An inertial sensing mechanism for measuring gait parameters and gait energy expenditure

2021 ◽  
Vol 70 ◽  
pp. 103056
Author(s):  
K.R Vidyarani ◽  
Viswanath Talasila ◽  
N Megharjun ◽  
M Supriya ◽  
K.J Ravi Prasad ◽  
...  
2019 ◽  
Vol 35 (S1) ◽  
pp. 95-95
Author(s):  
Luis María Sánchez-Gómez ◽  
Ana Isabel Hijas-Gómez ◽  
Mar Polo-DeSantos ◽  
Setefilla Luengo-Matos

IntroductionThe Stride Management Assist (SMA®) device consist in a portable robotic exoskeleton designed for gait rehabilitation and training by repetition of walking patterns with automated regular gait cycles. Used for adult population with gait disorders of neurological or musculoskeletal origin that require rehabilitation. The objective of this work is to assess its efficacy and safety.MethodsThis technology was identified by the early Awareness and Alert System, “SINTESIS-new technologies” of AETS-ISCIII. An early assessment of the technology was conducted. The searched databases were: Pubmed, Embase, WOS, Tripdatabase, ClinicalTrials.org and Cochrane Library. Clinical studies using the device published in any language until 10 October 2018 were reviewed.ResultsWe found 3 abstracts to congresses and 6 clinical trials that evaluated the use of the device. Outcomes measures among studies included spatiotemporal gait parameters, energy expenditure, muscular activity and functional performance. Five studies consisted in proof-of-concept analysis; 3 studies evaluated the effect of gait training with SMA® compared with conventional therapy alone in individuals after stroke (2 studies) and Parkinson disease (1 study); and 1 before-and-after study assessed the effect of gait training with SMA® in elderly adults. During its use, improvements in spatiotemporal gait parameters were described in 4/5 studies, and 2/5 studies showed less energy expenditure versus 2/5 studies that found no differences. After gait training, 3/4 studies described greater improvements in gait parameters when associated its use. Only one clinical trial collected safety data reporting no adverse events.ConclusionsThe SMA® device allows to increase the efficiency and parameters of the march during its use. The assistance in the stride might have an impact on health by facilitating the recovery of the gait; however, further research is needed to determine the feasibility in the latter case since comparative studies with conventional therapy are limited.


2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Maria Justine ◽  
Haidzir Manaf ◽  
Affeenddie Sulaiman ◽  
Shahir Razi ◽  
Hani Asilah Alias

This study compares energy expenditure (EE), gait parameters (GP), and level of fatigue (LOF) between 5-minute walking with sharp turning (ST) and corner turning (CT). Data were obtained from 29 community-dwelling elderly (mean age, 62.7 ± 3.54 years). For 5 minutes, in ST task, participants walked on a 3-meter pathway with 2 cones placed at each end (180° turning), while in CT task, participants walked on a 6-meter pathway with 4 cones placed at 4 corners (90° turning). The physiological cost index, pedometer, and 10-point Modified Borg Dyspnoea Scale were used to measure EE (beats/min), GP (no of steps), and LOF, respectively. Data were analyzed by using independentt-tests. EE during ST (0.62 ± 0.21 beats/min) was significantly higher than CT (0.48 ± 0.17 beats/min) (P<0.05). GP (434 ± 92.93 steps) and LOF (1.40 ± 1.11) in ST were found to be lower compared to GP (463 ± 92.18 steps) and LOF (1.54 ± 1.34) in CT (All,P>0.05). Higher EE in ST could be due to the difficulty in changing to a 180° direction, which may involve agility and different turning strategies (step-turn or pivot-turn) to adjust the posture carefully. In CT, participants could choose a step-turn strategy to change to a 90° direction, which was less challenging to postural control.


Author(s):  
DB Kowalsky ◽  
JR Rebula ◽  
LV Ojeda ◽  
PG Adamczyk ◽  
AD Kuo

AbstractHumans often traverse real-world environments with a variety of surface irregularities and inconsistencies, which can disrupt steady gait and require additional effort. Such effects have, however, scarcely been demonstrated quantitatively, because few laboratory biomechanical measures apply outdoors. Walking can nevertheless be quantified by other means. In particular, the foot’s trajectory in space can be reconstructed from foot-mounted inertial measurement units (IMUs), to yield measures of stride and associated variabilities. But it remains unknown whether such measures are related to metabolic energy expenditure. We therefore quantified the effect of five different outdoor terrains on foot motion (from IMUs) and net metabolic rate (from oxygen consumption) in healthy adults (N = 10; walking at 1.25 m/s). Energy expenditure increased significantly (P < 0.05) in the order Sidewalk, Dirt, Gravel, Grass, and Woodchips, with Woodchips about 27% costlier than Sidewalk. Terrain type also affected measures, particularly stride variability and virtual foot clearance (swing foot’s lowest height above consecutive footfalls). In combination, such measures can also roughly predict metabolic cost (adjusted R2 = 0.52, partial least squares regression), and even discriminate between terrain types (10% reclassification error). Body-worn sensors can characterize how uneven terrain affects gait, gait variability, and metabolic cost in the real world.


2018 ◽  
Vol 29 (4) ◽  
pp. 106-109
Author(s):  
Bobeena Rachel Chandy ◽  
Priya Gajendiran ◽  
Joyce Isaac ◽  
Bijesh Yadav ◽  
Rajdeep Ojha

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0228682
Author(s):  
Daniel B. Kowalsky ◽  
John R. Rebula ◽  
Lauro V. Ojeda ◽  
Peter G. Adamczyk ◽  
Arthur D. Kuo

Humans often traverse real-world environments with a variety of surface irregularities and inconsistencies, which can disrupt steady gait and require additional effort. Such effects have, however, scarcely been demonstrated quantitatively, because few laboratory biomechanical measures apply outdoors. Walking can nevertheless be quantified by other means. In particular, the foot’s trajectory in space can be reconstructed from foot-mounted inertial measurement units (IMUs), to yield measures of stride and associated variabilities. But it remains unknown whether such measures are related to metabolic energy expenditure. We therefore quantified the effect of five different outdoor terrains on foot motion (from IMUs) and net metabolic rate (from oxygen consumption) in healthy adults (N = 10; walking at 1.25 m/s). Energy expenditure increased significantly (P < 0.05) in the order Sidewalk, Dirt, Gravel, Grass, and Woodchips, with Woodchips about 27% costlier than Sidewalk. Terrain type also affected measures, particularly stride variability and virtual foot clearance (swing foot’s lowest height above consecutive footfalls). In combination, such measures can also roughly predict metabolic cost (adjusted R2 = 0.52, partial least squares regression), and even discriminate between terrain types (10% reclassification error). Body-worn sensors can characterize how uneven terrain affects gait, gait variability, and metabolic cost in the real world.


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