Age-specific differences in gait domains and global cognitive function in older women: gait characteristics based on gait speed modification

Machine learning approach to classifying declines of physical function and muscle strength associated with cognitive function in older women: gait characteristics based on three speeds

Background

The aging process is associated with a cognitive and physical declines that affects neuromotor control, memory, executive functions, and motor abilities. Previous studies have made efforts to find biomarkers, utilizing complex factors such as gait as indicators of cognitive and physical health in older adults. However, while gait involves various complex factors, such as attention and the integration of sensory input, cognitive-related motor planning and execution, and the musculoskeletal system, research on biomarkers that simultaneously considers multiple factors is scarce. This study aimed to extract gait features through stepwise regression, based on three speeds, and evaluate the accuracy of machine-learning (ML) models based on the selected features to solve classification problems caused by declines in cognitive function (Cog) and physical function (PF), and in Cog and muscle strength (MS).

Methods

Cognitive assessments, five times sit-to-stand, and handgrip strength were performed to evaluate the Cog, PF, and MS of 198 women aged 65 years or older. For gait assessment, all participants walked along a 19-meter straight path at three speeds [preferred walking speed (PWS), slower walking speed (SWS), and faster walking speed (FWS)]. The extracted gait features based on the three speeds were selected using stepwise regression.

Results

The ML model accuracies were revealed as follows: 91.2% for the random forest model when using all gait features and 91.9% when using the three features (walking speed and coefficient of variation of the left double support phase at FWS and the right double support phase at SWS) selected for the Cog+PF+ and Cog-PF- classification. In addition, support vector machine showed a Cog+MS+ and Cog-MS- classification problem with 93.6% accuracy when using all gait features and two selected features (left step time at PWS and gait asymmetry at SWS).

Conclusion

Our study provides insights into the gait characteristics of older women with decreased Cog, PF, and MS, based on the three walking speeds and ML analysis using selected gait features, and may help improve objective classification and evaluation according to declines in Cog, PF, and MS among older women.

The effects of cognitive intervention on inter-joint coordination during walking in the older adults with balance impairment

BACKGROUND

Cognitive interventions are among the effective training-on-gait parameters; however, the effects of such trainings on inter-joints coordination has not been much considered.

RESEARCH QUESTION

Can dual task and executive function training affect inter-joint coordination during walking in elderly with poor balance?

METHODS

Thirty elderly men were purposefully divided into three groups: 1) dual-task training group (DTG), 2) executive function training group (EFG) and 3) control group. After the pre-test, the experimental groups participated in 24 training sessions while the control group were required to do their normal daily tasks. VICON three-dimensional motion analysis system with four T20 series cameras was used to evaluate inter-joints coordination during the experiment. Participants had to walk a 12-meter path while kinematics of their joints was recorded. The inter-joint coordination at the sagittal plane and in four phases were assessed using the vector coding technique.

RESULTS

The findings of this study showed that the greatest effect of the intervention on the coordination between the joints was in the loading and mid-stance phases (p < 0.05). Also, the variability in the coupling angle showed a significant decrease in most phases (p < 0.05).

SIGNIFICANCE

Based on the obtained results, it can be argued that the loading and mid-stance are more involved in postural control and balance because the center of gravity is transferred between the legs and the person is normally on single-leg stance in these phases.

Comparative study of young-old and old-old people using functional evaluation, gait characteristics, and cardiopulmonary metabolic energy consumption

BACKGROUND

Walking is an important factor in daily life. Among older adults, gait function declines with age. In contrast to the many studies revealing gait differences between young adults and older adults, few studies have further divided older adults into groups. The purpose of this study was to subdivide an older adult population by age to identify age-related differences in functional evaluation, gait characteristics and cardiopulmonary metabolic energy consumption while walking.

METHODS

This was a cross-sectional study of 62 old adult participants who were classified into two age groups of 31 participants each as follows: young-old (65-74 years) and old-old (75-84 years) group. Physical functions, activities of daily living, mood state, cognitive function, quality of life, and fall efficacy were evaluated using the Short Physical Performance Battery (SPPB), Four-square Step Test (FSST), Timed Up and Go Test (TUG), Korean Version of the Modified Barthel Index, Geriatric Depression Scale (GDS), Korean Mini-mental State Examination, EuroQol-5 Dimensions (EQ-5D) questionnaire, and the Korean version of the Fall Efficacy Scale. A three-dimensional motion capture system (Kestrel Digital RealTime System®; Motion Analysis Corporation, Santa Rosa, CA, USA) and two force plates (TF-4060-B; Tec Gihan, Kyoto, Japan) were used to investigate spatiotemporal gait parameters (velocity, cadence, stride length, stride width, step length, single support, stance phase, and swing phase), kinematic variables (hip, knee, and ankle joint angles), and kinetic variables (hip, knee, and ankle joint moment and power) of gait. A portable cardiopulmonary metabolic system (K5; Cosmed, Rome, Italy) was used to measure cardiopulmonary energy consumption.

RESULTS

The old-old group showed significantly lower SPPB, FSST, TUG, GDS-SF, and EQ-5D scores (p < 0.05). Among spatiotemporal gait parameters, velocity, stride length, and step length were significantly lower in the old-old group than in the young-old group (p < 0.05). Among the kinematic variables, the knee joint flexion angles during initial contact and terminal swing phase were significantly higher in the old-old than the young-old group (P < 0.05). The old-old group also showed a significantly lower ankle joint plantarflexion angle during the pre- and initial swing phases (P < 0.05). Among the kinetic variables, the hip joint flexion moment and knee joint absorption power in the pre-swing phase were significantly lower in the old-old than the young-old group (P < 0.05).

CONCLUSION

This study demonstrated that participants 75-84 years of age had less functional gaits than their young-old counterparts (65-74 years old). As the walking pace of old-old people diminishes, driving strength to move ahead and pressure on the knee joint also tend to decrease together with stride length. These differences in gait characteristics according to age among older adults could improve our understanding of how aging causes variations in gait that increase the risk of falls. Older adults of different ages may require customized intervention plans, such as gait training methods, to prevent age-related falls.

TRIAL REGISTRATION

Clinical trials registration information: ClinicalTrials.gov Identifier: NCT04723927 (26/01/2021).

Determinants of age-related decline in walking speed in older women

Background

Walking speed is reduced with aging. However, it is not certain whether the reduced walking speed is associated with physical and coordination fitness. This study explores the physical and coordination determinants of the walking speed decline in older women.

Methods

One-hundred-eighty-seven active older women (72.2 ± 6.8 years) were asked to perform a 10-m walk test (self-selected and maximal walking speed) and a battery of the Senior fitness test: lower body strength, lower body flexibility, agility/dynamic balance, and aerobic endurance. Two parameters characterized the walking performance: closeness to the modeled speed minimizing the energetic cost per unit distance (locomotor rehabilitation index, LRI), and the ratio of step length to step cadence (walk ratio, WR). For dependent variables (self-selected and maximal walking speeds), a recursive partitioning algorithm (classification and regression tree) was adopted, highlighting interactions across all the independent variables.

Results

Participants were aged from 60 to 88 years, and their self-selected and maximal speeds declined by 22% and 26% (p < 0.05), respectively. Similarly, all physical fitness variables worsened with aging (muscle strength: 33%; flexibility: 0 to -8 cm; balance: 22%; aerobic endurance: 12%; all p < 0.050). The predictors of maximal walking speed were only WR and balance. No meaningful predictions could be made using LRI and WR as dependent variables.

Discussion

The results suggest that at self-selected speed, the decrease in speed itself is sufficient to compensate for the age-related decline in the motor functions tested; by contrast, lowering the WR is required at maximal speed, presumably to prevent imbalance. Therefore, any excessive lowering of LRI and WR indicates loss of homeostasis of walking mechanics and invites diagnostic investigation.

Estimating Health-Related Quality of Life Based on Demographic Characteristics, Questionnaires, Gait Ability, and Physical Fitness in Korean Elderly Adults

The elderly population in South Korea accounted for 15.5% of the total population in 2019. Thus, it is important to study the various elements governing the process of healthy aging. Therefore, this study investigated multiple prediction models to determine the health-related quality of life (HRQoL) in elderly adults based on the demographics, questionnaires, gait ability, and physical fitness. We performed eight physical fitness tests on 775 participants wearing shoe-type inertial measurement units and completing walking tasks at slower, preferred, and faster speeds. The HRQoL for physical and mental components was evaluated using a 36-item, short-form health survey. The prediction models based on multiple linear regression with feature importance were analyzed considering the best physical and mental components. We used 11 variables and 5 variables to form the best subset of features underlying the physical and mental components, respectively. We laid particular emphasis on evaluating the functional endurance, muscle strength, stress level, and falling risk. Furthermore, stress, insomnia severity, number of diseases, lower body strength, and fear of falling were taken into consideration in addition to mental-health-related variables. Thus, the study findings provide reliable and objective results to improve the understanding of HRQoL in elderly adults.

Prediction of Decline in Global Cognitive Function Using Machine Learning with Feature Ranking of Gait and Physical Fitness Outcomes in Older Adults

Gait and physical fitness are related to cognitive function. A decrease in motor function and physical fitness can serve as an indicator of declining global cognitive function in older adults. This study aims to use machine learning (ML) to identify important features of gait and physical fitness to predict a decline in global cognitive function in older adults. A total of three hundred and six participants aged seventy-five years or older were included in the study, and their gait performance at various speeds and physical fitness were evaluated. Eight ML models were applied to data ranked by the p-value (LP) of linear regression and the importance gain (XI) of XGboost. Five optimal features were selected using elastic net on the LP data for men, and twenty optimal features were selected using support vector machine on the XI data for women. Thus, the important features for predicting a potential decline in global cognitive function in older adults were successfully identified herein. The proposed ML approach could inspire future studies on the early detection and prevention of cognitive function decline in older adults.

XGBoost based machine learning approach to predict the risk of fall in older adults using gait outcomes

This study aimed to identify the optimal features of gait parameters to predict the fall risk level in older adults. The study included 746 older adults (age: 63–89 years). Gait tests (20 m walkway) included speed modification (slower, preferred, and faster-walking) while wearing the inertial measurement unit sensors embedded in the shoe-type data loggers on both outsoles. A metric was defined to classify the fall risks, determined based on a set of questions determining the history of falls and fear of falls. The extreme gradient boosting (XGBoost) model was built from gait features to predict the factor affecting the risk of falls. Moreover, the definition of the fall levels was classified into high- and low-risk groups. At all speeds, three gait features were identified with the XGBoost (stride length, walking speed, and stance phase) that accurately classified the fall risk levels. The model accuracy in classifying fall risk levels ranged between 67–70% with 43–53% sensitivity and 77–84% specificity. Thus, we identified the optimal gait features for accurate fall risk level classification in older adults. The XGBoost model could inspire future works on fall prevention and the fall-risk assessment potential through the gait analysis of older adults.

An integration of enhanced social force and crowd control models for high-density crowd simulation

Social force model is one of the well-known approaches that can successfully simulate pedestrians’ movements realistically. However, it is not suitable to simulate high-density crowd movement realistically due to the model having only three basic crowd characteristics which are goal, attraction, and repulsion. Therefore, it does not satisfy the high-density crowd condition which is complex yet unique, due to its capacity, density, and various demographic backgrounds of the agents. Thus, this research proposes a model that improves the social force model by introducing four new characteristics which are gender, walking speed, intention outlook, and grouping to make simulations more realistic. Besides, the high-density crowd introduces irregular behaviours in the crowd flow, which is stopping motion within the crowd. To handle these scenarios, another model has been proposed that controls each agent with two different states: walking and stopping. Furthermore, the stopping behaviour was categorized into a slow stop and sudden stop. Both of these proposed models were integrated to form a high-density crowd simulation framework. The framework has been validated by using the comparison method and fundamental diagram method. Based on the simulation of 45,000 agents, it shows that the proposed framework has a more accurate average walking speed (0.36 m/s) compared to the conventional social force model (0.61 m/s). Both of these results are compared to the real-world data which is 0.3267 m/s. The findings of this research will contribute to the simulation activities of pedestrians in a highly dense population.

Low composite functional movement screen score associated with decline of gait stability in young adults

Background

The functional movement screen (FMS)^TM is a screening tool used to evaluate fundamental motor function. A score of 14 for the composite total FMS score (TFMS) is generally used as the cut-off point (≤14/21). In addition, gait analysis is used to evaluate fundamental motor function in humans. Thus, evaluating the fundamental motor function using the FMS^TM test and gait analysis at various speeds can provide further understanding of any decline in gait stability. In this study, we aimed to investigate the association between gait ability and fundamental movement patterns in young adults according to the cut-off point.

Methods

A total of 439 participants (male: 203, female: 236) successfully completed the FMS test and a 1 min treadmill test; the participants were classified into two groups: low TFMS (≤14) and high TFMS (>14).

Results

The low TFMS group exhibited slower and shortened walking patterns and worsen gait variability than the high TFMS group. The coefficient of variance (CV) for the double support phase at a faster speed (male) and the stride length at a slower speed (female) were classifiers between the two groups. In addition, the low TFMS group demonstrated insufficient gait adaptation at the preferred and faster speeds based on the CV of the double support phase and gait asymmetry. Lower TFMS is associated with a decline in gait ability. Therefore, participants with a lower TFMS and poor gait ability may require intervention programs to prevent risk of future injury and to enhance motor function.

Characteristics of Gait Variability in the Elderly While Walking on a Treadmill with Gait Speed Variation

Gait variability (GV), which is a variable for predicting mobility issues and risk of falling in elderly people, is defined as the fluctuation in spatiotemporal characteristics from one step to the next in walking. The goal of this study was to analyze the age- and sex-related spatiotemporal variability characteristics of elderly individuals using the measurements taken while walking on a treadmill for one minute based on gait speed variation. Gait testing was conducted on 225 healthy male and female individuals aged 60–79 years who were able to walk and move on their own and, specifically, walk on a treadmill for one minute. The test was performed at three speed conditions—the preferred speed of the participant, 20% higher than the preferred speed, and 20% lower than the preferred speed—and data were recorded using shoe-type data loggers. The different age groups and sex could be distinguished using the coefficient of variance (CV) of the double support phase and gait asymmetry (GA) at the preferred speed, and CVs of stride length and stance phase at faster speed. The results indicated that the values of GV obtained from the test were used to determine the variation in gait characteristics of elderly individuals.

Sarcopenia as a Mediator of the Effect of a Gerontogymnastics Program on Cardiorespiratory Fitness of Overweight and Obese Older Women: A Randomized Controlled Trial

The objectives were to analyze the effect of a gerontogymnastics program on functional ability and fitness on overweight and obese older woman and to understand if sarcopenia mediates its effect. This randomized controlled trial involved 216 overweight and obese women. The experimental group (EG) carried out 12 weeks of a gerontogymnastics program. The assessment was of gait speed, cardiorespiratory fitness, functional capacity, and muscle strength. EG showed significant improvements in almost every test. When the effect of training was adjusted by gait speed, the improvement of the 6 min walk test (MWT) for the trained group was no longer significant (p = 0.127). The improvement of the 6 MWT was significantly and positively associated with the 10 m test (β = −10.087). After including the 10-m test in the equations, the association between the 6MWT and carrying out the training program decreased but remained significant (β = −19.904). The mediation analysis showed a significant, direct and indirect effect with a significant Sobel test value (z = 6.606 ± 7.733; p = 0.000). These results indicate that a gerontogymnastics program improves functional capacity and fitness; and the effect of a gerontogymnastics program on CRF is mediated by sarcopenia in older women who are overweight and obese.

Association between Gait Variability and Gait-Ability Decline in Elderly Women with Subthreshold Insomnia Stage

This study investigates the gait characteristics of elderly women, aged more than 65 years, with subthreshold insomnia stage at various walking speeds. A total of 392 participants (insomnia: 202 and controls: 190) wearing shoe-type inertial measurement units completed walking tests on a treadmill for a duration of 1 min at slower, preferred, and faster speeds. The insomnia group indicated lower pace parameters (range of Cohen's d: 0.283-0.499) and the single support phase (Cohen's d: 0.237), greater gait variability (range of Cohen's d: 0.217-0.506), and bilateral coordination (range of Cohen's d: 0.254-0.319), compared with their age-matched controls; the coefficient of variance (CV) of the stance phase at the faster speed condition was a crucial variable for distinguishing between insomnia and control groups. In addition, the insomnia group demonstrated insufficient gait adaptation at the slower and preferred speeds, as indicated by the CVs of the stride length, stride time, and step time. In particular, participants with worsened insomnia symptoms or sleep problems showed that these worse gait patterns may increase the potential risk of falling in elderly women. Thus, elderly women with subthreshold insomnia stage need to improve their sleep quality to enhance their physical functions.

Associating Gait Phase and Physical Fitness with Global Cognitive Function in the Aged

This study aimed to identify classifier variables by considering both gait and physical fitness for identifying adults aged over 75 years and global cognitive function declines in older adults. The participants included 735 adults aged 65–89 years who were asked to walk at three different speeds (slower, preferred, and faster) while wearing inertial measurement units embedded in shoe-type data loggers and to perform nine physical fitness tests. The variability in the stance phase as well as the strength, balance, and functional endurance showed a strong dependence on the age being over 75 years. The cognitive function was evaluated by the Mini-Mental State Examination; a longer stance phase at a slower walking speed and decreased grip strength and five times sit-to-stand were associated with cognitive function. These findings may be useful for determining the decline in physical performance of older adults. A longer stance phase and decreased grip strength and five times sit-to-stand may be factors that help distinguish declines in cognitive function from normal age-related declines.

Gait characteristics in individuals with Parkinson's disease during 1-minute treadmill walking

Background

No previous study has examined the age-dependent characteristics of gait in individuals between 50 and 79 years simultaneously in healthy individuals and individuals with Parkinson’s disease (PD) over continuous gait cycles. This study aimed to investigate age-related differences in gait characteristics on individuals age ranged 50–79 years, including individuals with PD, during a 1-minute treadmill walking session. Additionally, we aimed to investigate the differences associated with spatiotemporal gait parameters and PD compared in age-matched individuals.

Methods

This study included 26 individuals with PD and 90 participants age ranged 50–79 years. The treadmill walking test at a self-preferred speed was performed for 1 min. The embedded inertial measurement unit sensor in the left and right outsoles-based system was used to collect gait characteristics based on tri-axial acceleration and tri-axial angular velocities.

Results

Participants aged >60 years had a decreased gait speed and shortened stride and step, which may demonstrate a distinct shift in aging (all p < 0.005). Individuals with PD showed more of a decrease in variables with a loss of consistency, including gait asymmetry (GA), phase coordination index (PCI) and coefficient of variation (CV) of all variables, than age-matched individuals (all p < 0.001). Gait speed, stride and step length, stance phase, variability, GA and PCI were the variables that highly depended on age and PD.

Discussion

Older adults could be considered those older than 60 years of age when gait alterations begin, such as a decreased gait speed as well as shortened stride and step length. On the other hand, a loss of consistency in spatiotemporal parameters and a higher GA and PCI could be used to identify individuals with PD. Thus, the CV of all spatiotemporal parameters, GA and PCI during walking could play an important role and be useful in identifying individuals with PD.

Conclusion

This study provided the notable aging pattern characteristics of gait in individuals >50 years, including individuals with PD. Increasing age after 60 years is associated with deterioration in spatiotemporal parameters of gait during continuous 1-minute treadmill walking. Additionally, GA, PCI and the CV of all variables could be used to identify PD which would be placed after 70 years of age. It may be useful to determine the decline of gait performance in general and among individuals with PD.

Gait Characteristics under Imposed Challenge Speed Conditions in Patients with Parkinson's Disease During Overground Walking

Evaluating gait stability at slower or faster speeds and self-preferred speeds based on continuous steps may assist in determining the severity of motor symptoms in Parkinson's disease (PD) patients. This study aimed to investigate the gait ability at imposed speed conditions in PD patients during overground walking. Overall, 74 PD patients and 52 age-matched healthy controls were recruited. Levodopa was administered to patients in the PD group, and all participants completed imposed slower, preferred, and faster speed walking tests along a straight 15-m walkway wearing shoe-type inertial measurement units. Reliability of the slower and faster conditions between the estimated and measured speeds indicated excellent agreement for PD patients and controls. PD patients demonstrated higher gait asymmetry (GA) and coefficient of variance (CV) for stride length and stance phase than the controls at slower speeds and higher CVs for phases for single support, double support, and stance. CV of the double support phase could distinguish between PD patients and controls at faster speeds. The GA and CVs of stride length and phase-related variables were associated with motor symptoms in PD patients. Speed conditions should be considered during gait analysis. Gait variability could evaluate the severity of motor symptoms in PD patients.