Ageing effects on medio-lateral balance during walking with increased and decreased step width.

The current study used falls direction to categorize falls and explore age-related effects on the biomechanics of medio-lateral balance control. Minimum lateral margin (MLM) was defined as the critical swing phase event where the medio-lateral length between center of mass (CoM) and stance heel became minimum and accordingly, any lateral balance perturbation at MLM was considered to increase the risk of balance loss lateral to the stance foot. Lateral center of pressure (CoP) displacement from toe-off to MLM was also monitored to assess the risk of medio-lateral balance perturbation. Gait testing involving 30 young and 26 older male subjects was conducted under the three step width conditions: preferred and ± 50% wider and narrower. For an overall description of gait, spatio-temporal parameters were also obtained. Typical ageing effects on spatio-temporal parameters such as lower step velocity, shorter step length and prolonged double support time were found, emerging most clearly in narrower, followed by wider and least in preferred width walking. MLM and CoP lateral displacement were not differentiated between the two age groups, but older adults demonstrated significantly more variable MLM and CoP in their non-dominant limb when walking with non-preferred widths. Variability of step width reduced in increased and decreased step width conditions while MLM and CoP variability increased, suggesting less consistent medio-lateral CoM control despite consistent foot control in altered width conditions. In summary, older adults were found to have less consistent control of CoM with respect to the non-dominant stance foot when walking with narrower and wider widths possibly due to more variable medio-lateral CoP control.

Computation method for available response time due to tripping at minimum foot clearance.

Falls prevention is important for older individuals to maintain healthy lifestyles and is an essential challenge in sustaining the socioeconomic structure of many advanced nations. Tripping has been recognized as the largest cause of falls and accordingly, understanding tripping-induced anterior balance loss is necessary in reducing the overall frequency of falls among older adults. Hazardous anterior balance loss due to tripping can be attributed to the mid-swing phase event, minimum foot clearance (MFC). The mechanism of tripping-induced anterior balance loss can be described as anterior movement of the center of mass (CoM) passing the frontal boundary of the supporting base between the swing and stance toes. The first aim of the current study was to establish a computational method for determining available response time (ART) to anterior balance loss due to tripping at MFC, in other words, the time taken for CoM to reach the anterior boundary and therefore, the time limit for balance recovery. Kinematic information of CoM and both toes in addition to simulated impact force due to tripping at MFC were used to estimate ART. The second aim was to apply correlation analysis to a range of gait parameters to identify the factors influencing ART. ART for balance loss in the forward direction due to tripping was on average. 0.11s for both the dominant and non-dominant limbs' simulated tripping at MFC. Correlation analysis revealed five factors at MFC that prolong ART including: 1) greater fore-aft distance from CoM to stance toe, 2) greater sideway distance from CoM to swing toe, 3) longer distance from CoM to the frontal boundary of the supporting base, 4) slower CoM forward velocity and 5) slower horizontal toe velocity. The established ART computation method can be utilized to examine the effects of ageing and various gait tasks on the likelihood of tripping-induced anterior balance loss and associated falls.

On the feasibility of learning to predict minimum toe clearance under different walking speeds.

A major concern in human movement research is preventing tripping and falling which is known to cause severe injuries and high fatalities in elderly (>65 years) populations. Current falls prevention technology consists of active interventions e.g., strength and balance exercises, preimpact fall detectors, and passive interventions e.g., shower rails, hip protectors. However it has been found that these interventions with the exception of balance exercises do not effectively reduce falls risk. Recent work has shown that the minimum toe clearance (MTC) can be successfully monitored to detect gait patterns indicative of tripping and falling risk. In this paper, we investigate the feasibility of predicting MTC values of consecutive gait cycles under different walking speeds. The objective is two-fold, first to determine if end point foot trajectories can be accurately predicted and second, if walking speed is a significant parameter which influences the prediction process. The Generalized Regression Neural Networks and the Support Vector Regressor models were trained to predict MTC time series successively over an increasing prediction horizon i.e., 1 to 10 steps. Increased walking speeds resulted in increased MTC variability but no significant increase in mean MTC height. Root mean squared prediction errors ranged between 2.2-2.6mm or 10% of the mean values of the respective test data. The SVM slightly outperformed the GRNN predictions (0.5%-2.1% better accuracy). Best prediction accuracies decreased by 0.5mm for a doubling of walking speed i.e., from 2.5 km/h to 5.5 km/h. The results are encouraging because they demonstrate that the technique could be applied to forecasting low MTC values and provide new approaches to falls prevention technologies.

Controlling swing foot center of mass and toe trajectory to minimize tripping risk.

Swing toe trajectory has been investigated due to its association with tripping-induced falls. This study investigated how motion of the entire foot segment influences the toe trajectory. Seven young and seven older participants walked both over-ground and on a treadmill to obtain the swing foot trajectory data. No ageing effects were obtained for toe trajectory control. Older adults were found to have greater asymmetry at minimum ground clearance, especially in treadmill walking, whereas foot center of mass (COM) control was symmetrical, suggesting that foot COM motion does not influence toe trajectory. Correlation analysis indicated that foot COM and toe trajectory may be controlled independently due to ankle motions that modulate the toe's elevation, a finding that has implications for falls prevention strategies. The results also provide the first report of the foot's center of mass trajectory during the swing phase of the gait cycle. The foot's trajectory resembles pendulum motion but further work will be necessary to test the foot-pendulum control hypothesis.

A systematic review of the effect of ageing and falls history on minimum foot clearance characteristics during level walking.

Minimum foot clearance (MFC) is the minimum vertical distance between the lowest point of the foot of the swing leg and the walking surface during the swing phase of the gait cycle. MFC is a gait variable that is linked to the mechanism of a trip because reduced MFC for a given step during walking increases the susceptibility to tripping on an unseen obstacle or due to undetected changes in surface height. Given that tripping is a common cause of falls in older persons, this review was undertaken to determine whether ageing and/or history of falls in older adults influences MFC characteristics during level walking. Studies that assessed MFC characteristics including measures of central tendency (mean and/or median), variability (linear and non-linear measures) and shape (skewness, kurtosis) of the MFC distribution were included in the review. The final yield from a search of seven electronic research databases was 12 unique articles that met all the inclusion criteria. Ageing does not appear to alter measures of central tendency or shape of the MFC distribution. However greater MFC variability was observed in older compared to younger adults and older fallers compared to older non-fallers in the majority of studies. Greater MFC variability may contribute to increased risk of trips and associated falls in older compared to young adults and older fallers compared to older non-fallers.

A machine learning approach to k-step look-ahead prediction of gait variables from acceleration data.

This paper investigates the use of machine learning to predict a sensitive gait parameter based on acceleration information from previous gait cycles. We investigate a k-step look-ahead prediction which attempts to predict gait variable values based on acceleration information in the current gait cycle. The variable is the minimum toe clearance which has been demonstrated to be a sensitive falls risk predictor. Toe clearance data was collected under normal walking conditions and 9 features consisting of peak acceleration and their normalized occurrences times were extracted. A standard least squares estimator, a generalized regression neural network (GRNN) and a support vector regressor (SVR) were trained using 60% of the data to estimate the minimum toe clearance and the remaining 40% was used to validate the model. It was found that when the training data contained data from all subjects (inter-subject) the best GRNN model provided a root mean square error (RMSE) of 2.8 mm, the best SVR had RMSE of 2.7 mm while the standard least squares linear regression method obtained 3.3 mm. When the training and test data consisted of different subject examples (inter-subject) data, the linear SVR demonstrated superior generalization capability (RMSE=3.3 mm) compared to other competing models. Validation accuracies up to 5-step look-ahead predictions revealed robust performances for both GRNN and SVR models with no clear degradation in prediction accuracy.

A prototype wireless inertial-sensing device for measuring toe clearance.

Tripping and slipping are serious health concerns for the elderly because they result in life threatening injuries i.e., fractures and high medical costs. Our recent work in detection of tripping gait patterns has demonstrated that minimum toe clearance (MTC) is a sensitive falls risk predictor. MTC measurement has previously been done in gait laboratories and on treadmills which potentially imposes controlled walking conditions. In this paper, we describe a prototype design of a wireless device for monitoring vertical toe clearance. The sensors consists of a tri-axis accelerometer and dual-axis gyroscope connected to Crossbow sensor motes for wireless data transmission. Sensor data are transmitted to a laptop and displayed on a Matlab graphic user interface (GUI). We have performed zero base and treadmill experiments to investigate sensor performance to environmental variations and compared the calculated toe clearance against measurements made by an Optotrak motion system. It was found that device outputs were approximately independent of small ambient temperature variations, had a reliable range of 20m indoors and 50m outdoors and a maximum transmission rate of 20 packets/s. Toe clearance measurements were found to follow the Optotrak measurement trend but could be improved further by dealing with double integration errors and improving data transmission rates.

Ageing effects on knee and ankle joint angles at key events and phases of the gait cycle.

The objective of this research was to determine whether joint angles at critical gait events and during major energy generation/absorption phases of the gait cycle would reliably discriminate age-related degeneration during unobstructed walking. The gaits of 24 healthy adults (12 young and 12 elderly) were analysed using the PEAK Motus motion analysis system. The elderly participants showed significantly greater single (60.3% versus 62.3%, p < 0.01) and double ( p < 0.05) support times, reduced knee flexion (47.7 degrees versus 43.0 degrees , p < 0.05) and ankle plantarflexion (16.8 degrees compared to 3.3 degrees , p = 0.053) at toe off, reduced knee flexion during push-off and reduced ankle dorsiflexion (16.8 degrees compared to 22.0 degrees , p < 0.05) during the swing phase. The plantarflexing ankle joint motion during the stance to swing phase transition (A2) for the young group (31.3 degrees ) was about twice ( p < 0.05) that of the elderly (16.9 degrees ). Reduced knee extension range of motion suggests that the elderly favoured a flexed-knee gait to assist in weight acceptance. Reduced dorsiflexion by the elderly in the swing phase implies greater risk of toe contact with obstacles. Overall, the results suggest that joint angle measures at critical events/phases in the gait cycle provide a useful indication of age-related degeneration in the control of lower limb trajectories during unobstructed walking.

Neural network-based prediction of missing key features in vertical GRF-time recordings.

Ground reaction force (GRF) time recordings are frequently corrupted due to faulty stepping on a force platform during gait, and this results in the loss of valuable data and the need for additional data acquisition. This paper proposes a new approach based on artificial neural networks for the estimation of lost key gait parameters using the available features of an affected GRF-time trace. GRF-time plots were recorded using a force platform during normal walking of 14 young and 13 elderly individuals. Back-propagation neural network models were developed using features extracted from 466 vertical GRF-time characteristics that would be unaffected as inputs, and the likely affected gait features (e.g. stance time (ST), push-off force, (Fmax2) and push-off time (Tmax2)) as output. Performance of the models in predicting ST, Fmax2 and Tmax2 were tested using data from 30 new gait trials. The neural network model predicted the missing STs with 96.5% (+/-2.6%) accuracy (r>0.9). Accuracy of the ST prediction deteriorated when push-off force/time data were unavailable for the prediction model. Fmax2 and its time were reconstructed with an accuracy of 95.7% (+/-2.8%) and 97.6% (+/-1.7%) respectively. These results suggest that an artificial neural network may be applied to estimate missing ST, Fmax2 or Tmax2 information using features from an affected vertical GRF-time plot, and the method shows good promise for reconstructing gait forces from a corrupted force-time trace.

Neural networks for detection and classification of walking pattern changes due to ageing.

With age, gait functions reflected in the walking patterns degenerate and threaten the balance control mechanisms of the locomotor system. The aim of this paper is to explore applications of artificial neural networks for automated recognition of gait changes due to ageing from their respective gait-pattern characteristics. The ability of such discrimination has many advantages including the identification of at-risk or faulty gait. Various gait features (e.g., temporal-spatial, foot-ground reaction forces and lower limb joint angular data) were extracted from 12 young and 12 elderly participants during normal walking and these were utilized for training and testing on three neural network algorithms (Standard Backpropagation: Scaled Conjugate Gradient; and Backpropagation with Bayesian Regularization, BR). Receiver operating characteristics plots, sensitivity and specificity results as well as accuracy rates were used to evaluate performance of the three classifiers. Cross-validation test results indicate a maximum generalization performance of 83.3% in the recognition of the young and elderly gait patterns. Out of the three neural network algorithms, BR performed superiorly in the test results with best sensitivity, selectivity and detection rates. With the help of a feature selection technique, the maximum classification accuracy of the BR attained 100%, when trained with a small subset of selected gait features. The results of this study demonstrate the capability of neural networks in the detection of gait changes with ageing and their potentials for future applications as gait diagnostics.

A machine learning approach for automated recognition of movement patterns using basic, kinetic and kinematic gait data.

This paper investigated application of a machine learning approach (Support vector machine, SVM) for the automatic recognition of gait changes due to ageing using three types of gait measures: basic temporal/spatial, kinetic and kinematic. The gaits of 12 young and 12 elderly participants were recorded and analysed using a synchronized PEAK motion analysis system and a force platform during normal walking. Altogether, 24 gait features describing the three types of gait characteristics were extracted for developing gait recognition models and later testing of generalization performance. Test results indicated an overall accuracy of 91.7% by the SVM in its capacity to distinguish the two gait patterns. The classification ability of the SVM was found to be unaffected across six kernel functions (linear, polynomial, radial basis, exponential radial basis, multi-layer perceptron and spline). Gait recognition rate improved when features were selected from different gait data type. A feature selection algorithm demonstrated that as little as three gait features, one selected from each data type, could effectively distinguish the age groups with 100% accuracy. These results demonstrate considerable potential in applying SVMs in gait classification for many applications.

Gait characteristics of young and older individuals negotiating a raised surface: implications for the prevention of falls.

BACKGROUND: Falls in older individuals are a major public health issue because of the financial cost of surgery and re habilitation and the human cost of associated pain and disability. Older individuals are most likely to fall when negotiating an obstacle or obstruction during locomotion. This research was aimed at investigating lower limb motion while a subject negotiated a raised surface. METHODS: The gait of six healthy young (Y) women (mean age 23.1 years) and six healthy older (O) women (mean age 67.6 years) were analyzed with a PEAK motion analyzer and a dual-force-platform system during unobstructed walking and when the subjects were stepping on and off a raised surface of 15 cm. The effect of age on foot clearance and force platform variables was analyzed. RESULTS: During stepping on, the young women cleared the step by the lead foot by a significantly greater margin than the older subjects did (Y = 10.6 cm, O = 9.1 cm; p < .05) but trail-foot clearance was not significantly different (Y 9.4 cm, O = 8.8 cm). Foot clearance in stepping off was low compared with that of ascent, and the older individuals had a significantly higher lead (Y = 1.5 cm, O = 3.3 cm, p < .05) and trail (Y = 1.0 cm, O = 2.1 cm) vertical clearance. Older individuals positioned both the lead and the trail foot relatively farther from the step edge on ascending a raised surface, respectively, Y = 87% and O = 93% of the step cycle and Y = 29% and O = 34%. Foot placement in descent was qualitatively similar for the two groups. The force and the impulse data under the lead and the trail feet confirm modulations consistent with the foot clearance data. CONCLUSION: In negotiating a raised surface older individuals appear to use a nonoptimal foot placement strategy in which, compared with that of young subjects, the trail foot is placed a long way from the edge of the step. The older subjects allowed very little correction time and little latitude in foot placement beyond the edge of the step, suggesting that the approach to the obstacle may be a critical determinant of safety.

A method for the reconstruction of ground reaction force-time characteristics during gait from force platform recordings of simultaneous foot falls.

This paper proposes a method for the reconstruction of foot-ground reaction forces from force platform recordings of two consecutive footfalls. The reconstruction algorithm uses zero-derivative criterion (inflection point) to detect contralateral foot contacts and subtracts contralateral forces from the combined force-time curve in order to reconstruct force-time data. Experimental results suggest that the method can be applied to separate accurately foot-specific gait forces from corrupted force-time data as a result of incorrect stepping on a force platform.

A lateral cephalometric analysis of the adult nose.

PURPOSE: The purpose of this study was to establish a set of standard values for the form of the nose and its relationship to other craniofacial structures in young adult caucasians. SUBJECTS AND METHODS: The subjects were 50 (25 male, 25 female) caucasian dental students who gave no history of orthodontic treatment, facial surgery, or facial fractures. Lateral cephalometric radiographs were used to determine the form of the nose and its position relative to other craniofacial structures. RESULTS: The men had significantly longer and straighter noses than the women, and their noses also projected further from the face. The dorsum of the nose was straight in most subjects. The vertical distances from the tip of the nose to the most prominent part of the upper lip, to the incisal edge of the maxillary central incisor, and to soft tissue pogonion were significantly greater in the men. There were no gender differences in the horizontal distances between the same points and the tip of the nose. Subnasale was significantly more prominent in the men. CONCLUSIONS: In general, the findings of nasal form and position are in agreement with previous studies. Several gender differences in nasal form and position were found. The standards reported should prove to be a useful yardstick for clinicians engaged in procedures likely to alter the form of the adult human face.

Microcomputer-based system for clinical gait studies.

A microcomputer-based gait recording system is described which can be used to analyse gait routinely in the clinical environment. Foot-ground reaction forces are acquired and processed and the resultant force vector is superimposed on the television image of the subject in real time. A TV-computer interface quantifies the position of reflective markers attached to the joint centres of the lower limb, and moment values, stick-figure diagrams, and joint angle changes can also be displayed shortly after data collection. The system has routine clinical applications in orthotics and prosthetics and is also a valuable tool in teaching the biomechanics of human movement.

A microcomputer-based video vector system for clinical gait analysis.

A microcomputer-based video vector system has been developed to display the resultant ground reaction force vector on a television image of the subject in real-time. For each television field the force platform signals are acquired and processed and the resultant force vector superimposed on the video image of the walking subject. The force platform results are stored on disc and the composite video signals recorded on video tape for further analysis. The system is easy to set up and use and the results can be readily interpreted. The external moments produced at the joint centers by the ground reaction forces can be observed visually and, if required, quantification of the external moments can be achieved following data collection. The spatial resolution of the system is 0.342% vertically and 0.156% horizontally. The force vector visualization technique has routine applications in orthotics and prosthetics. It is also a useful technique for the teaching of biomechanics.

Does bupivacaine irrigation of third molar sockets reduce postoperative pain? A double blind controlled trial.

A double blind controlled randomised trial suggested that irrigation of third molar sockets with bupivacaine 0.75% produces significant reduction in pain scored on the first post-operative morning (p less than 0.01). However, this technique produces no significant reduction in opiate or oral analgesic consumption.

Instrumentation used in clinical gait studies: a review.

This paper reviews the currently available instrumentation used for gait studies and discusses the clinical suitability of the various methods of recording gait parameters. Most of the presently available motion analysis systems appear to be more suited to research than to the routine clinical situation. However the video vector visualization technique appears to be the most useful clinically since it produces a real time display, is simple to operate and interpretation of the data is easier than other systems available. Some further development of the video vector visualization system is necessary to improve its accuracy and to produce quantitative information.

Cholesterol emboli after cardiac catheterization. Eight cases and a review of the literature.

Cholesterol embolization is a puzzling event that may be increasingly iatrogenic in origin. Diagnosis is difficult and requires a high index of suspicion, an appropriate clinical picture, and usually, confirmation by biopsy. Certain laboratory abnormalities may be helpful; the elevated sedimentation rate and relative eosinophilia found in our patients concurs with other cases reported in the literature. Prognosis is related to the extent of systemic involvement, but renal disease is particularly threatening and gangrene and infection can be lethal. Multiple therapeutic regimens have been generally unsuccessful in altering the course of the disease process. The most significant impact on the disease can be made by its prevention. Cholesterol emboli occur spontaneously, but also after invasive aortic procedures such as diagnostic angiography or cardiovascular surgery. In addition, cardiac catheterization and percutaneous transluminal coronary angioplasty have the potential for arterial trauma and consequent cholesterol embolization. Although the apparent increasing numbers of cholesterol emboli may be a reflection of the increased use of arterial invasive procedures, they are being performed on an older, more severely ill population, with other risk factors for the development of embolic phenomena, i.e., age, smoking history, diabetes mellitus, hypertension, and peripheral vascular disease. Our observed cases and review of the literature do not furnish information concerning the comparative incidences of embolization as related to the suggested etiologies. Careful documentation of the clinical situation preceding the event, the type of procedure, the site of arterial entry, and the duration, difficulty, and extent of the intravascular invasion (i.e., above or below the left subclavian artery) are necessary for this purpose. Such data should help to develop guidelines for patient and procedure selection in order to minimize the possibility of cholesterol embolization.