Quantifying stair gait stability in young and older adults,with modifications to insole hardness

Stair gait falls are prevalent in older adults aged 65 years and older. Extrinsic variables such as changes to insole hardness are important factors that can compromise the balance control system and increase the incidence of falls, especially since age-related decline in the cutaneous sensation is common. Balance measurements such as the minimum center of mass/base of support (COM–BOS, termed ‘stability margin') and COM–BOS medial/lateral range provide information about stability during stair gait. This study was conducted to investigate stair gait stability of young and older adults, with modifications to insole hardness. Twenty healthy adults (10 young adults, 10 older adults) were recruited (mean age = 23.1, SD 2.1; mean age = 73.2, SD 5.5) and instructed to descend a 4 step staircase, for a total of 40 trials. All participants wore similar canvas shoes of varying sizes, and corresponding insole hardnesses (barefoot, soft, medium, hard). Kinematic equipment utilized 12 infrared markers anteriorly placed on the individual to record COM motion and BOS location. The findings from the study demonstrated that older adults were less stable during stair descent. Consequently, insole conditions revealed that the barefoot condition may increase the likelihood of falls, as opposed to the other insole hardnesses (soft, medium and hard). These results suggest that older adults while barefoot are putting themselves at a great risk of falling during stair descent. Since age-related changes are inevitable and the preferred footwear of choice inside the home is bare feet, this is a crucial issue that should be addressed.     

Age-independent and age-dependent sex differences in gait pattern determined by principal component analysis

Although various studies have reported significant sex differences in pelvic and/or hip-joint motion during normal walking in healthy adults, it is still unclear whether such differences are among the most dominant age-independent sex differences. This study was conducted to analyze the whole waveform of lower-extremity joint kinematics obtained from 191 healthy adults using a principal component analysis (PCA). The PCA was conducted using a 955 × 1212 input matrix constructed from the participants’ time-normalized pelvic and right-lower-limb-joint angles along three axes (five trials of 191 participants × 101 data points × 4 angles × 3 axes). Two-way (age × sex) analyses of variance were conducted on the principal component scores (PCSs) of principal component vectors (PCVs) 1 through 6, each of which explained more than 5% of the variance. We identified a PCV that exhibits a significant age–sex interaction (PCV 1). The characteristics of sex differences reported in previous studies could be observed in the reconstructed waveforms of this PCV. Thus, we can conclude that the sex differences in the gaits reported in previous studies are not consistent across age groups. Furthermore, we also found a PCV that exhibited only a significant sex difference (PCV 6). This PCV was the first and only PCV to exhibit a sex difference without any age-related effect or age–sex interaction. Therefore, we concluded that the movement related to this PCV is age-independent and is the most dominant sex difference in the gaits observed during normal walking.     

Reliability of walking and stair climbing kinematics in a young obese population using a standard kinematic and the CGM2 model

Background:Recently, the successor of the Conventional Gait Model, the CGM2 was introduced. Even though achievable reliability of gait kinematics is a well-assessed topic in gait analysis for several models, information about reliability in difficult study samples with high amount of subcutaneous fat is scarce and to date, not available for the CGM2. Therefore, this study evaluated the test–retest reliability of the CGM2 model for difficult data with high amount of soft tissue artifacts.Research question:What is the test–retest reliability of the CGM2 during level walking and stair climbing in a young obese population? Is there a clinically relevant difference in reliability between a standard direct kinematic model and the CGM2?Methods:A retrospective test–retest dataset from eight male and two female volunteers was used. It comprised standard 3D gait analysis data of three walking conditions: level walking, stair ascent and descent. To quantify test–retest reliability the Standard Error of Measurement (SEM) was calculated for each kinematic waveform for a direct kinematic model (Cleveland clinic marker set) and the CGM2.Results:Both models showed an acceptable level of test–retest reliability in all three walking conditions. However, SEM ranged between two and five degrees (${}^{\circ }$) for both models and, thus, needs consideration during interpretation. The choice of model did not affect reliability considerably. Differences in SEM between stair climbing and level walking were small and not clinically relevant ($<$1°).Significance:Results showed an acceptable level of reliability and only small differences between the models. It is noteworthy, that the SEM was increased during the first half of swing in all walking conditions. This might be attributed to increased variability resulting for example from inaccurate knee and ankle axis definitions or increased variability in the gait pattern and needs to be considered during data interpretation.     

Centre of mass motion during stair negotiation in young and older men

The aim of this study was to compare centre of mass (COM) motion and its separation from centre of pressure (COP) as 13 young men (aged 23-36 years) and 15 healthy, community dwelling older men (aged 73-84 years) ascended and descended a three step staircase at a controlled cadence of approximately 90 steps/min. Centre of mass was obtained from whole body motion analysis, and simultaneously, COP was obtained using force plates built into the steps. The following variables were investigated: medio-lateral COM range of motion; peak antero-posterior and medio-lateral COM-COP separation; and peak antero-posterior, medio-lateral, and vertical COM velocities. No significant differences in these variables between young men and older men were present during ascent or descent. It was concluded that frontal plane dynamic stability during stair negotiation is well maintained in healthy older men, and that healthy older men do not exhibit an altered strategy in traversing the COM in the plane of progression during stair negotiation.     

Knee and hip kinetics during normal stair climbing

Understanding joint kinetics during activities of daily living furthers our understanding of the factors involved in joint pathology and the effects of treatment. In this study, we examined hip and knee joint kinetics during stair climbing in 35 young healthy subjects using a subject-specific knee model to estimate bone-on-bone tibiofemoral and patello-femoral joint contact forces. The net knee forces were below one body weight while the peak posterior-anterior contact force was close to one body weight. The peak distal-proximal contact force was on average 3 times body weight and could be as high as 6 times body weight. These contact forces occurred at a high degree of knee flexion where there is a smaller joint contact area resulting in high contact stresses. The peak knee adduction moment was 0.42 (0.15) Nm/kg while the flexion moment was 1.16 (0.24) Nm/kg. Similar peak moment values, but different curve profiles, were found for the hip. The hip and knee posterior-anterior shear forces and the knee flexion moment were higher during stair climbing than during level walking. The most striking difference between stair ascent and level walking was that the peak patello-femoral contact force was 8 times higher during stair ascent. These data can be used as baseline measures in pathology studies, as input to theoretical joint models, and as input to mechanical joint simulators.     

Multispectral magnetic resonance image analysis using principal component and linear discriminant analysis

PURPOSE: To explore the possibilities of combining multispectral magnetic resonance (MR) images of different patients within one data matrix. MATERIALS AND METHODS: Principal component and linear discriminant analysis was applied to multispectral MR images of 12 patients with different brain tumors. Each multispectral image consisted of T1-weighted, T2-weighted, proton-density-weighted, and gadolinium-enhanced T1-weighted MR images, and a calculated relative regional cerebral blood volume map. RESULTS: Similar multispectral image regions were clustered, while dissimilar multispectral image regions were scattered in a single plot. Both principal component and linear discriminant analysis allowed discrimination between healthy and tumor regions on the image. In addition, linear discriminant analysis allowed discrimination between oligodendrogliomas and astrocytomas. However, the discriminant analysis method was partially capable of recognizing the tumor identity in unknown multispectral images. CONCLUSION: The proposed method may help the radiologist in comparing multispectral MR images of different patients in a more easy and objective way.     

Application of principal component analysis in vertical ground reaction force to discriminate normal and abnormal gait

Discrete parameters from ground reaction force (GRF) are been considered in gait analysis studies. However, principal component analysis (PCA) may provide additional insight into gait analysis for considering the complete pattern of GRF. This study aimed at testing the application of PCA to discriminate the vertical GRF pattern between control group (CG) and patients with lower limb fractures (FG), as well as proposing a score to quantify the abnormality of gait. Thirty-eight healthy subjects participated of CG and 13 subjects in FG, five subjects from FG were also evaluated after physiotherapeutic treatment (FGA). The GRF was measured by an instrumented treadmill. Principal component coefficients (PCCs) were obtained by singular value decomposition using GRF of complete stride. Two, four and six PCCs were used to obtain the standard distance (D). The classification between groups was mainly given by the first PC, which indicated higher loading factors during push off of affected side and heel strike of unaffected side. The classification performance achieved 92.2% accuracy with two PCCs, 94.1% with four PCCs and 96.1% with six PCCs. Four subjects reached normal boundary after treatment, with all FGA subjects presenting decreased D. This study demonstrates that PCA is an adequate method for discriminating normal and abnormal gait and D allows an objective evaluation of the progress and effectiveness of rehabilitation treatment.     

Discriminating features of ground reaction forces in overweight old and young adults during walking using functional principal component analysis

BackgroundLimited attention has been paid to age- or body size-related changes in the ground reaction forces (GRF) during walking despite their strong associations with lower limb injuries and pathology.Research questionDo the features of GRF during walking associate with age or body size?MethodsFifty-four participants were subdivided into four groups according to their age and body size: overweight old (n = 12), non-overweight old (n = 13), overweight young (n = 13), and non-overweight young (n = 16). Participants were asked to walk at their self-selected speeds on level ground with force plates embedded in the center of walkway. Functional principal component analysis (FPCA) was performed to extract major modes of variation and functional principal component scores (FPCs) in three-dimensional GRFs. Analysis of variance models were employed to investigate the effect of age, body size, or their interactions on the FPCs of each component of the GRF, with the adjustment to gait speed.ResultsSignificant age and body size effects were observed in FPC1 across all three-dimensional GRF. Both overweight and older groups showed greater braking force after heel-strike and greater propulsive forces during pre-swing when compared to the non-overweight and younger groups, respectively. The overweight old group displayed greater medial forces during mid-stance and the overweight young group showed prominently larger medial forces during pre-swing, while non-overweight old showed a tendency of flatter medial-lateral GRF waveforms during the entire stance phase. FPC2 revealed that only body size had an effect on three-dimensional GRF with the highest FPC2 scores in the overweight old group.SignificanceThree-dimensional GRF during walking could be altered by the body size and age, which were more pronounced in the overweight and older group. The more dynamic GRF pattern with greater and/or lower peaks could be contributing factors to the increased joint load and injury rates observed in overweight aged individuals.     

Predicting ground contact events for a continuum of gait types: An application of targeted machine learning using principal component analysis

An ongoing challenge in the application of gait analysis to clinical settings is the standardized detection of temporal events, with unobtrusive and cost-effective equipment, for a wide range of gait types. The purpose of the current study was to investigate a targeted machine learning approach for the prediction of timing for foot strike (or initial contact) and toe-off, using only kinematics for walking, forefoot running, and heel-toe running. Data were categorized by gait type and split into a training set (∼30%) and a validation set (∼70%). A principal component analysis was performed, and separate linear models were trained and validated for foot strike and toe-off, using ground reaction force data as a gold-standard for event timing. Results indicate the model predicted both foot strike and toe-off timing to within 20 ms of the gold-standard for more than 95% of cases in walking and running gaits. The machine learning approach continues to provide robust timing predictions for clinical use, and may offer a flexible methodology to handle new events and gait types.     

Biomechanical features of gait waveform data associated with knee osteoarthritis: an application of principal component analysis

This study compared the gait of 50 patients with end-stage knee osteoarthritis to a group of 63 age-matched asymptomatic control subjects. The analysis focused on three gait waveform measures that were selected based on previous literature demonstrating their relevance to knee osteoarthritis (OA): the knee flexion angle, flexion moment, and adduction moment. The objective was to determine the biomechanical features of these gait measures related to knee osteoarthritis. Principal component analysis was used as a data reduction tool, as well as a preliminary step for further analysis to determine gait pattern differences between the OA and the control groups. These further analyses included statistical hypothesis testing to detect group differences, and discriminant analysis to quantify overall group separation and to establish a hierarchy of discriminatory ability among the gait waveform features. The two groups were separated with a misclassification rate (estimated by cross-validation) of 8%. The discriminatory features of the gait waveforms were, in order of their discriminatory ability: the amplitude of the flexion moment, the range of motion of the flexion angle, the magnitude of the flexion moment during early stance, and the magnitude of the adduction moment during stance.     

Kinematics of stair descent in young and older adults and the impact of exercise training

Stair descent is a challenging task in old age. This study firstly investigated lower extremity kinematics during stair descent in young (YOU) and healthy, community dwelling older adults (OLD). Secondly, the impact of an exercise training intervention on age-related differences in stair descent was assessed. At baseline, a motion analysis system was used to determine spatio-temporal gait variables and lower extremity kinematics as YOU (n=23, age=27+/-3 years) and OLD (n=34, age=73+/-4 years) descended a three step staircase. The older adults were then divided into training (TRA) and control (CON) groups. For 12 months, TRA performed resistance, aerobic, balance, and flexibility exercises under supervision in a class environment (twice per week) and unsupervised at home (once per week). CON carried on with normal daily activities. Following the intervention, baseline measurements were repeated in TRA and CON. At baseline, total descent, stride cycle, and single support times were longer in OLD than in YOU. In addition, sagittal plane knee motion was lower in OLD whilst frontal and transverse plane pelvis and hip motion were higher in OLD. Exercise training did not reduce the age-related differences observed. In conclusion healthy older adults perform stair descent at a slower speed and with greater motion outside the plane of progression than young adults. We found no evidence that these differences are reduced by generic exercise training, at least in non-frail older adults.     

Six degree of freedom joint power in stair climbing

In the past, joint power has most often been calculated as the product of the sagittal plane joint moment and the sagittal plane joint angular velocity, thus modelling the joint as a simple one degree of freedom (DOF) hinge. More recently three DOF power has been calculated by taking the scalar product of the net joint moment and the angular velocity of the joint, thus modelling the joint as a ball and socket joint. We introduce a six DOF approach for calculating joint power, an approach which allows three degrees of rotational freedom, as well as three degrees of translational freedom, thus implementing a rigorous definition of true mechanical power. We established that for the hip joint during stair ascent, three DOF power was significantly greater than six DOF power (by as much as 60 W/kg), while for stair descent, one DOF power was significantly less than six DOF power (by up to 45 W/kg). On the basis of the total work done in raising the body up a set of stairs (weight × height), the six DOF approach provided more accurate results than either the one or three DOF models. We also showed that six DOF power data were as repeatable as joint moments, with variance ratios between 0.13 and 0.20. While these findings are certainly not the definitive word, they do offer some guidance regarding the effect that certain assumptions have when calculating joint power in three dimensions.     

Improving image contrast using principal component analysis for subsequent image segmentation

This article presents a technique for improving MR image contrast by linearly combining multiple MR images with different tissue contrast. The weighting coefficients of the linear combination are derived using principal component analysis. The contrast-enhanced composite image is segmented subsequently using gray level-based 1D segmentation methods. The technique reduces a multispectral image set to composite eigenimages and allows application of appropriate 1D segmentation methods that do not have equivalent counterparts in multispectral methods.     

The Dynamic Gait Index in healthy older adults: the role of stair climbing, fear of falling and gender

The Dynamic Gait Index (DGI) was developed as a clinical tool to assess gait, balance and fall risk. Because the DGI evaluates not only usual steady-state walking, but also walking during more challenging tasks, it may be an especially sensitive test. The present investigation evaluated the DGI and its association with falls, fear of falling, depression, anxiety and other measures of balance and mobility in 278 healthy elderly individuals. Measures included the DGI, the Berg Balance Test (BBT), the Timed Up and Go (TUAG), the Mini-Mental State Exam (MMSE), the Unified Parkinson's Disease Rating Scale (UPDRS) motor part, the Activities-specific Balance Confidence (ABC) scale and the number of annual falls. The DGI was moderately correlated with the BBT (r=0.53; p<0.001), the TUAG (r=-0.42; p<0.001) and the ABC (r=0.49; p<0.001). Fallers performed worse on the DGI compared to non-fallers (p=0.029). Scores on the DGI were near perfect in men (23.3+/-1.2), but among women, there was a small, but significant (p<0.001) decrease (22.5+/-1.6). The reduction in the DGI score in women was due to stair climbing performance, with many women (65%) choosing to walk while holding a handrail, compared to only 39% of men. Scores on the BBT, the TUAG, the UPDRS and the MMSE were similar in men and women. Conversely, ABC scores and fall history were different. These findings suggest that the DGI, although susceptible to ceiling effects, appears to be an appropriate tool for assessing function in healthy older adults.     

Collision avoidance behaviours between older adult and young adult walkers

BackgroundCollision avoidance between two walkers requires a mutual adaptation based on visual information in order to be successful. Age-related changes to visuomotor processing, kinesthetic input, and intersegmental dynamics increases the risk of collision and falls in older adults. However, few studies examine behavioural strategies in older adults during collision avoidance tasks with another pedestrian.Research questionIs there a difference between older adults’ and young adults’ collision avoidance behaviours with another pedestrian?MethodsSeventeen older adults ($\overline{\text{x}}$ = 68 ± 3 years) and seventeen young adults ($\overline{\text{x}}$ = 23 ± 2 years) walked at a comfortable walking speed along a 12.6 m pathway while avoiding another walker. Trials were randomized equally to include 20 interactions with the same age group and 21 interactions with the opposite age group. Minimum predicted distance (mpd) was used to characterize collision avoidance behaviours between older adults and young adults.ResultsOlder adults had riskier avoidance behaviours, passing closer to the other pedestrian (0.79 m ± 0.18 m) compared to when two young adults were on a collision course (0.93 m ± 0.17 m) (χ²(3) = 35.94, p < .0001). Whenever an older adult was on a collision course with a young adult, the young adult contributed more to the avoidance regardless of passing order.SignificanceThe results from the current study highlight age-related effects during a collision avoidance task in older adults resulting in risky behaviour and a potential collision. Future studies should further investigate age-related visuomotor deficits during collision avoidance tasks in cluttered environments using virtual reality in order to tease out factors that contribute most to avoidance behaviours in older adults.     

Registration of dynamic dopamine D2 receptor images using principal component analysis

This paper describes a novel technique for registering a dynamic sequence of single-photon emission tomography (SPET) dopamine D₂ receptor images, using principal component analysis (PCA). Conventional methods for registering images, such as count difference and correlation coefficient algorithms, fail to take into account the dynamic nature of the data, resulting in large systematic errors when registering time-varying images. However, by using principal component analysis to extract the temporal structure of the image sequence, misregistration can be quantified by examining the distribution of eigenvalues. The registration procedures were tested using a computer-generated dynamic phantom derived from a high-resolution magnetic resonance image of a realistic brain phantom. Each method was also applied to clinical SPET images of dopamine D₂ receptors, using the ligands iodine-123 iodobenzamide and iodine-123 epidepride, to investigate the influence of misregistration on kinetic modelling parameters and the binding potential. The PCA technique gave highly significant (P<0.001) improvements in image registration, leading to alignment errors in x and y of about 25% of the alternative methods, with reductions in autocorrelations over time. It could also be applied to align image sequences which the other methods failed completely to register, particularly ¹²³I-epidepride scans. The PCA method produced data of much greater quality for subsequent kinetic modelling, with an improvement of nearly 50% in the χ ² of the fit to the compartmental model, and provided superior quality registration of particularly difficult dynamic sequences. Received 1 August and in revised form 21 August 1997     

Spectral quantitation by principal component analysis using complex singular value decomposition.

Principal component analysis (PCA) is a powerful method for quantitative analysis of nuclear magnetic resonance spectral data sets. It has the advantage of being model independent, making it well suited for the analysis of spectra with complicated or unknown line shapes. Previous applications of PCA have required that all spectra in a data set be in phase or have implemented iterative methods to analyze spectra that are not perfectly phased. However, improper phasing or imperfect convergence of the iterative methods has resulted in systematic errors in the estimation of peak areas with PCA. Presented here is a modified method of PCA, which utilizes complex singular value decomposition (SVD) to analyze spectral data sets with any amount of variation in spectral phase. The new method is shown to be completely insensitive to spectral phase. In the presence of noise, PCA with complex SVD yields a lower variation in the estimation of peak area than conventional PCA by a factor of approximately 2. The performance of the method is demonstrated with simulated data and in vivo 31P spectra from human skeletal muscle.     

Correcting waveform bias using principal component analysis: Applications in multicentre motion analysis studies

Multicentre studies are rare in three dimensional motion analyses due to challenges associated with combining waveform data from different centres. Principal component analysis (PCA) is a statistical technique that can be used to quantify variability in waveform data and identify group differences. A correction technique based on PCA is proposed that can be used in post processing to remove nuisance variation introduced by the differences between centres. Using this technique, the waveform bias that exists between the two datasets is corrected such that the means agree. No information is lost in the individual datasets, but the overall variability in the combined data is reduced. The correction is demonstrated on gait kinematics with synthesized crosstalk and on gait data from knee arthroplasty patients collected in two centres. The induced crosstalk was successfully removed from the knee joint angle data. In the second example, the removal of the nuisance variation due to the multicentre data collection allowed significant differences in implant type to be identified. This PCA-based technique can be used to correct for differences between waveform datasets in post processing and has the potential to enable multicentre motion analysis studies.     

Fast MR parameter mapping using k‐t principal component analysis

Quantification of magnetic resonance parameters plays an increasingly important role in clinical applications, such as the detection and classification of neurodegenerative diseases. The major obstacle that remains for its widespread use in clinical routine is the long scanning times. Therefore, strategies that allow for significant decreases in scan time are highly desired. Recently, the k‐t principal component analysis method was introduced for dynamic cardiac imaging to accelerate data acquisition. This is done by undersampling k‐t space and constraining the reconstruction of the aliased data based on the k‐t Broad‐use Linear Acquisition Speed‐up Technique (BLAST) concept and predetermined temporal basis functions. The objective of this study was to investigate whether the k‐t principal component analysis concept can be adapted to parameter quantification, specifically allowing for significant acceleration of an inversion recovery fast imaging with steady state precession (TrueFISP) acquisition. We found that three basis functions and a single training data line in central k‐space were sufficient to achieve up to an 8‐fold acceleration of the quantification measurement. This allows for an estimation of relaxation times T₁ and T₂ and spin density in one slice with sub‐millimeter in‐plane resolution, in only 6 s. Our findings demonstrate that the k‐t principal component analysis method is a potential candidate to bring the acquisition time for magnetic resonance parameter mapping to a clinically acceptable level. Magn Reson Med, 2011. © 2011 Wiley‐Liss, Inc.