Lower limb musculoskeletal modeling during normal walking, one-legged forward hopping, side jumping and knee flexion:A Validation study of the AnyBody Modeling System for optimizing Anterior Cruciate Ligament Reconstruction

Computermodel kan krachten op kniegewricht goed voorspellen Het AMS-model, een computermodel dat menselijke bewegingen kan nadoen en voorspellen, kan gebruikt worden om de krachten die tijdens het lopen op het kniegewricht werken accuraat te voorspellen. Dat concludeert Adhi Wibawa in zijn promotieonderzoek. Hij testte het AMS-model met behulp van gezonde proefpersonen. Om te bestuderen hoe ons lichaam biomechanisch gezien werkt, worden er computermodellen ontwikkeld die de menselijke bewegingen nauwkeurig kunnen nadoen. Een van die computermodellen is het AMS-model (Anybody Modeling System). Wibawa testte dit model voor de loopbeweging in knie, enkel en voet. De promovendus deed dat door de bewegingen van tien gezonde proefpersonen tijdens verschillende loopactiviteiten (normaal lopen, springen op één been, opzij springen en buigen van de knie) te filmen en door het AMS-model vervolgens spieractiviteit te laten voorspellen op basis van de gefilmde beelden. Die voorspellingen konden vervolgens in de proefpersonen gecontroleerd worden door de elektrische activiteit te meten van de spieren en de zenuw die de spier aanstuurt. Wibawa concludeert dat het AMS-model de bewegingen in de enkel en de voet nog niet goed kan voorspellen. Dat komt waarschijnlijk doordat het model werkt met een vereenvoudigde versie van deze lichaamsdelen. Wel bleek het model goed in staat om te voorspellen welke krachten er op het kniegewricht werken tijdens normaal lopen. Door het systeem te verbeteren, zal de voorspellende kracht toenemen

A trap motion in validating muscle activity prediction from musculoskeletal model using EMG

Musculoskeletal modeling nowadays is becoming the most common tool for studying and analyzing human motion. Besides its potential in predicting muscle activity and muscle force during active motion, musculoskeletal modeling can also calculate many important kinetic data that are difficult to measure in vivo, such as joint force or ligament force. This paper will validate muscle activity predicted by the model during a static motion like knee flexion motion (squat motion). In this experiment, knee flexion motion was performed by 5 healthy subjects and modeled by using Gait Lower Extremity model from AnyBody Modeling System (AMS). Eight lower limb muscle activity prediction from the model will be validated by 8 EMG electrodes that measured the same muscles during squat motion. Muscle activity pattern and the position of onset would be used as a key factor in this validation study. Pearson correlation coefficient will be used to compare the pattern of both graphs. Knee joint force prediction from the model will also be compared with the literature studies. The result showed that 3 muscles showed high correlation coefficient, while the other 4 muscles showed slightly medium and one showed low correlation. Time delay of muscle activation between the model and EMG was recorded from Vastus Medialis muscle (18.38 ms) and Vastus Lateralis (22.8 ms), with muscle activation from the model was late compared to EMG. In conclusion, this statistical study has shown some detail differences between EMG and muscle activity prediction from the model. Knee flexion motion can be used as a trap motion when validating muscle activity of a musculoskeletal model, because the model will activate muscle activity based on motion data of markers, while in knee-flexed position, there was no marker’s movement, but the EMG was highly active due to the posture of the subjects in maintaining the knee-flexed position. However, the knee compressive force prediction from the model has showed positive confirmation from the literatures

Improving mechanical and neuromuscular deficits following anterior cruciate ligament reconstruction

Despite consistent resolution of knee laxity and return to physical activity following ACL reconstruction, a growing body of evidence implicates impaired weight acceptance strategies as frequent primary drivers in a host of poor long-term outcomes. Most egregiously, the majority of the people with ACL reconstruction will show radiographic evidence of knee osteoarthritis within 15 years of surgery. Abnormal compression of the knee joint due to impaired knee flexion during weight acceptance is exacerbated by a tendency toward concomitant co-contraction of the knee musculature. Despite a plethora of proposed training paradigms, performance deficits after ACL reconstruction prove particularly resistant to enduring change. The studies included in this dissertation examine the mechanical and neuromuscular impairments in weight acceptance during landing from a jump that underlie the limitations to success following ACL reconstruction. A path toward improving functional recovery by treating impairments in landing is suggested and a novel training approach is tested. First, a cross-sectional study examines both the impaired patterns of neuromuscular recruitment in people who have returned to sporting activity following ACL reconstruction and their relationship to mechanics in landing. A pre-test/post-test laboratory study further examines the relationship between imposed changes in landing mechanics and co-contraction between the hamstrings and the quadriceps musculature. Clarification of neuromuscular activation and coordination impairments allows development of specific treatment techniques. To address limitations in current practice, a new device, the Bodyweight Reduction Instrument to Deliver Graded Exercise (BRIDGE), is validated in a third study, in which the effects of body weight support on the mechanics of repetitive single leg hopping are tested. The use of the BRIDGE is then described in a clinical case study. Finally, a randomized clinical trial determines whether high volume jump training with reduced loading intensity via body weight support will preferentially enhance motor learning for improved coordination of the neuromuscular system during high demand tasks such as single leg landing. This dissertation thereby advances the science of rehabilitation to more effectively target mechanical and neuromuscular impairments that devastatingly contribute to the risk of re-injury and early onset osteoarthritis following ACL reconstruction

An investigation into perception of change in the foot-floor interface during repeated stretch-shortening cycles

Proprioceptive input is critical for normal and safe movement. There exists a gap in the literature regarding the assessment of proprioceptive function during dynamic tasks of the lower limb. To fill this gap, the present thesis has investigated perception of change in the foot-floor interface during repeated stretch-shortening cycles. This doctoral research serves as a foundation for considering proprioception as it pertains to dynamic function at the ankle

Neuromuscular markers of non-contact anterior cruciate ligament injury during dynamic tasks

This thesis explores the added value of neuromuscular markers of non-contact ACL injury risk. First, a systematic review was conducted to establish the existing evidence from the literature. The outcome of this review served to select candidate neuromuscular observations to be included in a large-scale prospective study. The two main risk factors that were found to be supported with some evidence were the (i) hamstrings to quadriceps ratio (HQR) and (ii) a unique neuromuscular activation pattern during side cutting. These parameters were included in a prospective cohort study to establish injury risk factors. After two years of data collection we still had not seen any non-contact ACL injuries in our study sample. As a fall back plan, the collected database was explored in search of evidence that can help support previous findings. First, we showed that quadriceps strength meaningfully affects HQRs (as quadriceps gets stronger, HQR value gets lower), introducing bias when profiling individuals for injury risk. We demonstrated how through an allometric approach this bias can be removed for future investigation into HQR as a risk factor for injury. Second, we evaluated whether HQR explains neuromuscular activations of the knee musculature during the execution a dynamic task. We found that variations between individuals in muscle (co-)activations were not explained by differences in muscle strength or HQR. Overall, through this work we have obtained a clear overview on the limited evidence on neuromuscular risk factors of non-contact ACL injury, provided in-depth insights into HQR as a measure of muscular capacity, and demonstrated how one should be careful in linking observations of muscular capacity with observations of muscular activation and vice versa

Advancing Musculoskeletal Robot Design for Dynamic and Energy-Efficient Bipedal Locomotion

Achieving bipedal robot locomotion performance that approaches human performance is a challenging research topic in the field of humanoid robotics, requiring interdisciplinary expertise from various disciplines, including neuroscience and biomechanics. Despite the remarkable results demonstrated by current humanoid robots---they can walk, stand, turn, climb stairs, carry a load, push a cart---the versatility, stability, and energy efficiency of humans have not yet been achieved. However, with robots entering our lives, whether in the workplace, in clinics, or in normal household environments, such improvements are increasingly important. The current state of research in bipedal robot locomotion reveals that several groups have continuously demonstrated enhanced locomotion performance of the developed robots. But each of these groups has taken a unilateral approach and placed the focus on only one aspect, in order to achieve enhanced movement abilities;---for instance, the motion control and postural stability or the mechanical design. The neural and mechanical systems in human and animal locomotion, however, are strongly coupled and should therefore not be treated separately. Human-inspired musculoskeletal design of bipedal robots offers great potential for enhanced dynamic and energy-efficient locomotion but also imposes major challenges for motion planning and control. In this thesis, we first present a detailed review of the problems related to achieving enhanced dynamic and energy-efficient bipedal locomotion, from various important perspectives, and examine the essential properties of the human locomotory apparatus. Subsequently, existing insights and approaches from biomechanics, to understand the neuromechanical motion apparatus, and from robotics, to develop more human-like robots that can move in our environment, are discussed in detail. These thorough investigations of the interrelated essential design decisions are used to develop a novel design for a musculoskeletal bipedal robot, BioBiped1, such that, in the long term, it is capable of realizing dynamic hopping, running, and walking motions. The BioBiped1 robot features a highly compliant tendon-driven actuation system that mimics key functionalities of the human lower limb system. In experiments, BioBiped1's locomotor function for the envisioned gaits is validated globally. It is shown that the robot is able to rebound passively, store and release energy, and actively push off from the ground. The proof of concept of BioBiped1's locomotor function, however, marks only the starting point for our investigations, since this novel design concept opens up a number of questions regarding the required design complexity for the envisioned motions and the appropriate motion generation and control concept. For this purpose, a simulator specifically designed for the requirements of musculoskeletally actuated robotic systems, including sufficiently realistic ground reaction forces, is developed. It relies on object-oriented design and is based on a numerical solver, without model switching, to enable the analysis of impact peak forces and the simulation of flight phases. The developed library also contains the models of the actuated and passive mono- and biarticular elastic tendons and a penalty-based compliant contact model with nonlinear damping, to incorporate the collision, friction, and stiction forces occurring during ground contact. Using these components, the full multibody system (MBS) dynamics model is developed. To ensure a sufficiently similar behavior of the simulated and the real musculoskeletal robot, various measurements and parameter identifications for sub-models are performed. Finally, it is shown that the simulation model behaves similarly to the real robot platform. The intelligent combination of actuated and passive mono- and biarticular tendons, imitating important human muscle groups, offers tremendous potential for improved locomotion performance but also requires a sophisticated concept for motion control of the robot. Therefore, a further contribution of this thesis is the development of a centralized, nonlinear model-based method for motion generation and control that utilizes the derived detailed dynamics models of the implemented actuators. The concept is used to realize both computer-generated hopping and human jogging motions. Additionally, the problem of appropriate motor-gear unit selection prior to the robot's construction is tackled, using this method. The thesis concludes with a number of simulation studies in which several leg actuation designs are examined for their optimality with regard to systematically selected performance criteria. Furthermore, earlier paradoxical biomechanical findings about biarticular muscles in running are presented and, for the first time, investigated by detailed simulation of the motion dynamics. Exploring the Lombard paradox, a novel reduced and energy-efficient locomotion model without knee extensor has been simulated successfully. The models and methods developed within this thesis, as well as the insights gained, are already being employed to develop future prototypes. In particular, the optimal dimensioning and setting of the actuators, including all mono- and biarticular muscle-tendon units, are based on the derived design guidelines and are extensively validated by means of the simulation models and the motion control method. These developments are expected to significantly enhance progress in the field of bipedal robot design and, in the long term, to drive improvements in rehabilitation for humans through an understanding of the neuromechanics underlying human walking and the application of this knowledge to the design of prosthetics