Differences in Gait Stability and Acceleration Characteristics Between Healthy Young and Older Females

Our aim was to evaluate differences in gait acceleration intensity, variability, and stability of feet and trunk between older females (OF) and young females (YF) using inertial sensors. Twenty OF (mean age 68.4, SD 4.1 years) and 18 YF (mean age 22.3, SD 1.7 years) were asked to walk straight for 100 meters at their preferred speed, while wearing inertial sensors on their heels and lower back. We calculated spatiotemporal measures, foot and trunk acceleration characteristics, their variability, and trunk stability using the local divergence exponent (LDE). Two-way ANOVA (such as the factors foot and age), Student's t-test and Mann–Whitney U test were used to compare statistical differences of measures between groups. Cohen's d effects were calculated for each variable. Foot maximum vertical (VT) acceleration and amplitude, trunk-foot VT acceleration attenuation, and their variability were significantly smaller in OF than in YF. In contrast, trunk mediolateral (ML) acceleration amplitude, maximum VT acceleration, amplitude, and their variability were significantly larger in OF than in YF. Moreover, OF showed lower stability (i.e., higher LDE values) in ML acceleration, ML, and VT angular velocity of the trunk. Even though we measured healthy OF, these participants showed lower VT foot accelerations with higher VT trunk acceleration, lower trunk-foot VT acceleration attenuation, less gait stability, and more variability of the trunk, and hence, were more likely to fall. These findings suggest that instrumented gait measurements may help for early detection of changes or impairments in gait performance, even before this can be observed by clinical eye or gait speed.

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Differences in gait stability, trunk and foot accelerations between healthy young and older women

10.1101/2021.02.24.432667 ◽

2021 ◽

Author(s):

Yuge Zhang ◽

Xinglong Zhou ◽

Mirjam Pijnappels ◽

Sjoerd M. Bruijn

Keyword(s):

Inertial Sensors ◽

Age Groups ◽

Vertical Acceleration ◽

Gait Stability ◽

Exercise Habits ◽

Young Females ◽

Age Related ◽

Spatiotemporal Parameters ◽

Lower Maximum ◽

The Difference

AbstractBackgroundGait stability has been shown to be affected by age-related mobility problems, but exercise habits may reduce decline in gait stability. Our aim was to evaluate the variability and stability of feet and trunk between older healthy females and young females using inertial sensors.Method20 older females (OF; mean age 68.4, SD 4.1 years) and 18 young females (YF; mean age 22.3, SD 1.7 years) were asked to walk at their preferred speed, while kinematics were measured using inertial sensors on heels and lower back. Spatiotemporal parameters, acceleration characteristics and their variability, as well as trunk stability as assessed using the local divergence exponent (LDE), were calculated and compared between age groups with two-way ANOVA analyses.ResultsTrunk-foot vertical acceleration attenuation, foot vertical acceleration maximum and amplitude, as well as their variability were significantly smaller in OF than in YF. In contrast, for trunk mediolateral acceleration amplitude, vertical acceleration maximum and amplitude, as well as their variability were significantly larger in OF than in YF. Moreover, OF showed lower stability (i.e. higher LDE values) in ML acceleration, ML and VT angular velocity on the trunk.ConclusionThese findings suggest that healthy older females had a lower maximum toe clearance so that were more likely to trip. Moreover, the acceleration of trunk was sensitive to the difference between healthy older and young females, both in variability and stability. Combined, although older adults had exercise habits, our metrics indicate that they were less stable, which may increase the risk of tripping and balance loss.

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Gait Variability and Complexity during Single and Dual-Task Walking on Different Surfaces in Outdoor Environment

Sensors ◽

10.3390/s21144792 ◽

2021 ◽

Vol 21 (14) ◽

pp. 4792

Author(s):

Denisa Nohelova ◽

Lucia Bizovska ◽

Nicolas Vuillerme ◽

Zdenek Svoboda

Keyword(s):

Dual Task ◽

Inertial Sensor ◽

Cognitive Task ◽

Real Life ◽

Gait Pattern ◽

Gait Variability ◽

Outdoor Environment ◽

Manual Task ◽

Lower Trunk ◽

Trunk Acceleration

Nowadays, gait assessment in the real life environment is gaining more attention. Therefore, it is desirable to know how some factors, such as surfaces (natural, artificial) or dual-tasking, influence real life gait pattern. The aim of this study was to assess gait variability and gait complexity during single and dual-task walking on different surfaces in an outdoor environment. Twenty-nine healthy young adults aged 23.31 ± 2.26 years (18 females, 11 males) walked at their preferred walking speed on three different surfaces (asphalt, cobbles, grass) in single-task and in two dual-task conditions (manual task—carrying a cup filled with water, cognitive task—subtracting the number 7). A triaxial inertial sensor attached to the lower trunk was used to record trunk acceleration during gait. From 15 strides, sample entropy (SampEn) as an indicator of gait complexity and root mean square (RMS) as an indicator of gait variability were computed. The findings demonstrate that in an outdoor environment, the surfaces significantly impacted only gait variability, not complexity, and that the tasks affected both gait variability and complexity in young healthy adults.

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Lower Trunk Acceleration Signals Reflect Fall Risk During Walking

IEICE Transactions on Information and Systems ◽

10.1587/transinf.2015cbl0001 ◽

2016 ◽

Vol E99.D (6) ◽

pp. 1482-1484

Author(s):

Yoshitaka OTANI ◽

Osamu AOKI ◽

Tomohiro HIROTA ◽

Hiroshi ANDO

Keyword(s):

Fall Risk ◽

Lower Trunk ◽

Trunk Acceleration ◽

Acceleration Signals

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WEARABLES REVEAL A GAP BETWEEN GAIT PERFORMANCE IN THE LAB AND DURING 24/7 MONITORING IN OLDER ADULTS

Innovation in Aging ◽

10.1093/geroni/igz038.1218 ◽

2019 ◽

Vol 3 (Supplement_1) ◽

pp. S335-S335

Author(s):

Inbar Hillel ◽

Laura Avanzino ◽

Andrea Cereatti ◽

Marcel Olde Rikkert ◽

Silvia Del Din ◽

...

Keyword(s):

Older Adults ◽

Dual Task ◽

Gait Speed ◽

Daily Living ◽

Laboratory Setting ◽

Gait Performance ◽

Lower Back ◽

Gait Features

Abstract We compared in-lab usual-walking (UW) and dual-task walking (DTW) to daily-living measures of gait obtained during 24/7 monitoring. In-lab gait features (e.g., gait speed, step and stride regularity) derived from UW and DTW were compared to the same gait features during daily-living in 150 elderly fallers (age: 76.5±6.3 years, 37.6% men). Features were extracted from a lower-back accelerometer. In daily-living setting, subjects wore the device for one week and pre-processing detected 30-second walking bouts. A histogram of all walking bouts was determined for each walking feature for each subject, then each subject’s typical, worst and best values were determined. Statistics of reliability were assessed using ICC and Bland-Altman. As expected, in-lab gait speed, step regularity, and stride regularity were worse during DTW, compared to UW. Gait speed, step regularity, and stride regularity during UW were significantly higher (i.e., better) from the typical daily-living values (p<0.0001) and different (p<0.000) from the worst and best values. DTW values tended to be similar to typical daily-living values (p=0.205, p=0.053, p=0.013 respectively). ICC assessment and Bland-Altman plots indicated that in-lab values do not reliably reflect the daily-walking values. Gait values during relatively long daily-living walking bouts are more similar to the corresponding values obtained in the lab during DTW, as compared to UW. Still, gait performance during most daily-living walking bouts are worse than that measured in-lab and do not reliably reflect each other. That is, an older adult’s typical daily-living gait cannot be estimated by simply measuring walking in a structured, laboratory setting.

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What Lies Beneath One’s Feet? Terrain Classification Using Inertial Data of Human Walk

Applied Sciences ◽

10.3390/app9153099 ◽

2019 ◽

Vol 9 (15) ◽

pp. 3099 ◽

Cited By ~ 2

Author(s):

Muhammad Zeeshan Ul Hasnain Hashmi ◽

Qaiser Riaz ◽

Mehdi Hussain ◽

Muhammad Shahzad

Keyword(s):

Inertial Sensors ◽

Support Vector ◽

Gait Patterns ◽

Lower Back ◽

Segmentation Approach ◽

Angular Velocities ◽

Measurement Units ◽

Normal Human ◽

Recorded Data ◽

Validation Strategy

The objective of this study was to investigate if the inertial data collected from normal human walk can be used to reveal the underlying terrain types. For this purpose, we recorded the gait patterns of normal human walk on six different terrain types with variation in hardness and friction using body mounted inertial sensors. We collected accelerations and angular velocities of 40 healthy subjects with two smartphones embedded inertial measurement units (MPU-6500) attached at two different body locations (chest and lower back). The recorded data were segmented with stride based segmentation approach and 194 tempo-spectral features were computed for each stride. We trained two machine learning classifiers, namely random forest and support vector machine, and cross validated the results with 10-fold cross-validation strategy. The classification tasks were performed on indoor–outdoor terrains, hard–soft terrains, and a combination of binary, ternary, quaternary, quinary and senary terrains. From the experimental results, the classification accuracies of 97% and 92% were achieved for indoor–outdoor and hard–soft terrains, respectively. The classification results for binary, ternary, quaternary, quinary and senary class classification were 96%, 94%, 92%, 90%, and 89%, respectively. These results demonstrate that the stride data collected with the low-level signals of a single IMU can be used to train classifiers and predict terrain types with high accuracy. Moreover, the problem at hand can be solved invariant of sensor type and sensor location.

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Estimating Dynamic Gait Stability Using Data from Non-aligned Inertial Sensors

Annals of Biomedical Engineering ◽

10.1007/s10439-010-0018-2 ◽

2010 ◽

Vol 38 (8) ◽

pp. 2588-2593 ◽

Cited By ~ 39

Author(s):

Sjoerd M. Bruijn ◽

Warner R. Th. Ten Kate ◽

Gert S. Faber ◽

Onno G. Meijer ◽

Peter J. Beek ◽

...

Keyword(s):

Inertial Sensors ◽

Gait Stability ◽

Using Data ◽

Dynamic Gait

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Wearable Inertial Gait Algorithms: Impact of Wear Location and Environment in Healthy and Parkinson’s Populations

Sensors ◽

10.3390/s21196476 ◽

2021 ◽

Vol 21 (19) ◽

pp. 6476

Author(s):

Yunus Celik ◽

Sam Stuart ◽

Wai Lok Woo ◽

Alan Godfrey

Keyword(s):

Gait Analysis ◽

Inertial Sensors ◽

Lower Back ◽

Outdoor Environments ◽

Outdoor Walking ◽

Absolute Agreement ◽

Walking Environment ◽

Indoor And Outdoor Environments ◽

The Impact ◽

Indoor And Outdoor

Wearable inertial measurement units (IMUs) are used in gait analysis due to their discrete wearable attachment and long data recording possibilities within indoor and outdoor environments. Previously, lower back and shin/shank-based IMU algorithms detecting initial and final contact events (ICs-FCs) were developed and validated on a limited number of healthy young adults (YA), reporting that both IMU wear locations are suitable to use during indoor and outdoor gait analysis. However, the impact of age (e.g., older adults, OA), pathology (e.g., Parkinson′s Disease, PD) and/or environment (e.g., indoor vs. outdoor) on algorithm accuracy have not been fully investigated. Here, we examined IMU gait data from 128 participants (72-YA, 20-OA, and 36-PD) to thoroughly investigate the suitability of ICs-FCs detection algorithms (1 × lower back and 1 × shin/shank-based) for quantifying temporal gait characteristics depending on IMU wear location and walking environment. The level of agreement between algorithms was investigated for different cohorts and walking environments. Although mean temporal characteristics from both algorithms were significantly correlated for all groups and environments, subtle but characteristically nuanced differences were observed between cohorts and environments. The lowest absolute agreement level was observed in PD (ICC2,1 = 0.979, 0.806, 0.730, 0.980) whereas highest in YA (ICC2,1 = 0.987, 0.936, 0.909, 0.989) for mean stride, stance, swing, and step times, respectively. Absolute agreement during treadmill walking (ICC2,1 = 0.975, 0.914, 0.684, 0.945), indoor walking (ICC2,1 = 0.987, 0.936, 0.909, 0.989) and outdoor walking (ICC2,1 = 0.998, 0.940, 0.856, 0.998) was found for mean stride, stance, swing, and step times, respectively. Findings of this study suggest that agreements between algorithms are sensitive to the target cohort and environment. Therefore, researchers/clinicians should be cautious while interpreting temporal parameters that are extracted from inertial sensors-based algorithms especially for those with a neurological condition.

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A Robust Multi-Channel EMG System for Lower Back and Abdominal Muscles Training

Current Directions in Biomedical Engineering ◽

10.1515/cdbme-2021-2041 ◽

2021 ◽

Vol 7 (2) ◽

pp. 159-162

Author(s):

Roman Kusche ◽

Jan Graßhoff ◽

Andra Oltmann ◽

Lukas Boudnik ◽

Philipp Rostalski

Keyword(s):

Spatial Information ◽

Electrode Placement ◽

Abdominal Muscles ◽

Motion Artefacts ◽

Lower Trunk ◽

Additional Information ◽

Dry Electrodes ◽

Lower Back ◽

Fitness Training ◽

Training Exercises

Abstract EMG is an established method to acquire the action potentials of contracted muscles. Although commercial EMG systems are available and it is one of the most researched biosignals, it has never become widely used in rehabilitation or fitness training monitoring. The reasons are technical challenges of wearable EMG systems regarding electrode placement, motion artefacts and the complex connectivity of multi-channel EMG measurements. We address this problem for the lower back and abdominal musculature, through a novel dry electrodes belt, multi-channel high density EMG circuitry and problem-specific signal processing. The subject can easily strap the dry electrodes belt around himself which provides 16 EMG channels. Interferences from the ECG and motion artefacts are reduced by a stationary wavelet decomposition. Afterwards, an inter-channel filter is applied to increase the robustness of the signals. Subject measurements during different kinds of typical abdominal and lower back training exercises were performed wearing the novel dry electrodes belt. The results show the possibility of robust EMG measurements from the lower back and abdominal muscles by utilizing the gathered redundancy, appropriately. The additional information obtained via the multi-channel EMG circuitry and spatial oversampling can be used to address current problems of EMG applications. It combines the advantages of robustness and the capability of using comfortable dry electrodes. Therefore, the proposed measurement method for acquiring spatial information about the muscle contractions from the lower trunk can be used for rehabilitation or fitness training monitoring.

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