The effect of stride length on the dynamics of barefoot and shod running

A number of interventions and technique changes have been proposed to attempt to improve performance and reduce the number of running related injuries. Running shoes, barefoot running and alterations in spatio-temporal parameters (stride frequency and stride length) have been associated with significant kinematic and kinetic changes, which may have implications for performance and injury prevention. However, because footwear interventions have been shown to also affect spatio-temporal parameters, there is uncertainty regarding the origin of the kinematic and kinetic alterations. Therefore, the purpose of this study was to independently evaluate the effects of shoes and changes in stride length on lower extremity kinetics. Eleven individuals ran over-ground at stride lengths ±5 and 10% of their preferred stride length, in both the barefoot and shod condition. Three-dimensional motion capture and force plate data were captured synchronously and used to compute lower extremity joint moments. We found a significant main effect of stride length on anterior–posterior and vertical GRFs, and sagittal plane knee and ankle moments in both barefoot and shod running. When subjects ran at identical stride lengths in the barefoot and shod conditions we did not observe differences for any of the kinetic variables that were measured. These findings suggest that barefoot running triggers a decrease in stride length, which could lead to a decrease in GRFs and sagittal plane joint moments. When evaluating barefoot running as a potential option to reduce injury, it is important to consider the associated change in stride length.     

Estimation of hurdle clearance parameters using a monocular human motion tracking method

This paper presents a method of monocular human motion tracking for estimation of hurdle clearance kinematic parameters. The analysis involved 10 image sequences of five hurdlers at various training levels. Recording of the sequences was carried out under simulated starting conditions of a 110 m hurdle race. The parameters were estimated using the particle swarm optimization algorithm and they are based on analysis of the images recorded with a 100 Hz camera. The proposed method does not involve using any special clothes, markers, inertial sensors, etc. As the quality criteria, the mean absolute error and mean relative error were used. The level of computed errors justifies the use of this method to estimate hurdle clearance parameters.     

A comparison of algorithms for body-worn sensor-based spatiotemporal gait parameters to the GAITRite electronic walkway

This study compares the performance of algorithms for body-worn sensors used with a spatiotemporal gait analysis platform to the GAITRite electronic walkway. The mean error in detection time (true error) for heel strike and toe-off was 33.9 ± 10.4 ms and 3.8 ± 28.7 ms, respectively. The ICC for temporal parameters step, stride, swing and stance time was found to be greater than 0.84, indicating good agreement. Similarly, for spatial gait parameters--stride length and velocity--the ICC was found to be greater than 0.88. Results show good to excellent concurrent validity in spatiotemporal gait parameters, at three different walking speeds (best agreement observed at normal walking speed). The reported algorithms for body-worn sensors are comparable to the GAITRite electronic walkway for measurement of spatiotemporal gait parameters in healthy subjects.     

Ambulatory estimation of foot placement during walking using inertial sensors

This study proposes a method to assess foot placement during walking using an ambulatory measurement system consisting of orthopaedic sandals equipped with force/moment sensors and inertial sensors (accelerometers and gyroscopes). Two parameters, lateral foot placement (LFP) and stride length (SL), were estimated for each foot separately during walking with eyes open (EO), and with eyes closed (EC) to analyze if the ambulatory system was able to discriminate between different walking conditions. For validation, the ambulatory measurement system was compared to a reference optical position measurement system (Optotrak). LFP and SL were obtained by integration of inertial sensor signals. To reduce the drift caused by integration, LFP and SL were defined with respect to an average walking path using a predefined number of strides. By varying this number of strides, it was shown that LFP and SL could be best estimated using three consecutive strides. LFP and SL estimated from the instrumented shoe signals and with the reference system showed good correspondence as indicated by the RMS difference between both measurement systems being 6.5±1.0 mm (mean ±standard deviation) for LFP, and 34.1±2.7 mm for SL. Additionally, a statistical analysis revealed that the ambulatory system was able to discriminate between the EO and EC condition, like the reference system. It is concluded that the ambulatory measurement system was able to reliably estimate foot placement during walking.     

Kinematics of running at different slopes and speeds

The aim of this study was to verify the influence of the combination of different running speeds and slopes based on main kinematic parameters in both groups of elite (RE) and amateur (RA) marathon runners. All subjects performed various tests on a treadmill at 0, 2, and 7% slopes at different speeds: 3.89, 4.17, 4.44, 4.72, and 5.00 m·s. A high speed digital camera, 210 Hz, has been used to record; Dartfish 5.5Pro has been used to perform a 2D video analysis. Step length (SL), step frequency (SF), flight time (FT), and contact time (CT) were determined and used for comparison. SL, SF, and FT parameters increased, and CT parameter decreased as speed increased. As slopes increased, SL and FT decreased and SF increased in both groups and only CT decreased in RE, whereas in RA, it increased. Data were fitted to the linear regression line (R > 0.95). The 2 groups were significantly different (p < 0.05) in FT, SL, and SF at all speeds in level running. A significant difference between the 2 groups was found in FT at 2 and 7% slopes at all speeds (p < 0.05). Percentage alterations in all variables were greater in the RA group. In conclusion, the choice of optimum SL and SF, through efficient running can be maintained, is influenced not only by speed but also by slopes. Elite runners perform more efficiently than amateur runners who have less experience.     

Determination of toe-off event time during treadmill locomotion using kinematic data

Researchers collecting gait kinematic data during treadmill locomotion are often interested in determining the times of toe off and heel strike for each stride. In the absence of additional hardware, only position data collected with motion-capture equipment may be available. Others have published methods for using kinematic data for detecting overground gait events. However, during treadmill locomotion, especially running, overground methods may not possess sufficient accuracy. The purpose of this paper is to describe a method for using kinematic data to determine the time of toe off during treadmill locomotion. Ten subjects walked and ran on a treadmill while a motion-capture system collected positional data from heel and toe markers. The treadmill was equipped with force platforms that allowed an accurate determination of foot-ground contact. The time of toe off was determined using the vertical component of the toe marker, and this method was found to have greater accuracy for event detection than other published methods. Researchers can use the described method to determine times of heel strike and toe off during treadmill locomotion using only kinematic data.     

Estimation of stride length in level walking using an inertial measurement unit attached to the foot: a validation of the zero velocity assumption during stance

In a variety of applications, inertial sensors are used to estimate spatial parameters by double integrating over time their coordinate acceleration components. In human movement applications, the drift inherent to the accelerometer signals is often reduced by exploiting the cyclical nature of gait and under the hypothesis that the velocity of the sensor is zero at some point in stance. In this study, the validity of the latter hypothesis was investigated by determining the minimum velocity of progression of selected points of the foot and shank during the stance phase of the gait cycle while walking at three different speeds on level ground. The errors affecting the accuracy of the stride length estimation resulting from assuming a zero velocity at the beginning of the integration interval were evaluated on twenty healthy subjects. Results showed that the minimum velocity of the selected points on the foot and shank increased as gait speed increased. Whereas the average minimum velocity of the foot locations was lower than 0.011 m/s, the velocity of the shank locations were up to 0.049 m/s corresponding to a percent error of the stride length equal to 3.3%. The preferable foot locations for an inertial sensor resulted to be the calcaneus and the lateral aspect of the rearfoot. In estimating the stride length, the hypothesis that the velocity of the sensor can be set to zero sometimes during stance is acceptable only if the sensor is attached to the foot.     

Frailty assessment based on wavelet analysis during quiet standing balance test

BackgroundA standard phenotype of frailty was independently associated with an increased risk of adverse outcomes including comorbidity, disability and with increased risks of subsequent falls and fractures. Postural control deficit measurement during quiet standing has been often used to assess balance and fall risk in elderly frail population. Real time human motion tracking is an accurate, inexpensive and portable system to obtain kinematic and kinetic measurements. The aim of this study was to examine orientation and acceleration signals from a tri-axial inertial magnetic sensor during quiet standing balance tests using the wavelet transform in a frail, a prefail and a healthy population.MethodsFourteen subjects from a frail population (79±4 years), eighteen subjects from a prefrail population (80±3 years) and twenty four subjects from a healthy population (40±3 years) volunteered to participate in this study. All signals were analyzed using time–frequency information based on wavelet decomposition and principal component analysis.FindingsThe absolute sum of the coefficients of the wavelet details corresponding to the high frequencies component of orientation and acceleration signals were associated with frail syndrome.InterpretationThese parameters could be of great interest in clinical settings and improved rehabilitation therapies and in methods for identifying elderly population with frail syndrome.     

Estimation of temporal parameters during sprint running using a trunk-mounted inertial measurement unit

The purpose of this study was to identify consistent features in the signals supplied by a single inertial measurement unit (IMU), or thereof derived, for the identification of foot-strike and foot-off instants of time and for the estimation of stance and stride duration during the maintenance phase of sprint running. Maximal sprint runs were performed on tartan tracks by five amateur and six elite athletes, and durations derived from the IMU data were validated using force platforms and a high-speed video camera, respectively, for the two groups. The IMU was positioned on the lower back trunk (L1 level) of each athlete. The magnitudes of the acceleration and angular velocity vectors measured by the IMU, as well as their wavelet-mediated first and second derivatives were computed, and features related to foot-strike and foot-off events sought. No consistent features were found on the acceleration signal or on its first and second derivatives. Conversely, the foot-strike and foot-off events could be identified from features exhibited by the second derivative of the angular velocity magnitude. An average absolute difference of 0.005 s was found between IMU and reference estimates, for both stance and stride duration and for both amateur and elite athletes. The 95% limits of agreement of this difference were less than 0.025 s. The results proved that a single, trunk-mounted IMU is suitable to estimate stance and stride duration during sprint running, providing the opportunity to collect information in the field, without constraining or limiting athletes' and coaches' activities.     

A simple field method to identify foot strike pattern during running

Identifying foot strike patterns in running is an important issue for sport clinicians, coaches and footwear industrials. Current methods allow the monitoring of either many steps in laboratory conditions or only a few steps in the field. Because measuring running biomechanics during actual practice is critical, our purpose is to validate a method aiming at identifying foot strike patterns during continuous field measurements. Based on heel and metatarsal accelerations, this method requires two uniaxial accelerometers. The time between heel and metatarsal acceleration peaks (THM) was compared to the foot strike angle in the sagittal plane (α_foot) obtained by 2D video analysis for various conditions of speed, slope, footwear, foot strike and state of fatigue. Acceleration and kinematic measurements were performed at 1000 Hz and 120 Hz, respectively, during 2-min treadmill running bouts. Significant correlations were observed between THM and α_foot for 14 out of 15 conditions. The overall correlation coefficient was r=0.916 (P<0.0001, n=288). The THM method is thus highly reliable for a wide range of speeds and slopes, and for all types of foot strike except for extreme forefoot strike during which the heel rarely or never strikes the ground, and for different footwears and states of fatigue. We proposed a classification based on THM: FFS<−5.49 ms<MFS<15.2 ms<RFS. With only a few precautions being necessary to ensure appropriate use of this method, it is reliable for distinguishing rearfoot and non-rearfoot strikers in situ.     

Quantification of gait parameters with inertial sensors and inverse kinematics

Measuring human gait is important in medicine to obtain outcome parameter for therapy, for instance in Parkinson’s disease. Recently, small inertial sensors became available which allow for the registration of limb-position outside of the limited space of gait laboratories. The computation of gait parameters based on such recordings has been the subject of many scientific papers. We want to add to this knowledge by presenting a 4-segment leg model which is based on inverse kinematic and Kalman filtering of data from inertial sensors. To evaluate the model, data from four leg segments (shanks and thighs) were recorded synchronously with accelerometers and gyroscopes and a 3D motion capture system while subjects (n = 12) walked at three different velocities on a treadmill. Angular position of leg segments was computed from accelerometers and gyroscopes by Kalman filtering and compared to data from the motion capture system. The four-segment leg model takes the stance foot as a pivotal point and computes the position of the remaining segments as a kinematic chain (inverse kinematics). Second, we evaluated the contribution of pelvic movements to the model and evaluated a five segment model (shanks, thighs and pelvis) against ground-truth data from the motion capture system and the path of the treadmill.ResultsWe found the precision of the Kalman filtered angular position is in the range of 2–6° (RMS error). The 4-segment leg model computed stride length and length of gait path with a constant undershoot of 3% for slow and 7% for fast gait. The integration of a 5th segment (pelvis) into the model increased its precision. The advantages of this model and ideas for further improvements are discussed.     

Intra-rater repeatability of gait parameters in healthy adults during self-paced treadmill-based virtual reality walking

Self-paced treadmill walking is becoming increasingly popular for the gait assessment and re-education, in both research and clinical settings. Its day-to-day repeatability is yet to be established. This study scrutinised the test-retest repeatability of key gait parameters, obtained from the Gait Real-time Analysis Interactive Lab (GRAIL) system. Twenty-three male able-bodied adults (age: 34.56 ± 5.12 years) completed two separate gait assessments on the GRAIL system, separated by 5 ± 3 days. Key gait kinematic, kinetic, and spatial-temporal parameters were analysed. The Intraclass-Correlation Coefficients (ICC), Standard Error Measurement (SEM), Minimum Detectable Change (MDC), and the 95% limits of agreements were calculated to evaluate the repeatability of these gait parameters. Day-to-day agreements were excellent (ICCs > 0.87) for spatial-temporal parameters with low MDC and SEM values, <0.153 and <0.055, respectively. The repeatability was higher for joint kinetic than kinematic parameters, as reflected in small values of SEM (<0.13 Nm/kg and <3.4°) and MDC (<0.335 Nm/kg and <9.44°). The obtained values of all parameters fell within the 95% limits of agreement. Our findings demonstrate the repeatability of the GRAIL system available in our laboratory. The SEM and MDC values can be used to assist researchers and clinicians to distinguish ‘real’ changes in gait performance over time.     

Non-linear changes of lower extremity kinetics prior to gait transition

IntroductionThe purpose of this study was to examine the changes of lower extremity kinetics during walk-to-run (WR) transition and if the changes would follow a non-linear trend within the five strides before WR transition using a constant acceleration protocol.MethodsFourteen participants performed gait transition on the instrumented treadmill at a constant acceleration. Peak, time to peak, and movement and power of hip, knee and ankle joints were recorded and analyzed in sagittal plane for five strides before gait transition. Three Two-way MANOVA were employed to examine the differences of kinetic measures among the five strides. Univariate analysis and Post-Hoc Tukey’s test would be applied if needed. Also, Post hoc polynomial trend analyses were used to examine the trend of the kinetic measures that significantly changed during the five strides.ResultsCompared to the first four strides, significant differences were observed for peaks moments, joint powers, and time to peaks in the last stride before running at ankle, knee, and hip joints respectively. In general, the changes of kinetic variables were following a quadratic trend during the five strides before running.ConclusionJoint kinetic measures actively change in non-linear patterns during the five strides before running to prepare for the gait transition, indicating that the gait transition is an active reorganization rather than a passive reaction.     

Adaptive changes in running kinematics as a function of head stability demands and their effect on shock transmission

This study aimed to identify adaptive changes in running kinematics and impact shock transmission as a function of head stability requirements. Fifteen strides from twelve recreational runners were collected during preferred speed treadmill running. Head stability demands were manipulated through real-time visual feedback that required head-gaze orientation to maintain within boxes of different sizes, ranging from 21° to 3° of visual angle with 3° decrements. The main outcome measures were tibial and head peak accelerations in the time and frequency domains (impact and active phases), shock transmission from tibia to head, stride parameters, and sagittal plane joint kinematics. Increasing head stability requirements resulted in decreases in the amplitude and integrated power of head acceleration during the active phase of stance. During the impact portion of stance tibial and head acceleration and shock transmission remained similar across visual conditions. In response to increased head stability requirements, participants increased stride frequency approximately 8% above preferred, as well as hip flexion angle at impact; stance time and knee and ankle joint angles at impact did not change. Changes in lower limb joint configurations (smaller hip extension and ankle plantar-flexion and greater knee flexion) occurred at toe-off and likely contributed to reducing the vertical displacement of the center of mass with increased head stability demands. These adaptive changes in the lower limb enabled runners to increase the time that voluntary control is allowed without embedding additional impact loadings, and therefore active control of the head orientation was facilitated in response to different visual task constraints.     

Agreement between spatiotemporal parameters from a photoelectric system with different filter settings and high-speed video analysis during running on a treadmill at comfortable velocity

The aim of this study was to determine the level of agreement between spatiotemporal gait characteristics from a photoelectric system with different filter settings and high-speed video analysis during running on a treadmill at comfortable velocity. Forty-nine runners performed a running protocol on a treadmill at comfortable velocity. Two systems were used to determine spatiotemporal parameters (i.e. contact time [CT], flight time [FT], step frequency [SF] and step length [SL]) during running: OptoGait system and high-speed video analysis at 1000 Hz. The collected data was re-filtered in the OptoGait software by using nine different settings (i.e. 0_0, 1_1, 2_2, 3_3, 3_4, 4_4, 4_5, 5_4 and 5_5), and compared to those obtained through video analysis. The Pearson correlation analysis revealed very large correlations (r > 0.9, p < 0.001) in CT, FT, SF and SL between both systems, regardless of the OptoGait’s filter settings. The ICC reported an almost perfect association (ICC > 0.9) for both SL and SF regardless of the filter setting. However, large variations between filter settings according to the data from video analysis were reported in CT and FT (0_0, 1_1 and 2_2 filter settings obtained an association ICC > 0.9, whereas other filters obtained lower ICCs). Bland-Altman plots revealed small bias and error and no presence of heteroscedasticity of error for 1_1 setting. In conclusion, the filter setting for the OptoGait system should be considered to minimize the bias and error of spatiotemporal parameters measurement. For running on a treadmill, the 1_1 filter setting is recommended if gait parameters are to be compared to a high-speed video analysis (1000 Hz).     

Stride length determination during overground running using a single foot-mounted inertial measurement unit

From a research perspective, detailed knowledge about stride length (SL) is important for coaches, clinicians and researchers because together with stride rate it determines the speed of locomotion. Moreover, individual SL vectors represent the integrated output of different biomechanical determinants and as such provide valuable insight into the control of running gait. In recent years, several studies have tried to estimate SL using body-mounted inertial measurement units (IMUs) and have reported promising results. However, many studies have used systems based on multiple sensors or have only focused on estimating SL for walking. Here we test the concurrent validity of a single foot-mounted, 9-degree of freedom IMU to estimate SL for running. We employed a running-specific, Kalman filter based zero-velocity update (ZUPT) algorithm to calculate individual SL vectors with the IMU and compared the results to SLs that were simultaneously recorded by a 6-camera 3D motion capture system. The results showed that the analytical procedures were able to successfully identify all strides that were recorded by the camera system and that excellent levels of absolute agreement (ICC(3,1) = 0.955) existed between the two methods. The findings demonstrate that individual SL vectors can be accurately estimated with a single foot-mounted IMU when running in a controlled laboratory setting.     

Gait Kinematic Analysis in Water Using Wearable Inertial Magnetic Sensors

Walking is one of the fundamental motor tasks executed during aquatic therapy. Previous kinematics analyses conducted using waterproofed video cameras were limited to the sagittal plane and to only one or two consecutive steps. Furthermore, the set-up and post-processing are time-consuming and thus do not allow a prompt assessment of the correct execution of the movements during the aquatic session therapy. The aim of the present study was to estimate the 3D joint kinematics of the lower limbs and thorax-pelvis joints in sagittal and frontal planes during underwater walking using wearable inertial and magnetic sensors. Eleven healthy adults were measured during walking both in shallow water and in dry-land conditions. Eight wearable inertial and magnetic sensors were inserted in waterproofed boxes and fixed to the body segments by means of elastic modular bands. A validated protocol (Outwalk) was used. Gait cycles were automatically segmented and selected if relevant intraclass correlation coefficients values were higher than 0.75. A total of 704 gait cycles for the lower limb joints were normalized in time and averaged to obtain the mean cycle of each joint, among participants. The mean speed in water was 40% lower than that of the dry-land condition. Longer stride duration and shorter stride distance were found in the underwater walking. In the sagittal plane, the knee was more flexed (≈ 23°) and the ankle more dorsiflexed (≈ 9°) at heel strike, and the hip was more flexed at toe-off (≈ 13°) in water than on land. On the frontal plane in the underwater walking, smoother joint angle patterns were observed for thorax-pelvis and hip, and ankle was more inversed at toe-off (≈ 7°) and showed a more inversed mean value (≈ 7°). The results were mainly explained by the effect of the speed in the water as supported by the linear mixed models analysis performed. Thus, it seemed that the combination of speed and environment triggered modifications in the joint angles in underwater gait more than these two factors considered separately. The inertial and magnetic sensors, by means of fast set-up and data analysis, can supply an immediate gait analysis report to the therapist during the aquatic therapy session.     

IMU: Inertial sensing of vertical CoM movement

The purpose of this study was to use a quaternion rotation matrix in combination with an integration approach to transform translatory accelerations of the centre of mass (CoM) from an inertial measurement unit (IMU) during walking, from the object system onto the global frame. Second, this paper utilises double integration to determine the relative change in position of the CoM from the vertical acceleration data. Five participants were tested in which an IMU, consisting of accelerometers, gyroscopes and magnetometers was attached on the lower spine estimated centre of mass. Participants were asked to walk three times through a calibrated volume at their self-selected walking speed. Synchronized data were collected by an IMU and an optical motion capture system (OMCS); both measured at 100 Hz. Accelerations of the IMU were transposed onto the global frame using a quaternion rotation matrix. Translatory acceleration, speed and relative change in position from the IMU were compared with the derived data from the OMCS. Peak acceleration in vertical axis showed no significant difference (p?0.05). Difference between peak and trough speed showed significant difference (p<0.05) but relative peak-trough position between the IMU and OMCS did not show any significant difference (p?0.05). These results indicate that quaternions, in combination with Simpsons rule integration, can be used in transforming translatory acceleration from the object frame to the global frame and therefore obtain relative change in position, thus offering a solution for using accelerometers in accurate global frame kinematic gait analyses.     

Measurement of stride parameters using a wearable GPS and inertial measurement unit

Both GPS and inertial measurement units (IMUs) have been extensively used in biomechanical studies. Expensive high accuracy GPS units can provide information about intrastride speed and position, but their application is limited by their size and cost. Single and double integration of acceleration from IMU provides information about short-term fluctuations in speed and position, but suffers from integration error over a longer period of time. The integration of GPS and IMU has been widely used in large and expensive units designed for survey and vehicle navigation. Here we propose a data fusion scheme, which is a Kalman filter based complementary filter and enhances the frequency response of the GPS and IMU used alone. We also report the design of a small (28 g) low cost GPS/IMU unit. Its accuracy after post-processing with the proposed data fusion scheme for determining average speed and intrastride variation was compared to a traditional high cost survey GPS. The low cost unit achieved an accuracy of 0.15 ms⁻¹ (s.d.) for horizontal speed in cycling and human running across a speed range of 3–10 ms⁻¹. The stride frequency and vertical displacement calculated based on measurements from the low cost GPS/IMU units had an s.d. of 0.08 Hz and 0.02 m respectively, compared to measurements from high performance OEM4 GPS units.     

3D gait assessment in young and elderly subjects using foot-worn inertial sensors

This study describes the validation of a new wearable system for assessment of 3D spatial parameters of gait. The new method is based on the detection of temporal parameters, coupled to optimized fusion and de-drifted integration of inertial signals. Composed of two wirelesses inertial modules attached on feet, the system provides stride length, stride velocity, foot clearance, and turning angle parameters at each gait cycle, based on the computation of 3D foot kinematics. Accuracy and precision of the proposed system were compared to an optical motion capture system as reference. Its repeatability across measurements (test-retest reliability) was also evaluated. Measurements were performed in 10 young (mean age 26.1±2.8 years) and 10 elderly volunteers (mean age 71.6±4.6 years) who were asked to perform U-shaped and 8-shaped walking trials, and then a 6-min walking test (6 MWT). A total of 974 gait cycles were used to compare gait parameters with the reference system. Mean accuracy±precision was 1.5±6.8 cm for stride length, 1.4±5.6 cm/s for stride velocity, 1.9±2.0 cm for foot clearance, and 1.6±6.1° for turning angle. Difference in gait performance was observed between young and elderly volunteers during the 6 MWT particularly in foot clearance. The proposed method allows to analyze various aspects of gait, including turns, gait initiation and termination, or inter-cycle variability. The system is lightweight, easy to wear and use, and suitable for clinical application requiring objective evaluation of gait outside of the lab environment.