Body Center Of Mass Trajectory Research Articles

Speed-dependent modulations of asymmetric center of body mass trajectory in the gait of above-knee amputee subjects.

How to achieve stable locomotion while overcoming various instabilities is an ongoing research topic. One essential factor for achieving a stable gait is controlling the center of body mass (CoM). The CoM yields more instability in the mediolateral direction. Examining speed-dependent modulations of the CoM trajectories in the frontal plane can provide insight into control policies for achieving stable locomotion. Although these modulations have been studied while assuming symmetric CoM trajectories, this assumption is generally incorrect. For example, amputee subjects demonstrate asymmetric CoM trajectories. Here, we investigated speed-dependent modulations of asymmetric CoM trajectories in above-knee amputee subjects using Fourier series expansion. Despite the asymmetric CoM trajectories in amputee subjects, the framework of Fourier series expansion clarified that amputee subjects showed the same speed-dependent modulations as non-amputee subjects whose CoM trajectories were symmetric. Specifically, CoM trajectories became narrower in the mediolateral direction and broader in the superoinferior direction as walking speed increased. The speed-dependent modulations of CoM trajectories had a functional role in improving dynamic stability, and faster walking speeds provided greater dynamic stability on both prosthetic and non-prosthetic sides. Although the asymmetry of foot contact duration and CoM trajectory decreased as walking speed increased, step width and the asymmetry of dynamic stability between prosthetic and non-prosthetic sides remained constant across the walking speed, which corresponded to the predictions by our framework. These findings could offer a better strategy for achieving stable walking for amputee subjects.

Mechanisms that stabilize human walking


 
 
 In this paper we review what mechanisms are used to stabilize human bipedal gait. Based on mechanical reasoning, potential mechanisms to control the body center of mass trajectory are modulation of foot placement, stance leg control consisting of modulation of ankle moments and push-off forces, and modulations of the body’s angular momentum. The first two mechanisms and especially the first are dominant in controlling center of mass accelerations during gait, while angular momentum control plays a lesser role, but may be important to control body alignment and orientation. The same control mechanisms stabilize both steady-state and perturbed gait in both the mediolateral and antero-posterior directions. Control is at least in part active and is affected by proprioceptive, visual and vestibular information. Results support that this reflects a feedback process in which sensory information is used to obtain an estimate of the center of mass state based on which foot placement and ankle moments are modulated. These active feedback mechanisms suggest training approaches for populations at risk of falling, such as augmenting their effective use by means of augmented feedback, or using their complementary nature to train one mechanism by constraining the other mechanisms.
 
 

Just a matter of indexes: symmetry in walking

Gait symmetry is related to differences between the left and right side of the body and provides information about functional limitation due to pathology/injury [1]. Many metrics exist to quantify gait symmetry, differing for the considered data source and mathematical approach [1]. Although the body center of mass (BCoM) is the point that globally represents an individual’s movement, very few studies have focused on the quantification of gait symmetry from its trajectory (Simmetry Index, SI) [2]. Conversely, the use of the Harmonic Ratio and of its improved version (iHR) has gained great popularity in recent years [3], being extracted from trunk 3D accelerations easily measured by wearable inertial devices. The relationship between the SI and iHR, however, has not been quantified yet. The aim of this study is thus to investigate this relationship in healthy adults during walking at different speeds. Five healthy adults (2 women, 1.69±0.08 m, 29.8±2.8 y) participates to this study (CAR 101/2021). They walked for 60 s on a treadmill at six different speeds (from 0.55 to 1.95 m/s with step of 0.28 m/s). The trajectories of 18 markers located on the main joint centers [4] were collected by an optoelectronic system (Vicon, 200 Hz). Simultaneously, lower trunk 3D linear accelerations were measured by an inertial sensor (APDM Opal, 200 Hz). The 3D trajectory of the BCoM was estimated from marker trajectories as the weighted mean of an 11–segment model [4]. Gait symmetry was then quantified for each stride and each direction (antero-posterior AP, medio-lateral ML, cranio-caudal CC) using two indices: the Symmetry Index (SI) from the BCoM trajectory [2] and the iHR from the trunk accelerations [3]. Both iHR and SI are based on the harmonic content of the relevant signal and range from 100% (perfect symmetry) to 0% (total asymmetry). To assess the effect of walking speed on SI and iHR values, a two-way repeated measure ANOVA was performed after verifying for normal data distribution. A total number of 1572 strides were analyzed, with a minimum of 288 strides for each participant. SI and iHR significantly differed in all three directions for each velocity (p<0.01), except at 1.39, 1.67 and 1.95 m/s in the ML direction (Fig. 1). When considering the effect of gait speed on symmetry values, the latter significantly changed only for the AP and CC components (p<0.0001) ( Fig. 1 ). SI and iHR may provide substantial different information about the level of gait symmetry, with iHR characterized by greater values in AP and CC directions and smaller values in ML direction. Interestingly, gait symmetry increases with speed, at least up to 1.67 m/s, in AP and CC directions. This is not the case for the ML component: whereas SI slightly decreases with speed (p<0.05), the high variability of iHR, already discussed in the literature [4], does not allow to identify any clear trend. It is suggested to carefully describe the methodology used to assess gait symmetry, as the type of data and the method used may strongly influence the final outcome and, thus, its clinical interpretation.

Speed- and mode-dependent modulation of the center of mass trajectory in human gaits as revealed by Lissajous curves

The central nervous system (CNS) achieves a stable gait at several speeds and modes while controlling diverse instability. An essential feature of a gait is the motion of the center of body mass (CoM). CoM motion is at larger risk for trespassing the base of support in the mediolateral direction than in the anteroposterior direction. How the CoM trajectory in the frontal plane changes depending on the speed or mode can thus provide insights about the neural control of stable gaits. Here, we reveal the speed- and mode-dependent modulations of the trajectory by utilizing a Lissajous curve. The current study clarifies that speed-dependent modulations are evident in walking. Between walking and running, there were significant mode-dependent modulations. In contrast, there were no significant speed-dependent modulations during running. Deviations from standard tendencies quantified via Lissajous curve fitting could be a sign of gait impairments and recovery after treatments.

Symmetry Analysis of Amputee Gait Based on Body Center of Mass Trajectory and Discrete Fourier Transform.

The calculation of symmetry in amputee gait is a valuable tool to assess the functional aspects of lower limb prostheses and how it impacts the overall gait mechanics. This paper analyzes the vertical trajectory of the body center of mass (CoM) of a group formed by transfemoral amputees and non-amputees to quantitatively compare the symmetry level of this parameter for both cases. A decomposition of the vertical CoM into discrete Fourier series (DFS) components is performed for each subject’s CoM trajectory to identify the main components of each pattern. A DFS-based index is then calculated to quantify the CoM symmetry level. The obtained results show that the CoM displays different patterns along a gait cycle for each amputee, which differ from the sine-wave shape obtained in the non-amputee case. The CoM magnitude spectrum also reveals more coefficients for the amputee waveforms. The different CoM trajectories found in the studied subjects can be thought as the manifestation of developed compensatory mechanisms, which lead to gait asymmetries. The presence of odd components in the magnitude spectrum is related to the asymmetric behavior of the CoM trajectory, given the fact that this signal is an even function for a non-amputee gait. The DFS-based index reflects this fact due to the high value obtained for the non-amputee reference, in comparison to the low values for each amputee.

Body center of mass trajectory and mechanical energy using inertial sensors: a feasible stride?

BackgroundThe description of the three-dimensional (3D) trajectory of the body center of mass (BCoM) provides useful insights on the mechanics of locomotion. The BCoM trajectory can be estimated from ground reaction forces, recorded by force platforms (GRF, gold standard), or from marker trajectories recorded by stereophotogrammetric systems (MKR). However, both instruments do not allow for monitoring locomotion in the real-life environment. In this perspective, magneto-inertial measurement units (MIMUs) are particularly attractive being wearable, thus enabling to collect movement data out of the laboratory. Research questionsTo investigate the feasibility and accuracy of a recent marketed full-body MIMU-based method for the estimation of the 3D BCoM trajectory and energetics during walking. MethodsTwelve subjects walked at self-selected and slow speed along a 12 m long walkway. GRF and MKR were acquired using three force platforms and a stereophotogrammetric system. MIMU data were collected using a full-body MIMU-based motion capture system (Xsens MTw Awinda). The 3D BCoM trajectory, external mechanical work and energy recovery were extracted from the data acquired by the three measurement systems, using state-of-the-art methods. The accuracy of both MKR- and MIMU-based estimates compared with GRF was assessed for the BCoM trajectory (maximum, minimum, range, and RMSD), as well as for mechanical work and energy recovery. ResultsA total number of 108 strides were analyzed. MIMU-based BCoM trajectory displayed larger errors in comparison with GRF (and MKR) for the trajectory ranges: 89 ± 47(93 ± 44)% in antero-posterior, 46 ± 25(40 ± 79)% medio-lateral and -13 ± 23(-5 ± 25)% vertical directions, leading to a 3D RMSD of 17 ± 5(12 ± 5) mm (mean ± SD). These discrepancies largely affected the estimation of both mechanical work and energy recovery (+115 ± 85% and -28 ± 21%, respectively). SignificancePreliminary findings highlighted that the tested MIMU-based method for BCoM trajectory estimation still lacks accuracy and that the quantification of energetics in real-life situations remains an open challenge.

WITHDRAWN: Body center of mass trajectory and mechanical energy using inertial sensors: A feasible stride?

WITHDRAWN: Body center of mass trajectory and mechanical energy using inertial sensors: A feasible stride?

On the Estimation Accuracy of the 3D Body Center of Mass Trajectory during Human Locomotion: Inverse vs. Forward Dynamics

The dynamics of body center of mass (BCoM) 3D trajectory during locomotion is crucial to the mechanical understanding of the different gaits. Forward Dynamics (FD) obtains BCoM motion from ground reaction forces while Inverse Dynamics (ID) estimates BCoM position and speed from motion capture of body segments. These two techniques are widely used by the literature on the estimation of BCoM. Despite the specific pros and cons of both methods, FD is less biased and considered as the golden standard, while ID estimates strongly depend on the segmental model adopted to schematically represent the moving body. In these experiments a single subject walked, ran, (uni- and bi-laterally) skipped, and race-walked at a wide range of speeds on a treadmill with force sensors underneath. In all conditions a simultaneous motion capture (8 cameras, 36 markers) took place. 3D BCoM trajectories computed according to five marker set models of ID have been compared to the one obtained by FD on the same (about 2,700) strides. Such a comparison aims to check the validity of the investigated models to capture the “true” dynamics of gaits in terms of distance between paths, mechanical external work and energy recovery. Results allow to conclude that: (1) among gaits, race walking is the most critical in being described by ID, (2) among the investigated segmental models, those capturing the motion of four limbs and trunk more closely reproduce the subtle temporal and spatial changes of BCoM trajectory within the strides of most gaits, (3) FD-ID discrepancy in external work is speed dependent within a gait in the most unsuccessful models, and (4) the internal work is not affected by the difference in BCoM estimates.

Characteristics of center of body mass trajectory and lower extremity joint motion responded by dynamic motions of balance training system

Purpose To provide an optimized strategy for balance rehabilitation training, we identified the change of joint angles in lower-extremity and trajectory of center of body mass (COM) in response to rotation of base plate of balance training equipment.

Sport specificity background affects the principal component structure of vertical squat jump performance of young adult female athletes

PurposeLong-term training specificity is thought to alter performance in tests evaluating strength and power production capability. The aim of the present study was to provide additional information to the limited existing knowledge concerning the possible differences of the force/time profile of squat jumping among different groups of young female athletes. MethodsOne hundred and seventy-three adult women (20.1 ± 2.8 years, 1.71 ± 0.09 m, 65.6 ± 10.3 kg, mean ± SD for age, height, and mass, respectively) engaged in track and field (TF), volleyball (VO), handball (HA), basketball (BA), and physical education students (PE) executed maximal squat jumps (SQJ) on a force plate. Pearson's correlation was used to identify the relationship between SQJ performance, the anthropometric characteristics and the biomechanical parameters. Differences concerning the biomechanical parameters among groups were investigated with analysis of variance, while the force- (FPD) or time- (TPD) dependency of SQJ execution was examined using principal components analysis (PCA). ResultsSQJ was unrelated to body height but significantly correlated with body mass (r = −0.26, p = 0.001). TF jumped higher and produced larger peak body power output compared to all the other groups (p < 0.05). All athletes were superior to PE since they performed the SQJ with a longer (p < 0.05) vertical body center of mass trajectory during the propulsion phase. PCA results revealed that TF significantly differentiated than the other groups by relying on FPD. ConclusionVarious different profiles of FPD and TPD were detected due to different sporting background in young female athletes. Since TF superiority in SQJ was relied on the larger power production and a greater FPD, female indoor team sport athletes are suggested to execute jumping exercises adopting the jumping strategies utilized by TF.

Estimation of 2-D Center of Mass Movement During Trunk Flexion–Extension Movements Using Body Accelerations

Motions of the center of body mass (COM) and body segment acceleration signals are commonly used to indicate movement performance and stability during standing activities. The COM trajectory is usually calculated by video motion analysis, which has a time consuming setup and also is not readily available in all clinical settings. In this paper, we present a novel method to estimate the COM trajectory from the upper and lower limb accelerations, based on experimental data. We have modeled the relationships that exist between the 2-D hip and trunk acceleration data with the 2-D COM trajectory in the sagittal plane, during four trunk flexion-extension movement tasks and estimated the COM trajectory based on that model. The model accounted for between 93 +/- 9% to 97 +/- 3% of the resultant COM trajectory's variability, depending on the task. This corresponded to a range of absolute error between the true and estimated COM trajectories of 0.65 +/- 0.62 to 1.07 +/- 1.13 cm. The advantage of this model compared to our previous work on COM trajectory estimation is that it does not require any calibration and provides a reasonably accurate estimation of the COM trajectory, which can be used to study human balance performance in any clinical setting.

Ambulatory Center of Mass Prediction Using Body Accelerations and Center of Foot Pressure

The center of body mass (COM), center of foot pressure (COP), and body segment acceleration signals are commonly used to indicate movement performance and stability during standing activities and walking. For balance maintenance and restoration, the human brain is capable of estimating and predicting the COM even in the absence of visual or vestibular information. Thus, we hypothesized that the COM may be acquired through the processing of proprioceptive somatosensory information, represented by body segment accelerations, and an external spatial reference, the ground support, represented by the COP. To investigate this hypothesis, we modeled the relationships that exist between the COP and accelerometer data with the 3-D COM trajectory, during walking on firm and irregular surfaces. The models accounted for 99.85 +/- 0.20% and 99.77 +/- 0.39% of the resultant COM trajectory's variability for the firm and irregular surfaces, respectively. This corresponded to a percentage error between the estimated and actual resultant COM of 16.06 +/- 11.11% for the firm surface and 21.41 +/- 12.70% for the doweling surface. In turn, this translates into an absolute error between the true and actual resultant COM of 3.62 +/- 2.69 cm and 4.74 +/- 3.01 cm for the firm and doweling surfaces, respectively. The model is novel in that it does not require any calibration and provides a reasonably accurate estimation of the COM, which can be compared to the brain's balance performance. Hence, this model could be used instead of the cumbersome method of video motion analysis for COM calculation.

태권도 주춤 서 몸통지르기 유형별 생체역학적 변인 비교 분석

The purpose of this study is to compare 4 different body punch types(type 1: a punch using a shoulder, type 2: a punch using a waist, type 3: a punch using lower extremities, and type 4: a punch with elbows by your side at chest level) in horseback-riding stance and establish suitable teaching theory and method, which would be a useful reference to Taekwondo instructors on the spot(in Taekwondo dojangs all around Korea). Five exhibition players from Korean national Taekwondo exhibition team participated in this study. Each participant was asked to perform the four different types of punches and their kinematic and kinetic data were recorded with 7 vicon cameras(125Hz) and two force plates(AMTI, 1200Hz). We analyzed displacement, time, resultant center of body mass trajectory, velocity, trunk angular velocity, and ground reaction force(GRF) from each body segment in body punch and the result. I performed 1-way ANOVA(RM) for average values of each player after standardization and statistical significance was set as p<.05. was as the following ; First, they showed a tendency to take the body punch posture with the biggest motion at a shoulder and on descending order a waist and a knee. Second, a mean time for each body punch on ascending order 0.46sec. for type 2, 0.49sec for type 3, 0.50sec. for type 4, and 0.56sec. for type 1. Third, a mean resultant center of body mass trajectory for each body punch the longest 4.07cm for type 3 and the shortest 2.458cm for type 1. Fourth, a mean of maximal velocity of a fist strike was the fastest 5.99m/s for type 3, 5.93m/s for type 4, 5.67m/s for type 2, and 5.01m/s for type 1 on the descending order. Fifth, a mean of maximal trunk angular velocity of the fastest 495.6deg./sec. for type 4 and 337.7deg./sec. for type 1 on the descending order. Sixth, strongest value was type 3, 2 for anterior-posterior ground reaction force(left -54.89N, right 60.58N), type 4 for medial-lateral GRF(left 83.59N, right -80.12N), and type 3 for vertical GRF(left 341.79N, right 426.11N).

GENERATION OF LINEAR AND ANGULAR MOMENTUM DURING INTERACTION WITH DEFORMABLE SURFACES

INTRODUCTION Generation of linear and angular momentum during goal directed movements involves regulation of the total body center of mass trajectory (CM) in relation to the reaction forces (RF) during contact with the environment. When interacting with energy-returning systems like a springboard, the performer is able store energy in the springboard during board depression for later use during the recoil phase. During the board depression phase of springboard dives initiated from a hurdle, no significant differences in CM trajectory in relation to the RF were observed between front (FS) and reverse (RS) somersaults (FS: rotate forward and translate forward; RS: rotate backward and translate forward). During the board recoil phase, between-task differences in angular impulse generation were achieved by modifying the relative orientation between the CM and the RF [1]. These results at the total body level, led us to hypothesize that no significant differences in multijoint control would be observed within subject during the board depression phases of the FS and RS, whereas significant differences in multijoint control would be observed during the recoil phase. We tested this hypothesis by comparing knee-hip coordination and muscle activation patterns during the take-off phase of the FS and RS dives performed by the same subjects.

Optimizing the determination of the body center of mass

The position or trajectory of the body center of mass (COM) is often a parameter of interest when studying posture or movement. For instance, in balance control studies the body COM can be related to the ground reaction force or to the base of support. Since small displacements of the body COM are important in balance control studies, it is essential to obtain valid estimates of the body COM. The main source of error in the determination of the body COM is the estimation of the masses and centers of mass of the body segments. Especially the determination of the trunk COM is prone to error. In the current study five subjects maintained three postures, differing in trunk angle, during a few seconds. The relation between the center of pressure of the ground reaction force and the vertical projection of the body COM during the postures was used to optimize the trunk COM position. Additionally the subjects performed two lifting movements. The validity of the body COM trajectory estimation during the lifting movements, both with and without optimized trunk COM, was checked by relating the external moment of the ground reaction force with respect to the body COM to the rate of change of the angular momentum of the whole body. It was shown that the correspondence between the external moment and the rate of change of the angular momentum improved after optimization of the trunk COM. This suggests that the body COM trajectory estimation can be improved by the proposed optimization procedure.