Full-body Kinematics Research Articles

Open-source software library for real-time inertial measurement unit data-based inverse kinematics using OpenSim.

Inertial measurements (IMUs) facilitate the measurement of human motion outside the motion laboratory. A commonly used open-source software for musculoskeletal simulation and analysis of human motion, OpenSim, includes a tool to enable kinematics analysis of IMU data. However, it only enables offline analysis, i.e., analysis after the data has been collected. Extending OpenSim's functionality to allow real-time kinematics analysis would allow real-time feedback for the subject during the measurement session and has uses in e.g., rehabilitation, robotics, and ergonomics. We developed an open-source software library for real-time inverse kinematics (IK) analysis of IMU data using OpenSim. The software library reads data from IMUs and uses multithreading for concurrent calculation of IK. Its operation delays and throughputs were measured with a varying number of IMUs and parallel computing IK threads using two different musculoskeletal models, one a lower-body and torso model and the other a full-body model. We published the code under an open-source license on GitHub. A standard desktop computer calculated full-body inverse kinematics from treadmill walking at 1.5 m/s with data from 12 IMUs in real-time with a mean delay below 55 ms and reached a throughput of more than 90 samples per second. A laptop computer had similar delays and reached a throughput above 60 samples per second with treadmill walking. Minimal walking kinematics, motion of lower extremities and torso, were calculated from treadmill walking data in real-time with a throughput of 130 samples per second on the laptop and 180 samples per second on the desktop computer, with approximately half the delay of full-body kinematics. The software library enabled real-time inverse kinematical analysis with different numbers of IMUs and customizable musculoskeletal models. The performance results show that subject-specific full-body motion analysis is feasible in real-time, while a laptop computer and IMUs allowed the use of the method outside the motion laboratory.

A public data set of walking full-body kinematics and kinetics in individuals with Parkinson's disease.

To our knowledge, there is no Parkinson's disease (PD) gait biomechanics data sets available to the public. This study aimed to create a public data set of 26 idiopathic individuals with PD who walked overground on ON and OFF medication. Their upper extremity, trunk, lower extremity, and pelvis kinematics were measured using a three-dimensional motion-capture system (Raptor-4; Motion Analysis). The external forces were collected using force plates. The results include raw and processed kinematic and kinetic data in c3d and ASCII files in different file formats. In addition, a metadata file containing demographic, anthropometric, and clinical data is provided. The following clinical scales were employed: Unified Parkinson's disease rating scale motor aspects of experiences of daily living and motor score, Hoehn & Yahr, New Freezing of Gait Questionnaire, Montreal Cognitive Assessment, Mini Balance Evaluation Systems Tests, Fall Efficacy Scale-International-FES-I, Stroop test, and Trail Making Test A and B. All data are available at Figshare (https://figshare.com/articles/dataset/A_dataset_of_overground_walking_full-body_kinematics_and_kinetics_in_individuals_with_Parkinson_s_disease/14896881). This is the first public data set containing a three-dimensional full-body gait analysis of individuals with PD under the ON and OFF medication. It is expected to contribute so that different research groups worldwide have access to reference data and a better understanding of the effects of medication on gait.

A need for speed: Objectively identifying full-body kinematic and neuromuscular features associated with faster sprint velocities.

Sprinting is multifactorial and dependent on a variety of kinematic, kinetic, and neuromuscular features. A key objective in sprinting is covering a set amount of distance in the shortest amount of time. To achieve this, sprinters are required to coordinate their entire body to achieve a fast sprint velocity. This suggests that a whole-body kinematic and neuromuscular coordinative strategy exists which is associated with improved sprint performance. The purpose of this study was to leverage inertial measurement units (IMUs) and wireless surface electromyography (sEMG) to find coordinative strategies associated with peak over-ground sprint velocity using machine learning. We recruited 40 healthy university age sprint-based athletes from a variety of athletic backgrounds. IMU and sEMG data were used as inputs into a principal components analysis (PCA) to observe major modes of variation (i.e., PC scores). PC scores were then used as inputs into a stepwise multivariate linear regression model to derive associations of each mode of variation with peak sprint velocity. Both the kinematic (R 2 = 0.795) and sEMG data (R 2 = 0.586) produced significant multivariate linear regression models. The PCs that were selected as inputs into the multivariate linear regression model were reconstructed using multi-component reconstruction to produce a representation of the whole-body movement pattern and changes in the sEMG waveform associated with faster sprint velocities. The findings of this work suggest that distinct features are associated with faster sprint velocity. These include the timing of the contralateral arm and leg swing, stance leg kinematics, dynamic trunk extension at toe-off, asymmetry between the right and left swing side leg and a phase shift feature of the posterior chain musculature. These results demonstrate the utility of data-driven frameworks in identifying different coordinative features that are associated with a movement outcome. Using our framework, coaches and biomechanists can make decisions based on objective movement information, which can ultimately improve an athlete's performance.

Interpersonal synchronization of spontaneously generated body movements

Interpersonal movement synchrony (IMS) is central to social behavior in several species. In humans, IMS is typically studied using structured tasks requiring participants to produce specific body movements. Instead, spontaneously generated (i.e., not instructed) movements have received less attention. To test whether spontaneous movements synchronize interpersonally, we recorded full-body kinematics from dyads of participants who were only asked to sit face-to-face and to look at each other. We manipulated interpersonal (i)visual contact and (ii) spatial proximity. We found that spontaneous movements synchronized across participants only when they could see each other and regardless of interpersonal spatial proximity. This synchronization emerged very rapidly and did not selectively entail homologous body parts (as in mimicry); rather, the synchrony generalized to nearly all possible combinations of body parts. Hence, spontaneous behavior alone can lead to IMS. More generally, our results highlight that IMS can be studied under natural and unconstrained conditions.

A Non-Laboratory Gait Dataset of Full Body Kinematics and Egocentric Vision

In this manuscript, we describe a unique dataset of human locomotion captured in a variety of out-of-the-laboratory environments captured using Inertial Measurement Unit (IMU) based wearable motion capture. The data contain full-body kinematics for walking, with and without stops, stair ambulation, obstacle course navigation, dynamic movements intended to test agility, and negotiating common obstacles in public spaces such as chairs. The dataset contains 24.2 total hours of movement data from a college student population with an approximately equal split of males to females. In addition, for one of the activities, we captured the egocentric field of view and gaze of the subjects using an eye tracker. Finally, we provide some examples of applications using the dataset and discuss how it might open possibilities for new studies in human gait analysis.

Identifying special operative trainees at-risk for musculoskeletal injury using full body kinematics.

Introduction: Non-combat musculoskeletal injuries (MSKIs) during military training significantly impede the US military's functionality, with an annual cost exceeding $3.7 billion. This study aimed to investigate the effectiveness of a markerless motion capture system and full-body biomechanical movement pattern assessments to predict MSKI risk among military trainees. Methods: A total of 156 male United States Air Force (USAF) airmen were screened using a validated markerless biomechanics system. Trainees performed multiple functional movements, and the resultant data underwent Principal Component Analysis and Uniform Manifold And Projection to reduce the dimensionality of the time-dependent data. Two approaches, semi-supervised and supervised, were then used to identify at-risk trainees. Results: The semi-supervised analysis highlighted two major clusters with trainees in the high-risk cluster having a nearly five times greater risk of MSKI compared to those in the low-risk cluster. In the supervised approach, an AUC of 0.74 was produced when predicting MSKI in a leave-one-out analysis. Discussion: The application of markerless motion capture systems to measure an individual's kinematic profile shows potential in identifying MSKI risk. This approach offers a novel way to proactively address one of the largest non-combat burdens on the US military. Further refinement and wider-scale implementation of these techniques could bring about substantial reductions in MSKI occurrence and the associated economic costs.

Relationships between kinematic characteristics and ratio of forces during initial sprint acceleration

ABSTRACT In track sprinting, acceleration performance is largely determined by the ability to generate a high ratio of forces (RF), but the technical features associated with this remain unknown. This study therefore investigated the relationships between selected kinematic characteristics and RF during the initial acceleration phase. Fourteen male sprinters completed two maximal 60 m sprints from a block start. Full-body kinematic and external kinetic data were obtained from the first four steps, and the relationships between selected kinematic characteristics and mean RF over the first four steps were determined. Placing the stance foot further behind (or less far in front of) the whole-body centre of mass at touchdown was significantly related to greater RF (r = −0.672), and more anterior orientation of the proximal end of the foot (r = −0.724) and shank (r = −0.764) segments at touchdown were also significantly related to greater RF. Following touchdown, greater ankle dorsiflexion range of motion during early stance was significantly related to greater RF (r = 0.728). When aiming to enhance RF during initial acceleration, practitioners should be encouraged to focus on lower leg configurations when manipulating touchdown distance, and the role of dorsiflexion during early stance is also an important consideration.

On-Field Biomechanical Assessment of High and Low Dive in Competitive 16-Year-Old Goalkeepers through Wearable Sensors and Principal Component Analysis.

Diving saves are the main duty of football goalkeepers. Few biomechanical investigations of dive techniques have been conducted, none in a sport-specific environment. The present study investigated the characteristics of goalkeepers’ dive in preferred (PS) and non-preferred (nPS) side through an innovative wearables-plus-principal-component analysis (PCA) approach. Nineteen competitive academy goalkeepers (16.5 ± 3.0 years) performed a series of high and low dives on their PS and nPS. Dives were performed in a regular football goal on the pitch. Full-body kinematics were collected through 17 wearable inertial sensors (MTw Awinda, Xsens). PCA was conducted to reduce data dimensionality (input matrix 310,878 datapoints). PCA scores were extracted for each kinematic variable and compared between PS and nPS if their explained variability was >5%. In high dive, participants exhibited greater hip internal rotation and less trunk lateral tilt (p < 0.047, ES > 0.39) in PS than nPS. In low dives, players exhibited greater ipsilateral hip abduction dominance and lower trunk rotation (p < 0.037, ES > 0.40) in PS than nPS. When diving on their nPS, goalkeepers adopted sub-optimal patterns with less trunk coordination and limited explosiveness. An ecological testing through wearables and PCA might help coaches to inspect relevant diving characteristics and improve training effectiveness.

The effect of vibration on kinematics and muscle activation during cycling

ABSTRACT Vibration has the potential to compromise performance in cycling. This study aimed to investigate the effects of vibration on full-body kinematics and muscle activation time series. Nineteen male amateur cyclists (mass 74.9 ± 5.9 kg, body height 1.82 ± 0.05 m, Vo2max 57 ± 9 ml/kg/min, age 27 ± 7 years) cycled (216 ± 16 W) with (Vib) and without (NoVib) vibration. Full-body kinematics and muscle activation time series were analysed. Vibration did not affect lower extremity joint kinematics significantly. The pelvic rotated with vibration towards the posterior direction (NoVib: 22.2 ± 4.8°, Vib: 23.1 ± 4.7°, p = 0.016, d = 0.20), upper body lean (NoVib: 157.8 ± 3.0°, Vib: 158.9 ± 3.4°, p = 0.001, d = 0.35) and elbow flexion (NoVib: 27.0 ± 8.2°, Vib: 29.4 ± 9.0°, p = 0.010, d = 0.28) increased significantly with vibration. The activation of lower extremity muscles (soleus, gastrocnemius lat., tibialis ant., vastus med., rectus fem., biceps fem.) increased significantly during varying phases of the crank cycle due to vibration. Vibration increased arm and shoulder muscle (triceps brachii, deltoideus pars scapularis) activation significantly over almost the entire crank cycle. The co-contraction of knee and ankle flexors and extensors (vastus med. – gastrocnemius lat., vastus med. – biceps fem., soleus – tibialis ant.) increased significantly with vibration. In conclusion vibrations influence main tasks such as propulsion and upper body stabilization on the bicycle to a different extent. The effect of vibration on the task of propulsion is limited due to unchanged lower body kinematics and only phase-specific increases of muscular activation during the crank cycle. Additional demands on upper body stabilization are indicated by adjusted upper body kinematics and increased muscle activation of the arm and shoulder muscles during major parts of the cranking cycle.

Do healthy athletes exhibit at-risk biomechanics for anterior cruciate ligament injury during pivoting movements?

ABSTRACT A consistent injury mechanism involving multiple joints has been highlighted in athletes experiencing anterior cruciate ligament (ACL) rupture. However, if and to what extent healthy athletes incur an unsafe biomechanical profile during high-dynamics movements is unknown. The present study aimed to investigate the occurrence of the ACL risk profile in a competitive pivoting sports population.Thirty-four athletes (22.8 ± 4.1 y) performed a frontal deceleration and a change of direction at 90°. Full-body kinematics was collected through 15 wearable inertial sensors (Awinda, Xsens). Nine ACL risk factors were defined based on four categories: limited lower limb flexion, valgus collapse, foot rotation and trunk rotation. A movement trial was considered ‘at-risk’ in the presence of at least 5 simultaneous risk factors. The rate of athletes with at-risk movements was assessed and multivariate regression for associated outcomes was conducted.The overall rate of injury profile occurrence was 9–12%. The injury profile was identified at least in one trial in 24 athletes (71%) and three trials in 5 athletes (15%). Significant associations were found for higher approaching speed (OR = 4.3) and female sex (OR = 4.8). A large occurrence of the typical ACL injury biomechanical profile was noticed. Large screenings are advisable to identify at-risk athletes and promote preventative strategies.

The biomechanics of maintaining effective force application across cycling positions

Cyclists are known to change their cycling position to reduce aerodynamic drag. Research has shown that this compromises their physical capacity to perform, but there is considerable inter-individual variability present. Proposed training specificity effects by cycling position do not explain all of the observations in the literature, so a search for other influencing parameters is warranted and might help practitioners to further optimise cycling position. This study captured full-body kinematics and 2D crank forces in 19 Time-Trial (TT) and 36 Road trained cyclists. Data in preferred and standardised cycling positions were systematically evaluated and showed that, amongst other kinematic differences, TT cyclists prefer a more forwardly positioned hip joint over Road cyclists. Despite their different setup, no effects in mechanical effectiveness were seen between the groups when tested in their preferred position. Across the standardised positions, the full cohort showed lower mechanical effectiveness when lowering trunk angle. However, significant group by position interactions showed this effect to be less extreme for the TT group. Kinematic data revealed that an increased pelvic tilt resulted in increased hip flexion and induced a more dorsiflexed ankle angle. In addition, linear hip position acutely responded to positional changes by moving forwards when the trunk angle was lowered. A more forwards hip position is thus associated with maintaining a better mechanical effectiveness in aerodynamic cycling positions. This suggests that there is potential to mitigate the effect of negative crank forces in aerodynamic positions by acutely adjusting the saddle placement to facilitate linear hip movement.

Effects of age and surface instability on the control of the center of mass.

During standing, posture can be controlled by accelerating the Center of Mass (CoM) through shifting the center of pressure (CoP) within the base of support by applying ankle moments ("CoP mechanism"), or through the "counter-rotation mechanism", i.e., changing the angular momentum of segments around the CoM to change the direction of the ground reaction force. Postural control develops over the lifespan; at both the beginning and the end of the lifespan adequate postural control appears more challenging. In this study, we aimed to assess mediolateral balance performance and the related use of the postural control mechanisms in children, older adults and younger adults when standing on different (unstable) surfaces. Sixteen pre-pubertal children (6-9y), 17 younger adults (18-24y) and eight older adults (65-80y) performed bipedal upright standing trials of 16s on a rigid surface and on three balance boards that could freely move in the frontal plane, varying in height (15-19cm) of the surface of the board above the point of contact with the floor. Full body kinematics (16 segments, 48 markers, using SIMI 3D-motion analysis system (GmbH) and DeepLabCut and Anipose) were retrieved. Performance related outcome measures, i.e., the number of trials with balance loss and the Root Mean Square (RMS) of the time series of the CoM acceleration, the contributions of the CoP mechanism and the counter-rotation mechanism to the CoM acceleration in the frontal plane and selected kinematic measures, i.e. the orientation of the board and the head and the Mean Power Frequency (MPF) of the balance board orientation and the CoM acceleration were determined. Balance loss only occurred when standing on the highest balance board, twice in one older adult once in one younger adult. In children and older adults, the RMS of the CoM accelerations were larger, corresponding to poorer balance performance. Across age groups and conditions, the contribution of the CoP mechanism to the total CoM acceleration was much larger than that of the counter-rotation mechanisms, ranging from 94% to 113% vs 23% to 38% (with totals higher than 100% indicating opposite effects of both mechanisms). Deviations in head orientation were small compared to deviations in balance board orientation. We suggest that the CoP mechanism is dominant, since the counter-rotation mechanism would conflict with stabilizing the orientation of the head in space.

The effect of constraining mediolateral ankle moments and foot placement on the use of the counter-rotation mechanism during walking

During walking, the center of mass (CoM) position can be controlled relative to the base of support by shifts of the center of pressure through modulation of foot placement and ankle moments (CoP-mechanism). An additional mechanism is the counter-rotation mechanism, i.e. changing the angular momentum of segments around the CoM to change the direction of the ground reaction force. It is unknown if, and how, humans use the counter-rotation mechanism to accelerate the CoM during walking and how this interacts with the CoP-mechanism. Thirteen healthy adults walked on a treadmill, while full-body kinematic and force plate data were obtained. The contributions of the CoP and the counter-rotation mechanisms to CoM-acceleration during steady-state walking, walking on LesSchuh (i.e. constraining mediolateral CoP shifts underneath the stance foot) and walking on LesSchuh at 50% of normal step width, constraining both foot placement and ankle mechanisms (LesSchuh50%) were calculated. The within-stride variance in CoM-acceleration due to the CoP-mechanism was smaller and the within-stride variance in CoM-acceleration due to the counter-rotation mechanism was larger during LesSchuh50% compared to steady-state walking. This suggests that the counter-rotation mechanism is used to stabilize gait when needed, but the CoP-mechanism was the main contributor to the total CoM-acceleration. The use of the counter-rotation mechanism may be limited, because angular accelerations ultimately need to be reversed and because of interference with other task constraints, such as head stabilization and preventing interference with the gait pattern.

Muscle forces and fascicle behavior during three hamstring exercises.

Knowledge about muscular forces and fascicle behavior during hamstring exercises can optimize exercise prescription, but information on these outcomes across different exercises is lacking. We aimed to characterize and compare lower‐limb muscle forces and biceps femoris long head muscle fascicle behavior between three hamstring exercises: the Nordic hamstring curl (NHC), single‐leg Roman chair (RCH), and single‐leg deadlift (DL). Ten male participants performed the exercises while full‐body kinematics, ground reaction forces, surface muscle activation, and biceps femoris long head fascicle behavior were measured. Mean fascicle length was highest in the DL, followed by the RCH and NHC. Fascicle lengthening was higher in the NHC compared with the RCH and DL, with no difference between the RCH and DL. Biceps femoris short and long head, semitendinosus, and semimembranosus peak forces were generally higher in the NHC compared with the RCH and DL, while mean forces during the eccentric phase were generally not different between the NHC and RCH. Peak forces in the NHC coincided with low biceps femoris long head and semimembranosus muscle activation. The NHC generally has the highest peak hamstring muscle forces and results in more fascicle lengthening when compared to the DL and RCH. The NHC may therefore be most effective to promote increases in fascicle length. While the NHC may be effective to promote biceps femoris short head and semitendinosus strength adaptations, the RCH and DL may be more effective to promote strength increases in the biceps femoris long head and semimembranosus.

Contribution of arm movements to balance recovery after tripping in older adults

Falls are common in daily life, often caused by trips and slips and, particularly in older adults, with serious consequences. Although arm movements play an important role in balance control, there is limited research into the role of arm movements during balance recovery after tripping in older adults. We investigated how older adults use their arms to recover from a trip and the difference in the effects of arm movements between fallers (n = 5) and non-fallers (n = 11).Sixteen older males and females (69.7 ± 2.3 years) walked along a walkway and were occasionally tripped over suddenly appearing obstacles. We analysed the first trip using a biomechanical model based on full-body kinematics and force-plate data to calculate whole body orientation during the trip and recovery phase. With this model, we simulated the effects of arm movements at foot-obstacle impact and during trip recovery on body orientation.Apart from an increase in sagittal plane forward body rotation at touchdown in fallers, we found no significant differences between fallers and non-fallers in the effects of arm movements on trip recovery. Like earlier studies in young adults, we found that arm movements during the recovery phase had most favourable effects in the transverse plane: by delaying the transfer of angular momentum of the arms to the body, older adults rotated the tripped side more forward thereby allowing for a larger recovery step. Older adults that are prone to falling might improve their balance recovery after tripping by learning to prolong ongoing arm movements.

Pitching Mechanics and the Relationship to Accuracy in Professional Baseball Pitchers

Background: Biomechanical predictors of pitching accuracy are underevaluated in baseball research. It is unclear how pitchers with higher accuracy differ in terms of kinematics and upper extremity kinetics. Purpose: To differentiate high- and low-accuracy professional pitchers by full-body kinematic and upper extremity kinetic parameters. Study Design: Descriptive laboratory study. Methods: In total, 121 professional baseball pitchers threw 8 to 12 fastballs while assessed with motion-capture technology (480 Hz). Pitchers were divided into high-accuracy (n = 33), moderate-accuracy (n = 52), and low-accuracy (n = 36) groups based on the absolute center deviation of each pitcher’s average pitch to the center of the pitching chart by greater or less than 0.5 SD from the mean, respectively. The 95% confidence ellipses with comparisons of major and minor radii and pitching probability density grids were constructed. Analysis of variance was used to compare kinematic and kinetic values between groups. Results: The absolute center deviation (14.5% ± 6.7% vs 33.5% ± 3.7% grid width; P < .001) was significantly lower in the high-accuracy compared with the low-accuracy group, with no significant difference in ball velocity (38.0 ± 1.7 vs 38.5 ± 2.0 m/s; P = .222). Lead knee flexion at ball release (30.6°± 17.8° vs 40.1°± 16.3°; P = .023) was significantly less for the high-accuracy pitchers. Peak normalized shoulder internal rotation torque (5.5% ± 1.0% vs 4.9% ± 0.7% body weight [BW] × body height [BH]; P = .008), normalized elbow varus torque (5.4% ± 1.0% vs 4.8% ± 0.7% BW × BH; P = .008), and normalized elbow medial force (42.9% ± 7.3% vs 38.6% ± 6.2% BW; P = .024) were significantly greater for the low-accuracy group compared with the high-accuracy group. Conclusion: Professional pitchers with increased accuracy experienced decreased throwing arm kinetics. These pitchers had increased lead knee extension at later stages of the pitch, potentially providing more stable engagement with the ground and transference of kinetic energy to the upper extremities. Professional pitchers can consider increasing lead knee extension at the final stages of the pitch to improve the accuracy of their throws and mitigate elbow varus torque. Clinical Relevance: Increased elbow varus torque, shoulder internal rotation torque, and elbow medial force in less accurate pitchers may contribute to increased injury risk in this group.

Continuous and Unified Modeling of Joint Kinematics for Multiple Activities

Intuitive control of powered prosthetic lower limbs is still an open-ended research goal. Current controllers employ discrete locomotion modes for well-defined and frequently encountered scenarios such as stair ascent, stair descent, or ramps. Non-standard movements such as <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">side-shuffling into cars and avoiding obstacles</b> are challenging to powered limb users. Human locomotion is a continuous motion comprising rhythmic and non-rhythmic movements, fluidly adapting to the environment. It exhibits strong inter-joint coordination and the movement of a single joint can be largely predicted based on the movement of the rest of the body. We explore a continuous and unified kinematics estimation strategy for a wide variety of movements without the need for labeled examples. Our data-driven approach uses natural body motion from the intact limbs and trunk to generate a kinematic reference trajectory for prosthetic joints. Wearable sensors were worn by 63 subjects without disabilities to record full-body kinematics during typical scenarios (flat ground and stairs), and non-rhythmic and atypical movements (side shuffles, weaving through cones, backward walking). A Recurrent Neural Network (RNN) was trained to predict right ankle and knee kinematics from the kinematics of other joints as inputs. Results were assessed on 3 different test subjects previously unseen by the network. All predictions had a RMSE of less than 7.5 degrees and a high correlation across activities. These offline predictions were robust to subject-specific variations such as walking speed and step length. Additionally, to test the feasibility of using a data-driven reference towards prosthetic control in real-time, a systems test was designed with a single participant. The controller acquired live kinematics, generated predictions using a pre-trained neural network, and demonstrated the capability to actuate the knee joint of a powered prosthesis for the treadmill walking task.

Ankle muscles drive mediolateral center of pressure control to ensure stable steady state gait

During steady-state walking, mediolateral gait stability can be maintained by controlling the center of pressure (CoP). The CoP modulates the moment of the ground reaction force, which brakes and reverses movement of the center of mass (CoM) towards the lateral border of the base of support. In addition to foot placement, ankle moments serve to control the CoP. We hypothesized that, during steady-state walking, single stance ankle moments establish a CoP shift to correct for errors in foot placement. We expected ankle muscle activity to be associated with this complementary CoP shift. During treadmill walking, full-body kinematics, ground reaction forces and electromyography were recorded in thirty healthy participants. We found a negative relationship between preceding foot placement error and CoP displacement during single stance; steps that were too medial were compensated for by a lateral CoP shift and vice versa, steps that were too lateral were compensated for by a medial CoP shift. Peroneus longus, soleus and tibialis anterior activity correlated with these CoP shifts. As such, we identified an (active) ankle strategy during steady-state walking. As expected, absolute explained CoP variance by foot placement error decreased when walking with shoes constraining ankle moments. Yet, contrary to our expectations that ankle moment control would compensate for constrained foot placement, the absolute explained CoP variance by foot placement error did not increase when foot placement was constrained. We argue that this lack of compensation reflects the interdependent nature of ankle moment and foot placement control. We suggest that single stance ankle moments do not only compensate for preceding foot placement errors, but also assist control of the subsequent foot placement. Foot placement and ankle moment control are ‘caught’ in a circular relationship, in which constraints imposed on one will also influence the other.

A Dataset of Human Motion and Muscular Activities in Manual Material Handling Tasks for Biomechanical and Ergonomic Analyses

Manual Material Handling (MMH) activities represent a large portion of the workers’ tasks in the tertiary sector. The ability to monitor, model, and predict human behaviours are crucial to both the design of productive human-robot collaboration and an efficient physical exposure assessment system that can prevent Work-related Musculoskeletal Disorders (WMSDs), with the ultimate goal of improving workers’ quality of life. The combined use of wearable sensors and machine learning (ML) techniques can fulfil these purposes. Inertial Measurement Units (IMUs) and surface Electromyography (sEMG) allow collecting kinematic data and muscular activity information that can be used for biomechanical analyses, ergonomic risk assessment, and as input of ML algorithms aimed at joint torque/load estimation, and Human Activity Recognition (HAR). The latter needs a large amount of annotated training samples, and the use of publicly available datasets is the way forward. Nowadays, the majority of them concern Activities of Daily Life (ADLs) and, including only kinematic data, have limited applications. This paper presents a fully labelled dataset of working activities that include full-body kinematics from 17 IMUs and upper limbs sEMG data from 16 channels. Fourteen subjects participated in the experiment performed in laboratory settings for overall 18.6 hours of recordings. The activities are divided into two sets. The first includes lifting, lowering, and carrying objects, MMH activities suitable for ergonomic risk assessment, and HAR. The second includes isokinetic arm movements, mainly targeting load and joint torque estimation.

Neuromuscular Age-Related Adjustment of Gait When Moving Upwards and Downwards.

Locomotor movements are accommodated to various surface conditions by means of specific locomotor adjustments. This study examined underlying age-related differences in neuromuscular control during level walking and on a positive or negative slope, and during stepping upstairs and downstairs. Ten elderly and eight young adults walked on a treadmill at two different speeds and at three different inclinations (0°, +6°, and −6°). They were also asked to ascend and descend stairs at self-selected speeds. Full body kinematics and surface electromyography of 12 lower-limb muscles were recorded. We compared the intersegmental coordination, muscle activity, and corresponding modifications of spinal motoneuronal output in young and older adults. Despite great similarity between the neuromuscular control of young and older adults, our findings highlight subtle age-related differences in all conditions, potentially reflecting systematic age-related adjustments of the neuromuscular control of locomotion across various support surfaces. The main distinctive feature of walking in older adults is a significantly wider and earlier activation of muscles innervated by the sacral segments. These changes in neuromuscular control are reflected in a reduction or lack of propulsion observed at the end of stance in older adults at different slopes, with the result of a delay in the timing of redirection of the centre-of-mass velocity and of an unanticipated step-to-step transition strategy.