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      MGait : Model-Based Gait Analysis Using Wearable Bend and Inertial Sensors

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          Abstract

          Movement disorders, such as Parkinson’s disease, affect more than 10 million people worldwide. Gait analysis is a critical step in the diagnosis and rehabilitation of these disorders. Specifically, step and stride lengths provide valuable insights into the gait quality and rehabilitation process. However, traditional approaches for estimating step length are not suitable for continuous daily monitoring since they rely on special mats and clinical environments. To address this limitation, this article presents a novel and practical step-length estimation technique using low-power wearable bend and inertial sensors. Experimental results show that the proposed model estimates step length with 5.49% mean absolute percentage error and provides accurate real-time feedback to the user.

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          Prevalence of Parkinson’s disease across North America

          C. Marras, J Beck, J. H. Bower … (2018)
          Estimates of the prevalence of Parkinson’s disease in North America have varied widely and many estimates are based on small numbers of cases and from small regional subpopulations. We sought to estimate the prevalence of Parkinson’s disease in North America by combining data from a multi-study sampling strategy in diverse geographic regions and/or data sources. Five separate cohort studies in California (2), Minnesota (1), Hawaii USA (1), and Ontario, Canada (1) estimated the prevalence of PD from health-care records (3), active ascertainment through facilities, large group, and neurology practices (1), and longitudinal follow-up of a population cohort (1). US Medicare program data provided complementary estimates for the corresponding regions. Using our age- and sex-specific meta-estimates from California, Minnesota, and Ontario and the US population structure from 2010, we estimate the overall prevalence of PD among those aged ≥45 years to be 572 per 100,000 (95% confidence interval 537–614) that there were 680,000 individuals in the US aged ≥45 years with PD in 2010 and that that number will rise to approximately 930,000 in 2020 and 1,238,000 in 2030 based on the US Census Bureau population projections. Regional variations in prevalence were also observed in both the project results and the Medicare-based calculations with which they were compared. The estimates generated by the Hawaiian study were lower across age categories. These estimates can guide health-care planning but should be considered minimum estimates. Some heterogeneity exists that remains to be understood.
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            Validity of the GAITRite walkway system for the measurement of averaged and individual step parameters of gait.

            Lorraine Webster, Andreas Feller, Joanne Wittwer (2005)
            This study compared individual step and averaged spatial and temporal gait parameters measured with an instrumented walkway system (GAITRite) with a three-dimensional motional analysis system (Vicon-512). Ten subjects aged 54-83 years (mean 66.5 years) who had undergone knee replacement surgery participated. Subjects walked across the GAITRite walkway at self-selected comfortable and fast speeds at the same time as the Vicon system recorded the motion of reflective markers attached to the subjects' shoes. Walking speed, cadence, step length and step time variables, averaged across one walk for both systems, showed an excellent level of agreement with intra-class correlation coefficients (ICCs) between 0.92 and 0.99 and repeatability coefficients (RCs) between 1.0% and 5.9% of mean values. Step length and step time variables recorded for each footstep also showed good agreement between the systems at both comfortable and fast speeds (ICCs between 0.91 and 0.99; RCs between 2.6% and 7.8%). Frequency distributions showed that individual step values were within 1.5 cm and 0.02 s on the majority (80-94%) of occasions. These data indicate that the GAITRite system is a valid tool for measuring both averaged and individual step parameters of gait. It is also valid for use in older subjects following knee joint replacement surgery.
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              Gait asymmetry in patients with Parkinson's disease and elderly fallers: when does the bilateral coordination of gait require attention?

              Meir Plotnik, Galit Yogev, Jeffrey M. Hausdorff … (2007)
              While it is known that certain pathologies may impact on left-right symmetry of gait, little is known about the mechanisms that contribute to gait symmetry or how high in the hierarchy of the control of gait symmetry is regulated in humans. To assess the contribution of cognitive function to gait symmetry, we measured gait asymmetry (GA) in three subject groups, patients with Parkinson's disease (PD, n = 21), idiopathic elderly fallers (n = 15), and healthy elderly controls (n = 11). All subjects walked, under two walking conditions: usual walking and dual tasking (cognitive loading) condition. For each subject, the swing time (SW) was calculated and averaged across strides for the left and right feet (SWL and SWR). GA was defined as: 100 x /ln(SWR/SWL)/. For both the PD patients and the elderly fallers GA values were significantly higher during the usual walking condition, as compared with the control group (P < 0.01). In addition, for both the PD patients and the elderly fallers, GA significantly increased when they walked and performed a dual task, compared with the usual walking condition (P < 0.003). In contrast, dual tasking did not affect the GA of the healthy controls (P = 0.518). GA was associated with gait speed and gait variability, but no correlations were found between GA and the asymmetry of the classic PD motor symptoms. Thus, the results suggest that the ability to generate a steady, rhythmic walk with a bilaterally coordinated gait does not rely heavily on mental attention and cognitive resources in healthy older adults. In contrast, however, when gait becomes impaired and less automatic, GA apparently relies on cognitive input and attention.
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                Author and article information

                Journal
                Title: ACM Transactions on Internet of Things
                Abbreviated Title: ACM Trans. Internet Things
                Publisher: Association for Computing Machinery (ACM)
                ISSN (Print): 2691-1914
                ISSN (Electronic): 2577-6207
                Publication date Created: February 28 2022
                Publication date (Electronic): October 27 2021
                Publication date (Print): February 28 2022
                Volume: 3
                Issue: 1
                Pages: 1-24
                Affiliations
                [1 ]University of Wisconsin-Madison, Madison, Wisconsin, USA
                [2 ]Arizona State University, Tempe, Arizona, USA
                [3 ]Washington State University, Pullman, Washington, USA
                Article
                DOI: 10.1145/3485434
                SO-VID: 97652a40-bf21-410a-8599-495ede869244
                Copyright © © 2022
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