Body Segment Accelerations Research Articles

Relationship of Knee Abduction Moment to Trunk and Lower Extremity Segment Acceleration during Sport-Specific Movements.

The knee abduction moment (KAM) has been identified as a significant predictor of anterior cruciate ligament (ACL) injury risk; however, the cost and time demands associated with collecting three-dimensional (3D) kinetic data have prompted the need for alternative solutions. Wearable inertial measurement units (IMUs) have been explored as a potential solution for quantitative on-field assessment of injury risk. Most previous work has focused on angular velocity data, which are highly susceptible to bias and noise relative to acceleration data. The purpose of this pilot study was to assess the relationship between KAM and body segment acceleration during sport-specific movements. Three functional tasks were selected to analyze peak KAM using optical motion capture and force plates as well as peak triaxial segment accelerations using IMUs. Moderate correlations with peak KAM were observed for peak shank acceleration during single-leg hop; peak trunk, thigh, and shank accelerations during a deceleration task; and peak trunk, pelvis, and shank accelerations during a 45° cut. These findings provide preliminary support for the use of wearable IMUs to identify peak KAM during athletic tasks.

승마 운동이 sit-to-stand 동작 시 신체 동적 안정성에 미치는 영향

The purpose of this study was to analyze the effect of horseback riding exercise on the body dynamic stability of body during STS(sit-to-stand) movement. Twenty teenage students participated in this study, and 8 motion capture cameras were used during STS before and after the 12-week horseback riding exercise program. The knee, pelvis, and trunk segment root mean square acceleration and attenuation factors were analyzed in the AP, ML, VT directions. paired t-test was evaluated to compare mean differences between before and after 12 weeks. During sit-to-stand motion after horseback riding exercise, the ML direction RMS acceleration value of the trunk segment decreased, whereas the pelvis and trunk segment RMS acceleration values increased in the AP and VT directions. And while the VT direction Ckp and Ckt attenuation values increased, the VT direction Cpt and ML and AP direction attenuation values decreased. Therefore, it was found that horseback riding exercise also affected the attenuation determined by the forward and upward body acceleration of teenagers and the mutual acceleration of body segments during STS.

On the impact of the erroneous identification of inertial sensors' locations on segments and whole-body centers of mass accelerations: a sensitivity study in one transfemoral amputee.

The kinematics of the body center of mass (bCoM) may provide crucial information supporting the rehabilitation process of people with transfemoral amputation. The use of magneto-inertial measurement units (MIMUs) is promising as it may allow in-the-field bCoM motion monitoring. Indeed, bCoM acceleration might be obtained by fusing the estimated accelerations of body segments' centers of mass (sCoM), the formers being computed from the measured accelerations by segment-mounted MIMUs and the known relative position between each pair of MIMU and underlying sCoM. This paper investigates how erroneous identifications of MIMUs positions impact the accuracy of estimated 3D sCoM and bCoM accelerations in transfemoral amputee gait. Using an experimental design approach, 215 simulations of erroneous identifications of MIMUs positions (up to 0.02 m in each direction) were simulated over seven recorded gait cycles of one participant. MIMUs located on the trunk and sound lower limbs were shown to explain up to 77% of the variance in the accuracy of the estimated bCoM acceleration, presumably due to the higher mass and/or angular velocity of these segments during gait of lower-limb amputees. Therefore, a special attention should be paid when identifying the positions of MIMUs located on segments contributing the most to the investigated motion. Sensitivity of the estimated vertical body center of mass acceleration to erroneous identifications of MIMU positions in the anteroposterior (AP), mediolateral (ML), and vertical (V) directions, expressed in percentage of the total variance of the estimation accuracy.

Joint Angle Estimation by Body Segment Acceleration in the Activities of Daily Living

Joint Angle Estimation by Body Segment Acceleration in the Activities of Daily Living

Inertial sensing of the motion speed effect on the sit-to-walk activity

The STW execution at motion speed faster than normal most possibly enhances the risk for balance loss due to the increase in body segment accelerations. The purpose of the study was to use inertial sensing to examine the effect of motion speed on the STW segmental kinematics and its temporal events. Eighteen young men (20.7 ± 2.0 years) performed STW trials at preferred (PS) and fast (FS) motion speed. Data were collected with Xsens inertial sensors positioned at the trunk, thigh, shank, and foot segments. The maximum segmental values of angular displacement, angular velocity and linear acceleration, the duration of total STW (ttotal), the absolute and relative (% ttotal) phase duration (Flexion, Transition, Extension, Walking) and, the absolute and relative time taken to reach each maximum value were determined. In FS, ttotal and the absolute phase duration (except for Transition), were all significantly shorter (p = 0.000). The relative phase duration was not altered (p > 0.05), except for the Extension shortening (p = 0.001). The maximum angular displacement was altered only for the thigh (decreased, p = 0.038) and shank (increased, p = 0.004). Maximum angular velocities and linear accelerations were all significantly increased (p = 0.000 for all). The absolute time to reach the maximum values shortened in FS (p ≤ 0.05), while, the relative times were not altered (p > 0.05), except for the delayed trunk maximum angular displacement (p = 0.039). Inertial sensing appears to identify the motion speed effect on STW segmental kinematics and their temporal events in healthy young men. The results of the study may contribute improving the preventive or rehabilitation interventions in persons with impaired postural control.

Continuous ambulatory hand force monitoring during manual materials handling using instrumented force shoes and an inertial motion capture suit

Hand forces (HFs) are commonly measured during biomechanical assessment of manual materials handling; however, it is often a challenge to directly measure HFs in field studies. Therefore, in a previous study we proposed a HF estimation method based on ground reaction forces (GRFs) and body segment accelerations and tested it with laboratory equipment: GFRs were measured with force plates (FPs) and segment accelerations were measured using optical motion capture (OMC). In the current study, we evaluated the HF estimation method based on an ambulatory measurement system, consisting of inertial motion capture (IMC) and instrumented force shoes (FSs).Sixteen participants lifted and carried a 10-kg crate from ground level while 3D full-body kinematics were measured using OMC and IMC, and 3D GRFs were measured using FPs and FSs. We estimated 3D hand force vectors based on: (1) FP+OMC, (2) FP+IMC and (3) FS+IMC. We calculated the root-mean-square differences (RMSDs) between the estimated HFs to reference HFs calculated based on crate kinematics and the GRFs of a FP that the crate was lifted from.Averaged over subjects and across 3D force directions, the HF RMSD ranged between 10-15N when using the laboratory equipment (FP + OMC), 11-18N when using the IMC instead of OMC data (FP+IMC), and 17-21N when using the FSs in combination with IMC (FS + IMC). This error is regarded acceptable for the assessment of spinal loading during manual lifting, as it would results in less than 5% error in peak moment estimates.

Sensor node acceleration signatures and electromyography in synchronisation and sequencing analysis in sports: A rowing perspective

Following a review of the key determinants of successful rowing, a wireless body sensor network was developed to monitor boat and body segment acceleration and surface electromyography in major muscles recruited during the rowing stroke cycle. Its design was optimised to yield maximum information about the rowing stroke cycle from fewest sensors and minimise the power consumption of the nodes. The system was validated against the Qualisys motion capture and high-speed camera system with most Pearson correlation coefficients in excess of r = 0.8. On-land ergometer experimentation allowed muscle recruitment over the stroke cycle to be studied, with data from multiple experiments combined using correlation of the acceleration signatures of back and thigh nodes (r = 0.95). It was demonstrated that it was possible to identify one of the common rowing errors of ‘shooting-the-slide’ from the data collected, and that a marked decrease in correlation of good-to-bad technique over the drive phase of the stroke (0.95 reducing to 0.34 in the experiment undertaken) could be used to indicate the presence of this error. Extension of the wireless body sensor network to encompass boat and two oarsmen was demonstrated, allowing correlation of their rowing signatures to be studied, indicating their cohesion as a crew.

Estimating dynamic external hand forces during manual materials handling based on ground reaction forces and body segment accelerations

Direct measurement of hand forces during assessment of manual materials handling is infeasible in most field studies and some laboratory studies (e.g., during patient handling). Therefore, this study proposed and evaluated the performance of a novel hand force estimation method based on ground reaction forces (GRFs) and body segment accelerations.Ten male subjects performed a manual lifting/carrying task while an optoelectronic motion tracking system measured 3D full body kinematics, a force plate measured 3D GRFs and an instrumented box measured 3D hand forces. The estimated 3D hand forces were calculated by taking the measured GRF vector and subtracting the force vectors due to weight and acceleration of all body segments.Root-mean-square difference (RMSD) between estimated and measured hand forces ranged from 11 to 27N. When ignoring the segment accelerations (just subtracting body weight from the GRFs), the hand force estimation errors were much higher, with RMSDs ranging from 21 to 101N. Future studies should verify the performance of the proposed hand force estimation method when using an ambulatory field measurement system.

Dynamic Analysis and Motion Measurement of Ski Turns Using Inertial and Force Sensors

This paper proposes the dynamic motion analysis method of ski turns using inertial and force sensors. The motion analysis of ski turns in gliding on an actual field is important to resolve the mechanism of ski turns. However, it is difficult to measure physical exertion due to the severe experimental surrounding such as the outside snow conditions and the weather on the mountain. Therefore, few studies have analyzed ski turns quantitatively. The control force of skier gliding on the actual snow field must be clarified to resolve the mechanism of ski turns. In the previous studies, we developed the 3D posture estimation method of skier gliding at high speed. This method can estimate the Roll- Pitch-Yaw angles in local coordinate by the information of inertial sensors using the Unscented Kalman filter. The control force of skier (joint torque) can be calculated by combining this method and the measurement of reaction force from snow surface. We conducted the experiment of skier gliding on the actual snow field. The inertial sensors were attached to the body segments (upper body, lumber, femur, and lower thigh) of skier and ski boots, and the 6- axis force sensors were installed between boots and skis. The inertial sensors measure angular velocity and acceleration of body segments, and the force sensors measure the reaction force from snow surface. The joint torque (lumber spine, hip, knee and ankle) of skier is calculated by applying the measurement information to the Newton- Euler method. The analysis results using joint torque indicates the control force of skier gliding on the actual snow field. Therefore, the analysis method and results can be used to evaluate the skill of turns and to resolve the mechanism of ski turns.

Improvement of musculoskeletal model inputs: adjustment of acceleration by dynamic optimisation

The knowledge of intrinsic dynamics in terms of joint torques and muscle tensions is of importance for clinical investigations. The common process is to solve a multibody inverse dynamic problem based on a set of iterative equations using noisy experimental data as guest. Body segment accelerations are usually assessed by double differentiation, a method well-known to amplify kinematic measurement noise. As a result, iterative equations propagate uncertainties leading to inconsistencies between measured external force and the rate of change of linear momentum. Recent studies addressed this residual force problem by adjusting mass distribution while they calculate force tensions or by dealing with acceleration computation. However, these different approaches were based on a least-square problem still leading to approximate intrinsic dynamics. The aim of this communication is to compute joint accelerations by solving a dynamic optimization problem. We will examine the effect of the optimal adjustment on joint torques and muscle tensions.

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.

Upper limb activity over time in complex regional pain syndrome type 1 as objectively measured with an upper limb-activity monitor: An explorative multiple case study

Background An upper limb-activity monitor (ULAM) has been developed to determine activity limitations in complex regional pain syndrome type 1 (CRPS1). The ULAM is based on 24 h ambulatory monitoring of body segment accelerations and enables valid and objective quantification of mobility and upper limb activity in transversal studies. Aims To explore upper limb activity over time in acute upper limb CRPS1 as measured with the ULAM in a longitudinal study, and to compare this to time courses of other outcome measures for activity limitations and impairments. Methods Four subjects were measured four times during a treatment protocol. Several ULAM outcome measures related to upper limb usage and mobility, three questionnaires (RASQ, DASH, RAND36), and six impairment outcome indicators (VAS-momentary pain, VAS-pain resulting from effort, volume, temperature, active range of motion, strength) were used. Results Objectively measured upper limb activity frequently improved; improvements of >5% were found for 63% of the ULAM outcome measures at final assessment. The ULAM outcome measures had a time course more similar to the body-part and CRPS1 specific questionnaire RASQ than the other questionnaires. The time course of impaired temperature was most often in accordance with the ULAM, and both VAS scores showed least accordance. Conclusions Clear changes in upper limb activity over time were frequently found as objectively measured with the ULAM, and relationships among the time courses of the ULAM and other outcome measures were largely explainable. The ULAM can validly assess upper limb activity over time in CRPS1, but between-measurement variability needs careful consideration.

Assessment of two-dimensional induced accelerations from measured kinematic and kinetic data

A simple algorithm is presented to calculate the induced accelerations of body segments in human walking for the sagittal plane. The method essentially consists of setting up 2x4 force equations, 4 moment equations, 2x3 joint constraint equations and two constraints related to the foot-ground interaction. Data needed for the equations are, next to masses and moments of inertia, the positions of ankle, knee and hip. This set of equations is put in the form of an 18x18 matrix or 20x20 matrix, the solution of which can be found by inversion. By applying input vectors related to gravity, to centripetal accelerations or to muscle moments, the 'induced' accelerations and reaction forces related to these inputs can be found separately. The method was tested for walking in one subject. Good agreement was found with published results obtained by much more complicated three-dimensional forward dynamic models.

Biomechanical analysis of two patient handling tasks

Nursing personnel have a high prevalence of back problems related to patient handling. The demand for evaluation of techniques for patient handling tasks motivates the development of reliable and easy to use biomechanical models. Complete dynamic analyses are complicated to carry out and when simpler analyses are sufficient they should be used instead. The aim of the study was to find out if two patient handling tasks could be analyzed “semidynamically”, i.e. by ignoring the inertial effects from single body segments. The two taska were (1) turning patient in bed and (2) moving the patient up the bed, respectively, and twelve physiotherapists participated as subjects. Two persons collaborate in moving the patient using a drawsheet and a friction-reducing plastic sheet. Motions, ground force reactions and subjective ratings of exertion were registered. Body segment accelerations, free moments of ground reactions and net moments at the lower back were determined. It was found that the tasks did not require fully dynamic analyses since the segmental contributions to the inertial effects were negligible. Large values of the free moment of ground reaction revealed asymmetry and twisted postures in one of the tasks, though it at first appeared to be a largely two-dimensional situation.

Inertial effects from single body segments in dynamic analysis of lifting

Biomechanical calculations of loads on the locomotor system in lifting tasks are often based on static models. Several investigators have shown, though, that in a dynamic act like lifting, inertial effects are not generally negligible. A complete dynamic analysis includes the calculation of linear and angular accelerations of body segments and is rather complicated to carry out. So it was of interest to find out whether the contribution of single body segments to the dynamic effects of the whole body might be negligible. Ten male subjects lifted a 12.8 kg box using two different techniques and two speeds. Ground reactions and body segment movements were recorded and reaction forces and net moments at different joints were calculated with static, dynamic and 'semidynamic' methods. The latter method incorporated the ground reaction forces as measured from a force plate but was otherwise equal to the static method. The results from semidynamic analyses agreed well with those from complete dynamic analyses for the ankle, knee, hip, and L5/S1 joints. For example, the semidynamically calculated peak moments at L5/S1 differed on average less than 3% from the dynamically calculated values. The contributions of the lower extremities and the pelvis to the dynamic effects of the whole body seemed to be quite small. The less complicated semidynamic method offers a good alternative to a fully dynamic analysis for estimations of peak moments in the lower back, at least for the studied lifting techniques.

A comparison of the triceps surae and residual muscle moments at the ankle during cycling

The rigid linked system model and principles of inverse dynamics have been widely used to calculate residual muscle moments during various activities. EMG driven models and optimization algorithms have also been presented in the literature in efforts to estimate skeletal muscle forces and evaluate their possible contribution to the residual muscle moment. Additionally, skeletal muscle-tendon forces have been measured, directly, in both animals and humans. The purpose of this investigation was to calculate the moment produced by the triceps surae muscles and compare it to the residual muscle moment at the ankle during cycling at three power outputs (90, 180 and 270 W). Inferences were made regarding the potential contribution made by each triceps surae component to the tendon force using EMG and muscle-tendon length changes. A buckle-type transducer was surgically implanted on the right Achilles tendon of one male subject. Achilles tendon forces measured in vivo were multiplied by their corresponding moment arms to yield the triceps surae moment during the three working conditions. Moment arm lengths were obtained in a separate experiment using magnetic resonance imaging (MRI). Pedal reaction forces, body segment accelerations (determined from high speed film), and appropriate mass parameters served as input to the inverse solution. The triceps surae moment was temporally in phase with and consistently represented approximately 65% of the residual muscle moment at the ankle. These data demonstrate the feasibility of using implanted transducers in human subjects and provide a greater understanding of musculoskeletal mechanics during normal human movements.