Lisa M. Stirling

Discrimination of gender-, speed-, and shoe-dependent movement patterns in runners using full-body kinematics.

Changes in gait kinematics have often been analyzed using pattern recognition methods such as principal component analysis (PCA). It is usually just the first few principal components that are analyzed, because they describe the main variability within a dataset and thus represent the main movement patterns. However, while subtle changes in gait pattern (for instance, due to different footwear) may not change main movement patterns, they may affect movements represented by higher principal components. This study was designed to test two hypotheses: (1) speed and gender differences can be observed in the first principal components, and (2) small interventions such as changing footwear change the gait characteristics of higher principal components. Kinematic changes due to different running conditions (speed - 3.1m/s and 4.9 m/s, gender, and footwear - control shoe and adidas MicroBounce shoe) were investigated by applying PCA and support vector machine (SVM) to a full-body reflective marker setup. Differences in speed changed the basic movement pattern, as was reflected by a change in the time-dependent coefficient derived from the first principal. Gender was differentiated by using the time-dependent coefficient derived from intermediate principal components. (Intermediate principal components are characterized by limb rotations of the thigh and shank.) Different shoe conditions were identified in higher principal components. This study showed that different interventions can be analyzed using a full-body kinematic approach. Within the well-defined vector space spanned by the data of all subjects, higher principal components should also be considered because these components show the differences that result from small interventions such as footwear changes.

Flexibility, muscle strength and running biomechanical adaptations in older runners.

BACKGROUND The increased injury risk in older runners has been associated with alterations in muscle strength, flexibility, and gait biomechanics. This study investigated whether older runners exhibit changes in muscle strength, flexibility and running biomechanics compared to younger runners, and possible relationships between these changes. METHODS Thirty-five young (20-36yrs) and 35 older (55-71yrs) recreational runners participated in the study. Measures of three-dimensional biomechanical data during treadmill running at 2.7m/s and measures of muscle strength and flexibility were compared between groups. A correlation analysis between biomechanical and clinical variables was also performed. FINDINGS Older runners demonstrated an overall reduction in muscle strength and flexibility, and altered running patterns compared to young runners but correlations between clinical and biomechanical variables were scarce. Reduced hip, ankle and trunk excursions along with reduced knee and ankle positive work were found in older runners. Older runners also exhibited increased knee abduction impulse, ankle abduction impulse and vertical loading rates. In contrast, older runners did not present a distal-to-proximal lower extremity joint moment redistribution. INTERPRETATION We observed age-related reduced strength and flexibility concomitant with alterations in running biomechanics, but a lack of correlation between these variables. This finding hampers the use of single, or even a subset of characteristics to better understand age-related changes in runners. The observed changes are complex and multivariate in nature. Clinicians will most likely have to monitor both clinical and biomechanical characteristics to optimize care. However, future studies need to prospectively address what are biomechanical age-related risk factors in runners.

Tissue vibration in prolonged running

The impact force in heel-toe running initiates vibrations of soft-tissue compartments of the leg that are heavily dampened by muscle activity. This study investigated if the damping and frequency of these soft-tissue vibrations are affected by fatigue, which was categorized by the time into an exhaustive exercise. The hypotheses were tested that (H1) the vibration intensity of the triceps surae increases with increasing fatigue and (H2) the vibration frequency of the triceps surae decreases with increasing fatigue. Tissue vibrations of the triceps surae were measured with tri-axial accelerometers in 10 subjects during a run towards exhaustion. The frequency content was quantified with power spectra and wavelet analysis. Maxima of local vibration intensities were compared between the non-fatigued and fatigued states of all subjects. In axial (i.e. parallel to the tibia) and medio-lateral direction, most local maxima increased with fatigue (supporting the first hypothesis). In anterior-posterior direction no systematic changes were found. Vibration frequency was minimally affected by fatigue and frequency changes did not occur systematically, which requires the rejection of the second hypothesis. Relative to heel-strike, the maximum vibration intensity occurred significantly later in the fatigued condition in all three directions. With fatigue, the soft tissue of the triceps surae oscillated for an extended duration at increased vibration magnitudes, possibly due to the effects of fatigue on type II muscle fibers. Thus, the protective mechanism of muscle tuning seems to be reduced in a fatigued muscle and the risk of potential harm to the tissue may increase.

Piper rhythm of the electromyograms of the abductor pollicis brevis muscle during isometric contractions

A temporal pattern coding, synchronization and rhythmicity form an integral part of central nervous system information controlling the muscle activation. Rhythmic oscillations of muscles at frequencies of 35-60 Hz were already noted in the electromyograms by Piper (1907). The purpose of this study was to resolve the Piper rhythm in the EMG of the APB muscle and report the pacing frequencies of the Piper rhythm. The Piper rhythm was identified using the power of the EMG signals extracted by a wavelet transform at higher frequencies (170-271 Hz). The results showed distinct power of the intensity extracted by the wavelets in a frequency band ranging from about 30-60 Hz. The band was reflected in the power spectra of the EMG intensity and in the first eigenvector of a principal component analysis of the power spectra. The fact that the Piper rhythm shown in this study for the APB muscle yielded a large contribution to the total power means that one can use the frequency and amplitude of the Piper rhythm in future analysis of EMG signals to monitor the influence and changes of the central command.

Classification of muscle activity based on effort level during constant pace running.

During running, psychologic and physiologic changes are manifested in the perception of effort, muscle properties and movement strategies. The latter two aspects are expressed as changes in electromyographic (EMG) activity. This paper tests the hypothesis that the EMG signals change in a systematic way during a run and that these changes are related to the effort level of the runner. Fifteen female recreational runners performed 1-h treadmill runs at a constant speed (95% of speed at ventilatory threshold). EMG signals were recorded from four muscles (tibialis anterior, gastrocnemius medialis, vastus lateralis, and semitendinosus). The wavelet transformed EMG data were used to discriminate between different effort phases of running using a support vector machine (SVM) approach. The effect of the penalty parameter, C, and cross validation folds, n, used were evaluated and found to have little influence on the outcome. Recognition rates of >80% were achieved for all C and n values across all muscles. Average recognition rates were: TA - 89.2, GM - 88.3%, VL - 84.6% and ST - 94.0%. These results suggest that selected lower extremity EMG signals using wavelet-based methods contained highly systematic differences that could be used by the SVM to discriminate between the low- and high-effort stages of prolonged running.

Fatigue-related decrease in Piper rhythm frequency of the abductor pollicis brevis muscle during isometric contractions

The purpose of this study was to analyze how the frequency of the Piper rhythm of the abductor pollicis brevis muscle (APB) and thus of the rhythmic synchronization of motor units changes with fatigue. Fourteen subjects participated in the study. The EMG signals were measured during maximum voluntary contractions, and a mimicked motor unit action potential was used to simulate an EMG signal containing no rhythmicity. The simulated EMG was used as a reference. The Piper rhythm was extracted from the high frequency power (170-271 Hz) of the wavelet transformed real and simulated EMG data using the difference of the autocorrelation functions of the power. The study shows that the Piper rhythm of the APB muscle, its pacing frequency and pacing amplitude can be extracted from the EMG signal recorded during a fatiguing task. One can conclude that the pacing frequencies observed in various hands covered the whole frequency range of the Piper band which includes the beta and the gamma band frequencies observed in brain activity (17-60 Hz). While the pacing frequency decreased with fatigue the pacing amplitude did not change significantly. The Piper rhythm is a result of a changing central drive and its measurement thus allows observing changes of central drive to the muscle. The ability to better resolve the Piper rhythm in the EMG without using the coherence with the brain activity opens the possibility to study the behavior of central control in the peripheral signal.

Piper rhythm in the activation of the gastrocnemius medialis during running.

The presence of temporal rhythmicity in electromyographic (EMG) signals at frequencies of 35-60 Hz was initially noted by Piper (1907). This modulation and synchronization of motor unit activity is generally accepted to represent a centrally generated coding of motor commands. The purpose of this study was to resolve and quantify the Piper rhythm in the gastrocnemius medialis (GM) muscle during running. EMG was recorded from the GM of 14 female runners during 1-h treadmill runs. The average wavelet transform was computed for EMG from series of steps taken at 2 min intervals throughout the run. The total intensity across three wavelets (center frequencies: 170, 218 and 271 Hz) was computed and a histogram indicating the incidence peaks in this signal was generated for each subject. In order to rule out effects of the analysis process, the process was repeated using simulated EMG data. Autocorrelations of the histograms were used to extract the frequency of the peaks resulting in rhythmicity at 25-55 Hz. The ability to measure superimposed rhythmicity in EMG signals during dynamic tasks allows investigation of the role of aspects of central drive during movement. In particular, the changes in central control during dynamic activities can be examined with this approach.

Data preprocessing for distance-based unsupervised Intrusion Detection

Since Intrusion Detection Systems (IDSs) operate in real-time, they should be light-weighted to detect intrusions as fast as possible. Distance-based Outlier Detection (DBOD) is one of the most widely-used techniques for detecting outliers due to its simplicity and efficiency. Additionally, DBOD is an unsupervised approach which overcomes the problem of the lack of training datasets with known intrusions. However, since IDSs usually have high-dimensional datasets, using DBOD becomes subject to the curse of the dimensionality problem. Furthermore, intrusion datasets should be normalized before calculating pair-wise distance between observations. The purpose of this research is conduct a comparative study among different normalization methods in conjunction with a well-known feature extraction technique; Principle Component Analysis (PCA). Therefore, the efficiency of these methods as data preprocessing techniques can be investigated when applying DBOD to detect intrusions. Experiments were performed using two kinds of distance metrics; Euclidean distance and Mahalanobis distance. We further examined the PCA using 7 threshold values to indicate the number of Principle components to consider according to their total contribution in the variability of features. These approaches have been evaluated using the KDD Cup 1999 intrusion detection (KDD-Cup) dataset. The main purpose of this study is to find the best attribute normalization method along with the correct threshold value for PCA so that a fast unsupervised IDS can discover intrusions effectively. The results recommended using the Log normalization method combined the Euclidean distance while performing PCA.

Quantification of the manifestations of fatigue during treadmill running

Abstract During whole-body exercise, fatigue is difficult to quantify; however, changes to mechanical, physiological and psychological systems during exercise are associated with the development of fatigue. To quantify fatigue, one must therefore assess changes occurring in these variables. The purpose of this study was to demonstrate a method to assign weightings to selected variables and to combine them into a single value quantifying changes occurring during exercise. Twelve female recreational runners performed one hour of treadmill running, during which heart rate, respiration rate, stride frequency and six selected psychological variables were collected at defined intervals throughout the run. Data were normalised and a principle component analysis was performed. The resulting first eigenvector was termed the “contribution vector” and indicated the weighting of each variable towards the global exercise-induced changes in the body. The projection of data onto the contribution vector resulted in a value described as the “fatigue index”. An assessment of the generalisation of the method to new data was performed using a leave-one-out cross-validation procedure and indicated that the index is accurate to within 3.01% of the maximum index value measured. The method developed here has the advantage over current methods due to its multifactorial, causal and customisable nature.

Effects of strengthening and stretching exercise programmes on kinematics and kinetics of running in older adults: a randomised controlled trial

ABSTRACT The aim of this study was to investigate the effects of strengthening and stretching exercises on running kinematics and kinetics in older runners. One hundred and five runners (55–75 years) were randomly assigned to either a strengthening (n = 36), flexibility (n = 34) or control (n = 35) group. Running kinematics and kinetics were obtained using an eight-camera system and an instrumented treadmill before and after the eight-week exercise protocol. Measures of strength and flexibility were also obtained using a dynamometer and inclinometer/goniometer. A time effect was observed for the excursion angles of the ankle sagittal (P = 0.004, d = 0.17) and thorax/pelvis transverse (P < 0.001, d = 0.20) plane. Similarly, a time effect was observed for knee transverse plane impulse (P = 0.013, d = 0.26) and ground reaction force propulsion (P = 0.042, d = −0.15). A time effect for hip adduction (P = 0.006, d = 0.69), ankle dorsiflexion (P = 0.002, d = 0.47) and hip internal rotation (P = 0.048, d = 0.30) flexibility, and hip extensor (P = 0.001, d = −0.48) and ankle plantar flexor (P = 0.01, d = 0.39) strength were also observed. However, these changes were irrespective of exercise group. The results of the present study indicate that an eight-week stretching or strengthening protocol, compared to controls, was not effective in altering age-related running biomechanics despite changes in ankle and trunk kinematics, knee kinetics and ground reaction forces along with alterations in muscle strength and flexibility were observed over time.