Agreement of Gait Events Detection during Treadmill Backward Walking by Kinematic Data and Inertial Motion Units

Gottlieb, Uri; Balasukumaran, Tharani; Hoffman, Jay R.; Springer, Shmuel

doi:10.3390/s20216331

Cited by 12 publications

(9 citation statements)

References 23 publications

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“…The peaks of sagittal angular velocity and acceleration data were identified as initial foot contact (IC) and terminal foot contact (TC) during both FW and BW. In a previous work, we demonstrated excellent reliability (interclass correlation > 0.9) between this method and data acquired with an eight-camera motion capture system (Qualisys, Göteborg, Sweden) and analyzed with Visual 3-D software (C-motion, Inc., Kingston, ON, Canada) to identify IC and TC ( Gottlieb et al, 2020 ).…”

Section: Methodsmentioning

confidence: 77%

Random walk: Random number generation during backward and forward walking- the role of aging

Shapiro

Shaki²,

Gottlieb³

et al. 2022

Front. Aging Neurosci.

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Deficits in executive function, visuospatial abilities, and cognitive embodiment may impair gait performance. This study aimed to investigate the effect of age on random number generation (RNG) performance during forward and backward locomotion to assess cognitive flexibility and cognitive embodiment during walking. Another aim was to examine the effect of age on the associations of RNG performance during walking with stride time variability (STV), the percentage of double support (DS%), and visuospatial abilities as measured by a spatial orientation test (SOT). Twenty old (age 68.8 ± 5.3, 65% female) and 20 young (age 25.2 ± 2.2, 45% female) adults generated random numbers during backward walking (BW) and forward walking (FW) over-ground and over a treadmill with an internal focus of attention and visual-attentive distraction; six walking conditions in total. To assess cognitive flexibility, sample entropy was calculated for each RNG sequence. The average of the first 5 numbers in each RNG task was calculated to assess the relationship between small/large numbers and movement direction. STV and DS% were recorded using inertial measurement units, and spatial orientation was measured using a computerized test. The older subjects had less flexibility in generating random numbers in three of the six walking conditions. A negative correlation between RNG flexibility and STV was found in older adults during treadmill BW with visual-attentive distraction and forward over-ground walking, whereas no correlations were demonstrated in the young group. The spatial orientation score (a higher value means a worse outcome) correlated positively with RNG flexibility in the older group under all walking conditions, suggesting that older adults with better visuospatial orientation have lower cognitive flexibility, and vice versa. There was no correlation between small/large numbers and direction of motion in either group. The correlation between RNG flexibility and STV may indicate similar executive control of verbal and gait rhythmicity in old adults. Conversely, our results suggest that cognitive flexibility and visuospatial ability may decline differently.

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Section: Methodsmentioning

confidence: 77%

Random walk: Random number generation during backward and forward walking- the role of aging

Shapiro

Shaki²,

Gottlieb³

et al. 2022

Front. Aging Neurosci.

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“…Studies with full-body IMUs measuring either mobility-related tasks in older adults or symptoms in PD patients did not measure simultaneously with optical motion capture [ 41 , 42 , 43 ]. Other mobility related-studies that validated IMU-based algorithms against optical motion capture only measured the lower body simultaneously with both systems [ 44 , 45 ]. The upper body can however also provide relevant information regarding mobility [ 4 , 46 ].…”

Section: Discussionmentioning

confidence: 99%

Proposed Mobility Assessments with Simultaneous Full-Body Inertial Measurement Units and Optical Motion Capture in Healthy Adults and Neurological Patients for Future Validation Studies: Study Protocol

Warmerdam

Romijnders

Geritz

et al. 2021

Sensors

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Healthy adults and neurological patients show unique mobility patterns over the course of their lifespan and disease. Quantifying these mobility patterns could support diagnosing, tracking disease progression and measuring response to treatment. This quantification can be done with wearable technology, such as inertial measurement units (IMUs). Before IMUs can be used to quantify mobility, algorithms need to be developed and validated with age and disease-specific datasets. This study proposes a protocol for a dataset that can be used to develop and validate IMU-based mobility algorithms for healthy adults (18–60 years), healthy older adults (>60 years), and patients with Parkinson’s disease, multiple sclerosis, a symptomatic stroke and chronic low back pain. All participants will be measured simultaneously with IMUs and a 3D optical motion capture system while performing standardized mobility tasks and non-standardized activities of daily living. Specific clinical scales and questionnaires will be collected. This study aims at building the largest dataset for the development and validation of IMU-based mobility algorithms for healthy adults and neurological patients. It is anticipated to provide this dataset for further research use and collaboration, with the ultimate goal to bring IMU-based mobility algorithms as quickly as possible into clinical trials and clinical routine.

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“…Ankle angles in the frontal plane during walking were calculated using the Cardan rotation sequence [57]. The raw angle data were then filtered using a first-order, low-pass, 10 Hz Butterworth filter and smoothened by a third-order Savitzky-Golay filter [58]. Each measurement was then divided into separate stance phases (from heel contact to the same foot next toe-off).…”

Section: Ankle Kinematicsmentioning

confidence: 99%

The Immediate Carryover Effects of Peroneal Functional Electrical Stimulation Differ between People with and without Chronic Ankle Instability

Gottlieb

Hoffman

Springer

2022

Sensors

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Chronic ankle instability (CAI) is a common condition that may develop after an ankle sprain. Compared with healthy individuals, those with CAI demonstrate excessive ankle inversion and increased peroneal electromyography (EMG) activity throughout the stance phase of gait, which may put them at greater risk for re-injury. Functional electrical stimulation (FES) of targeted muscles may provide benefits as a treatment modality to stimulate immediate adaptation of the neuromuscular system. The present study investigated the effect of a single, 10 min peroneal FES session on ankle kinematics and peroneal EMG activity in individuals with (n = 24) or without (n = 24) CAI. There were no significant differences in ankle kinematics between the groups before the intervention. However, after the intervention, healthy controls demonstrated significantly less ankle inversion between 0–9% (p = 0.009) and 82–87% (p = 0.011) of the stance phase. Furthermore, a significant within-group difference was observed only in the control group, demonstrating increased ankle eversion between 0–7% (p = 0.011) and 67–81% (p = 0.006) of the stance phase after the intervention. Peroneal EMG activity did not differ between groups or measurements. These findings, which demonstrate that peroneal FES can induce ankle kinematics adaptations during gait, can help to develop future interventions for people with CAI.

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Agreement of Gait Events Detection during Treadmill Backward Walking by Kinematic Data and Inertial Motion Units

Cited by 12 publications

References 23 publications

Random walk: Random number generation during backward and forward walking- the role of aging

Random walk: Random number generation during backward and forward walking- the role of aging

Proposed Mobility Assessments with Simultaneous Full-Body Inertial Measurement Units and Optical Motion Capture in Healthy Adults and Neurological Patients for Future Validation Studies: Study Protocol

The Immediate Carryover Effects of Peroneal Functional Electrical Stimulation Differ between People with and without Chronic Ankle Instability

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