Gait analysis in neurological populations: Progression in the use of wearables

Çelik, Yunus; Stuart, Samuel; Woo, Wai Lok; Godfrey, Alan

doi:10.1016/j.medengphy.2020.11.005

Cited by 98 publications

(84 citation statements)

References 243 publications

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“…An IMU including a triaxial accelerometer (Q'z TAG Walk; Sumitomo Electric Industries Ltd., Osaka, Japan) was used to measure trunk acceleration during gait. The IMU was positioned over the third lumbar vertebra (L3) and secured to the subject using an elastic band according to previous studies [ 2 , 4 , 9 ]. The x , y , and z -axes of the accelerometer corresponded to the mediolateral, anteroposterior, and vertical directions, respectively.…”

Section: Methodsmentioning

confidence: 99%

“…Trunk acceleration measurement by IMU during gait represents the characteristics of walking and is useful to identify gait abnormalities [7]. IMUs can be used not only for calculating important gait parameters, such as spatiotemporal parameters [8][9][10], or for investigating the gait stability and variability between normal and pathological gaits but also for classifying different types of gait patterns, for example, the stroke patient gait pattern [11] or Parkinson's disease gait pattern [12]. These benefits have led to gait analysis with IMUs being widely used in clinical settings and care units.…”

Section: Introductionmentioning

confidence: 99%

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Immediate Effect of Restricted Knee Extension on Ground Reaction Force and Trunk Acceleration during Walking

Osaka

Fujita

Kobara

et al. 2021

Rehabilitation Research and Practice

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Gait parameters calculated from trunk acceleration reflect the features of gait; however, they cannot evaluate the gait pattern corresponding to the gait cycle. This study is aimed at investigating the differences in gait parameters calculated from trunk acceleration during gait corresponding to the gait cycle in healthy subjects with restricted knee extension. Participants included eight healthy volunteers who walked normally (NW) and with knee orthosis that restricted knee extension (ER). The ground reaction force (GRF), joint angles, and trunk acceleration during walking were measured using four force plates, a three-dimensional motion analysis system, and an inertial measurement unit. The peak GRF of the vertical components, joint ranges of motion, and moments of force were analyzed. The root mean square (RMS) and amplitude peak ratio (AR) of autocorrelation function were calculated from the trunk acceleration waveform. The first peak GRF and peak ankle dorsiflexion angles significantly increased during ER. The peak hip extension, knee flexion, knee extension angles, and the peak moment of knee extension significantly decreased during ER compared to that during NW. The acceleration AR significantly decreased during ER compared to that during NW. There was no significant difference in the RMS between the two conditions. The acceleration AR may show the temporal postural structure with restricted knee extension from the terminal stance phase for the ipsilateral limb to the initial stance phase for the contralateral limb. These results suggest that novel metrics for accelerometry gait analysis can reveal gait abnormalities, with restricted knee extension corresponding to the gait cycle.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Immediate Effect of Restricted Knee Extension on Ground Reaction Force and Trunk Acceleration during Walking

Osaka

Fujita

Kobara

et al. 2021

Rehabilitation Research and Practice

View full text Add to dashboard Cite

show abstract

“…Thus, both walkways and motion capturing systems are only suitable for measurements in clinical settings or other controlled environments. A less restrictive option are wearable sensors [ 20 ] for gait tracking [ 21 , 22 ].…”

Section: Introductionmentioning

confidence: 99%

Contactless Gait Assessment in Home-like Environments

Botros

Gyger

Schütz

et al. 2021

Sensors

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Gait analysis is an important part of assessments for a variety of health conditions, specifically neurodegenerative diseases. Currently, most methods for gait assessment are based on manual scoring of certain tasks or restrictive technologies. We present an unobtrusive sensor system based on light detection and ranging sensor technology for use in home-like environments. In our evaluation, we compared six different gait parameters, based on recordings from 25 different people performing eight different walks each, resulting in 200 unique measurements. We compared the proposed sensor system against two state-of-the art technologies, a pressure mat and a set of inertial measurement unit sensors. In addition to test usability and long-term measurement, multi-hour recordings were conducted. Our evaluation showed very high correlation (r>0.95) with the gold standards across all assessed gait parameters except for cycle time (r=0.91). Similarly, the coefficient of determination was high (R2>0.9) for all gait parameters except cycle time. The highest correlation was achieved for stride length and velocity (r≥0.98,R2≥0.95). Furthermore, the multi-hour recordings did not show the systematic drift of measurements over time. Overall, the unobtrusive gait measurement system allows for contactless, highly accurate long- and short-term assessments of gait in home-like environments.

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“…Currently, there is no de nitive way of objectively understanding the reasons for lack of differences in free-living gait between our chronic mTBI and healthy control cohorts, as there are many unknown factors that affect free-living assessments. For example, not knowing the environments people were regularly walking in, the surfaces they walked on, or the types of terrain encountered [54]. Equally, it is not possible to quantify the usual free-living mobility habits of the participants or if this cohort display any compensatory behaviour strategies (e.g.…”

Section: Free Living Gait Characteristics Are Not Impaired In Chronicmentioning

confidence: 99%

Free-living Turning Rather Than Gait Differentiates People with Chronic Mild Traumatic Brain Injury from Controls

Powell¹,

Godfrey²,

Parrington³

et al. 2021

Preprint

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Background: Physical function remains a crucial component of mild traumatic brain injury (mTBI) assessment and recovery. Traditional approaches to assess mTBI lack sensitivity to subtle deficits post-injury, which can impact quality of life, daily function and can lead to chronic issues. Inertial measurement units (IMU) provide an objective alternative for measuring physical function of gait and turning and can be used in any environment. Our recent work has found that turning quality is more sensitive than the quantity of physical activity when comparing chronic mTBI and healthy controls. However, no studies have compared the quality of free-living gait and turning characteristics concurrently in chronic mTBI and healthy controls. This study aimed to determine whether free-living gait or turning is more sensitive in differentiating chronic mTBI from controls.Methods: Thirty-two people with chronic self-reported balance symptoms after mTBI (age: 40.88 ± 11.78 years, median days post injury: 440.68 days) and 23 healthy controls (age: 48.56 ± 22.56 years) were assessed for ~7 days using a single IMU at the waist on a belt. Free-living gait and turning characteristics were evaluated for chronic mTBI and controls using multi-variate analysis. Receiver operating characteristics (ROC) and Area Under the Curve (AUC) analysis were used to determine outcome sensitivity to chronic mTBI.Results: Free-living gait characteristics were not different in chronic mTBI and controls (all p>0.05). In contrast, all but two (number of turns and average velocity CV) free-living turning characteristics were significantly different between chronic mTBI and controls, whilst controlling for age and sex (Bonferroni adjusted p<0.002). The chronic mTBI group had larger turn angles and longer turn durations compared to controls. ROC and AUC analysis showed turn duration (AUC = 0.92) was the most sensitive measure for differentiating chronic mTBI from controls. Conclusions: Results show that turning rather than gait characteristics were significantly different between chronic mTBI and controls, with turn duration being the most sensitive measure. These results suggest turning is a suitable surrogate biomarker to assess and monitor chronic mTBI.

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Gait analysis in neurological populations: Progression in the use of wearables

Cited by 98 publications

References 243 publications

Immediate Effect of Restricted Knee Extension on Ground Reaction Force and Trunk Acceleration during Walking

Immediate Effect of Restricted Knee Extension on Ground Reaction Force and Trunk Acceleration during Walking

Contactless Gait Assessment in Home-like Environments

Free-living Turning Rather Than Gait Differentiates People with Chronic Mild Traumatic Brain Injury from Controls

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