TKA patients with unsatisfying knee function show changes in neuromotor synergy pattern but not joint biomechanics

Nearly 20% of patients who have undergone total knee arthroplasty (TKA) report persistent poor knee function. This study explores the idea that, despite similar knee joint biomechanics, the neuro-motor synergies may be different between high-functional and low-functional TKA patients. We hypothesized that (1) high-functional TKA recruit a more complex neuro-motor synergy pattern compared to low-functional TKA and (2) high-functional TKA patients demonstrate more stride-to-stride variability (flexibility) in their synergies. Gait and electromyography (EMG) data were collected during level walking for three groups of participants: (i) high-functional TKA patients (n = 13); (ii) low-functional TKA patients (n = 13) and (iii) non-operative controls (n = 18). Synergies were extracted from EMG data using non-negative matrix factorization. Analysis of variance and Spearman correlation analyses were used to investigate between-group differences in gait and neuro-motor synergies. Results showed that synergy patterns were different among the three groups. Control subjects used 5–6 independent neural commands to execute a gait cycle. High functional TKA patients used 4–5 independent neural commands while low-functional TKA patients relied on only 2–3 independent neural commands to execute a gait cycle. Furthermore, stride-to-stride variability of muscles’ response to the neural commands was reduced up to 15% in low-functional TKAs compared to the other two groups

Neck loading in high performance combat pilots during aerial combat manoeuvres and specific neck strengthening exercises

Background: Neck pain and injury is a common occurrence in high performance combat pilots (HPCP) around the world. The cause of this has been attributed to exposure to the unavoidable high mechanical loading related to the neck being positioned in non-neutral head postures whilst being exposed to moderate to high +Gz levels. Specific neck conditioning exercises have been proposed as being a possible method to decrease the incidence of neck pain and injury in this population. However, there has been sparsely published research examining the suitability of selected exercises for HPCP who participate in regular aerial combat manoeuvres (ACM)

Simulation And Control At the Boundaries Between Humans And Assistive Robots

Human-machine interaction has become an important area of research as progress is made in the fields of rehabilitation robotics, powered prostheses, and advanced exercise machines. Adding to the advances in this area, a novel controller for a powered transfemoral prosthesis is introduced that requires limited tuning and explicitly considers energy regeneration. Results from a trial conducted with an individual with an amputation show self-powering operation for the prosthesis while concurrently attaining basic gait fidelity across varied walking speeds. Experience in prosthesis development revealed that, though every effort is made to ensure the safety of the human subject, limited testing of such devices prior to human trials can be completed in the current research environment. Two complementary alternatives are developed to fill that gap. First, the feasibility of implementing impulse-momentum sliding mode control on a robot that can physically replace a human with a transfemoral amputation to emulate weight-bearing for initial prototype walking tests is established. Second, a more general human simulation approach is proposed that can be used in any of the aforementioned human-machine interaction fields. Seeking this general human simulation method, a unique pair of solutions for simulating a Hill muscle-actuated linkage system is formulated. These include using the Lyapunov-based backstepping control method to generate a closed-loop tracking simulation and, motivated by limitations observed in backstepping, an optimal control solver based on differential flatness and sum of squares polynomials in support of receding horizon controlled (e.g. model predictive control) or open-loop simulations. v The backstepping framework provides insight into muscle redundancy resolution. The optimal control framework uses this insight to produce a computationally efficient approach to musculoskeletal system modeling. A simulation of a human arm is evaluated in both structures. Strong tracking performance is achieved in the backstepping case. An exercise optimization application using the optimal control solver showcases the computational benefits of the solver and reveals the feasibility of finding trajectories for human-exercise machine interaction that can isolate a muscle of interest for strengthening

Humerus osteology, myology, and finite element structure analysis of Cheloniidae

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Knee and Hip Joint Kinematics Predict Quadriceps and Hamstrings Neuromuscular Activation Patterns in Drop Jump Landings.

PURPOSE: The purpose was to assess if variation in sagittal plane landing kinematics is associated with variation in neuromuscular activation patterns of the quadriceps-hamstrings muscle groups during drop vertical jumps (DVJ). METHODS: Fifty female athletes performed three DVJ. The relationship between peak knee and hip flexion angles and the amplitude of four EMG vectors was investigated with trajectory-level canonical correlation analyses over the entire time period of the landing phase. EMG vectors consisted of the {vastus medialis(VM),vastus lateralis(VL)}, {vastus medialis(VM),hamstring medialis(HM)}, {hamstring medialis(HM),hamstring lateralis(HL)} and the {vastus lateralis(VL),hamstring lateralis(HL)}. To estimate the contribution of each individual muscle, linear regressions were also conducted using one-dimensional statistical parametric mapping. RESULTS: The peak knee flexion angle was significantly positively associated with the amplitudes of the {VM,HM} and {HM,HL} during the preparatory and initial contact phase and with the {VL,HL} vector during the peak loading phase (p<0.05). Small peak knee flexion angles were significantly associated with higher HM amplitudes during the preparatory and initial contact phase (p<0.001). The amplitudes of the {VM,VL} and {VL,HL} were significantly positively associated with the peak hip flexion angle during the peak loading phase (p<0.05). Small peak hip flexion angles were significantly associated with higher VL amplitudes during the peak loading phase (p = 0.001). Higher external knee abduction and flexion moments were found in participants landing with less flexed knee and hip joints (p<0.001). CONCLUSION: This study demonstrated clear associations between neuromuscular activation patterns and landing kinematics in the sagittal plane during specific parts of the landing. These findings have indicated that an erect landing pattern, characterized by less hip and knee flexion, was significantly associated with an increased medial and posterior neuromuscular activation (dominant hamstrings medialis activity) during the preparatory and initial contact phase and an increased lateral neuromuscular activation (dominant vastus lateralis activity) during the peak loading phase

Model-Based Estimation of Muscle Forces Exerted During Movements

Estimation of individual muscle forces during human movement can provide insight into neural control and tissue loading and can thus contribute to improved diagnosis and management of both neurological and orthopaedic conditions. Direct measurement of muscle forces is generally not feasible in a clinical setting, and non-invasive methods based on musculoskeletal modeling should therefore be considered. The current state of the art in clinical movement analysis is that resultant joint torques can be reliably estimated from motion data and external forces (inverse dynamic analysis). Static optimization methods to transform joint torques into estimates of individual muscle forces using musculoskeletal models, have been known for several decades. To date however, none of these methods have been successfully translated into clinical practice. The main obstacles are the lack of studies reporting successful validation of muscle force estimates, and the lack of user-friendly and efficient computer software. Recent advances in forward dynamics methods have opened up new opportunities. Forward dynamic optimization can be performed such that solutions are less dependent on measured kinematics and ground reaction forces, and are consistent with additional knowledge, such as the force–length–velocity–activation relationships of the muscles, and with observed electromyography signals during movement. We conclude that clinical applications of current research should be encouraged, supported by further development of computational tools and research into new algorithms for muscle force estimation and their validation

Advancing Medical Technology for Motor Impairment Rehabilitation: Tools, Protocols, and Devices

Excellent motor control skills are necessary to live a high-quality life. Activities such as walking, getting dressed, and feeding yourself may seem mundane, but injuries to the neuromuscular system can render these tasks difficult or even impossible to accomplish without assistance. Statistics indicate that well over 100 million people are affected by diseases or injuries, such as stroke, Parkinson’s Disease, Multiple Sclerosis, Cerebral Palsy, peripheral nerve injury, spinal cord injury, and amputation, that negatively impact their motor abilities. This wide array of injuries presents a challenge to the medical field as optimal treatment paradigms are often difficult to implement due to a lack of availability of appropriate assessment tools, the inability for people to access the appropriate medical centers for treatment, or altogether gaps in technology for treating the underlying impairments causing the disability. Addressing each of these challenges will improve the treatment of movement impairments, provide more customized and continuous treatment to a larger number of patients, and advance rehabilitative and assistive device technology. In my research, the key approach was to develop tools to assess and treat upper extremity movement impairment. In Chapter 2.1, I challenged a common biomechanical[GV1] modeling technique of the forearm. Comparing joint torque values through inverse dynamics simulation between two modeling platforms, I discovered that representing the forearm as a single cylindrical body was unable to capture the inertial parameters of a physiological forearm which is made up of two segments, the radius and ulna. I split the forearm segment into a proximal and distal segment, with the rationale being that the inertial parameters of the proximal segment could be tuned to those of the ulna and the inertial parameters of the distal segment could be tuned to those of the radius. Results showed a marked increase in joint torque calculation accuracy for those degrees of freedom that are affected by the inertial parameters of the radius and ulna. In Chapter 2.2, an inverse kinematic upper extremity model was developed for joint angle calculations from experimental motion capture data, with the rationale being that this would create an easy-to-use tool for clinicians and researchers to process their data. The results show accurate angle calculations when compared to algebraic solutions. Together, these chapters provide easy-to-use models and tools for processing movement assessment data. In Chapter 3.1, I developed a protocol to collect high-quality movement data in a virtual reality task that is used to assess hand function as part of a Box and Block Test. The goal of this chapter is to suggest a method to not only collect quality data in a research setting but can also be adapted for telehealth and at home movement assessment and rehabilitation. Results indicate that the data collected in this protocol are good and the virtual nature of this approach can make it a useful tool for continuous, data driven care in clinic or at home. In Chapter 3.2 I developed a high-density electromyography device for collecting motor unit action potentials of the arm. Traditional surface electromyography is limited by its ability to obtain signals from deep muscles and can also be time consuming to selectively place over appropriate muscles. With this high-density approach, muscle coverage is increased, placement time is decreased, and deep muscle activity can potentially be collected due to the high-density nature of the device[GV2] . Furthermore, the high-density electromyography device is built as a precursor to a high-density electromyography-electrical stimulation device for functional electrical stimulation. The customizable nature of the prototype in Chapter 3.2 allows for the implementation both recording and stimulating electrodes. Furthermore, signal results show that the electromyography data obtained from the device are of high quality and are correlated with gold standard surface electromyography sensors. One key factor in a device that can record and then stimulate based on the information from the recorded signals is an accurate movement intent decoder. High-quality movement decoders have been designed by closed-loop device controllers in the past, but they still struggle when the user interacts with objects of varying weight due to underlying alterations in muscle signals. In Chapter 4, I investigate this phenomenon by administering an experiment where participants perform a Box and Block Task with objects of 3 different weights, 0 kg, 0.02 kg, and 0.1 kg. Electromyography signals of the participants right arm were collected and co-contraction levels between antagonistic muscles were analyzed to uncover alterations in muscle forces and joint dynamics. Results indicated contraction differences between the conditions and also between movement stages (contraction levels before grabbing the block vs after touching the block) for each condition. This work builds a foundation for incorporating object weight estimates into closed-loop electromyography device movement decoders. Overall, we believe the chapters in this thesis provide a basis for increasing availability to movement assessment tools, increasing access to effective movement assessment and rehabilitation, and advance the medical device and technology field

Recovery of arm-hand function after stroke: developing neuromechanical biomarkers to optimize rehabilitation strategies.

The aim of this thesis was to explore the neuromechanics of recovery of arm-hand function after stroke. A literature review revealed six articles that measured biomechanical and electromyographical outcome measures simultaneously, while applying active and passive tasks and multiple movement velocities to separate neural and non-neural contributors to movement disorders after stroke. Therefore, a neuromechanic assessment protocol was developed. Parameters were responsive to clinical status and had good to excellent test-retest reliability. Selective muscle activation was assessed with high measurement reliability and was significantly lower in chronic stroke patients compared to healthy participants. Longitudinally, neuromechanical parameters were combined with data on arm-hand function at six months after stroke. Paresis and diminished modulation of reflexes were associated with poor functional outcome. Changes in tissue properties were represented by a shift in wrist rest angle towards flexion and decline in passive range of motion. Increase in active range of motion and steady rest angle contributed most to prediction of functional outcome. The precision diagnostics provided by a neuromechanical assessment protocol could support clinical decision making and should be used in prediction models and as biomarkers in recovery of arm-hand function after stroke, for example by improving the selection of time-window and patients.ZON/MW grant 89000001LUMC / Geneeskund

Identification of dynamic myoelectric signal-to-force models during isometric lumbar muscle contractions

A 14-muscle myoelectric signal (MES)-driven muscle force prediction model of the L3-L4 cross section is developed which includes a dynamic MES-force relationship and allows for cocontraction. Model parameters are estimated from MES and moments data recorded during rapid exertions in trunk flexion, extension, lateral bending and axial twist. Nine young healthy males participated in the experimental testing. The model used in the parameter estimation is of the output error type. Consistent and physically feasible parameter estimates were obtained by normalizing the RMS MES to maximum exertion levels and using nonlinear constrained optimization to minimize a cost function consisting of the trace of the output error covariance matrix. Model performance was evaluated by comparing measured and MES-predicted moments over a series of slow and rapid exertions. Moment prediction errors were on the order of 25, 30 and 40% during attempted trunk flexion-extensions, lateral bends and axial twists, respectively. The model and parameter estimation methods developed provide a means to estimate lumbar muscle and spine loads, as well as to empirically investigate the use and effects of cocontraction during physical task performances.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/31486/1/0000408.pd

Examining the influence of muscle fatigue on knee joint mechanics during an athletic cutting task

The purpose of the current study was to examine the influence of lower limb muscle fatigue on the mechanics of the knee joint during an athletic cutting task. A biomechanical methodology was utilized to examine 12 recreationally active females, who cycled through a fatigue-inducing protocol, using a slideboard, followed by the performance of five maximal cuts, until fatigue resulted in trial termination. 3D motion capture was utilized to capture full body movements and changing joint angles of the hip, knee and ankle during the weight acceptance of the cutting maneuver. A force plate was used to record the ground reaction forces of the participants during weight acceptance of the athletic cut. Lastly, surface electromyography monitored the muscle activity of nine muscles on the dominant leg of the participants. Repeated measures ANOVA (p\u3c0.05), with Tukey’s significant post hoc test, was used to determine significance of the main effect of time on the measured variables. Analysis of the kinematic data revealed that, as fatigue progressed, hip and knee flexion angle significantly decreased during weight acceptance. Kinetic data revealed that peak anterior-posterior shear force significantly increased, and medial-lateral impulse of force significantly decreased, as participants progressed through the fatiguing protocol. Finally, surface electromyography data showed an overall significant decrease in muscle activation from the beginning to the end of trial, however, further investigation of pairwise comparisons indicated that, from 60-100% of the trial, muscle activation significantly increased. This work contributes to the body of work concerning exercise induced muscle fatigue and provides further insight into the underlying mechanism of acute injury during heightened fatigued states. The knowledge gained from this study can be used to advise and improve training prescription and monitoring strategies