new technologies such as the magnetic and inertial measurement units (MIMU) are becoming widely accepted as tools for the assessment of human motion in clinical and research settings. They are relatively easy-to-use and potentially suitable for estimating gait kinematic features, including spatio-temporal parameters. The objective of this thesis regards the development and testing in clinical contexts of robust MIMUs based methods for assessing gait spatio-temporal parameters applicable across a number of different pathological gait patterns. First, considering the need of a solution the least obtrusive as possible, the validity of the single unit based approach was explored. A comparative evaluation of the performance of various methods reported in the literature for estimating gait temporal parameters using a single unit attached to the trunk first in normal gait and then in different pathological gait conditions was performed. Then, the second part of the research headed towards the development of new methods for estimating gait spatio-temporal parameters using shank worn MIMUs on different pathological subjects groups. In addition to the conventional gait parameters, new methods for estimating the changes of the direction of progression were explored. Finally, a new hardware solution and relevant methodology for estimating inter-feet distance during walking was proposed. Results of the technical validation of the proposed methods at different walking speeds and along different paths against a gold standard were reported and showed that the use of two MIMUs attached to the lower limbs associated with a robust method guarantee a much higher accuracy in determining gait spatio-temporal parameters. In conclusion, the proposed methods could be reliably applied to various abnormal gaits obtaining in some cases a comparable level of accuracy with respect to normal gait

    Gait monitoring: from the clinics to the daily life

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    Monitoring of gait in daily living allows a quantitative analysis of walking in unrestricted conditions, with many potential clinical applications. This thesis aims at addressing the limitations that still hinder the wider adoption of this approach in clinical practice, providing healthcare professionals and researchers new tools which may impact on current gait assessment procedures and improve the treatment of many diseases leading to – or generated by – mobility impairments. The thesis comprises four experimental sections: Accuracy of commercially-available devices. Step detection accuracy in currently available physical activity monitors was assessed in healthy individuals. The best performing device was then tested in multiple sclerosis patients, showing reliability but highly speed-dependent accuracy. These findings suggest that a short set of tests performed in controlled conditions could inform researchers before starting unsupervised monitoring of gait in patients. Differences between laboratory and free-living gait parameters. The study assessed the accuracy of two algorithms for gait event detection, and provided normative values of gait temporal parameters for healthy subjects in different environments and types of walking. A pilot study toward clinical application. This pilot study compared laboratory based tests with daily living assessment of gait features in multiple sclerosis patients. Results provided clear evidence that in this population clinical gait tests might not represent typical gait patterns of daily living. Analysis of free-living walking in patients with Diabetes. A systematic review is presented looking for evidence of the effectiveness of walking as physical activity to reduce inflammation. Then, cadence and step duration variability are examined during free-living walking in a group of patients with diabetes. This thesis systematically highlighted potential and actual limitations in the use of wearable sensors for gait monitoring in daily life, providing clear practical indications and normative values which are essential for the widespread informed and effective clinical adoption of this technology

    Proceedings XXI Congresso SIAMOC 2021

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    XXI Congresso Annuale della SIAMOC, modalità telematica il 30 settembre e il 1° ottobre 2021. Come da tradizione, il congresso vuole essere un’occasione di arricchimento e mutuo scambio, dal punto di vista scientifico e umano. Verranno toccati i temi classici dell’analisi del movimento, come lo sviluppo e l’applicazione di metodi per lo studio del movimento nel contesto clinico, e temi invece estremamente attuali, come la teleriabilitazione e il telemonitoraggio

    Wearable Sensors in the Evaluation of Gait and Balance in Neurological Disorders

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    The aging population and the increased prevalence of neurological diseases have raised the issue of gait and balance disorders as a major public concern worldwide. Indeed, gait and balance disorders are responsible for a high healthcare and economic burden on society, thus, requiring new solutions to prevent harmful consequences. Recently, wearable sensors have provided new challenges and opportunities to address this issue through innovative diagnostic and therapeutic strategies. Accordingly, the book “Wearable Sensors in the Evaluation of Gait and Balance in Neurological Disorders” collects the most up-to-date information about the objective evaluation of gait and balance disorders, by means of wearable biosensors, in patients with various types of neurological diseases, including Parkinson’s disease, multiple sclerosis, stroke, traumatic brain injury, and cerebellar ataxia. By adopting wearable technologies, the sixteen original research articles and reviews included in this book offer an updated overview of the most recent approaches for the objective evaluation of gait and balance disorders
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