E.K.J. Chadwick

Glenohumeral Contact Forces and Muscle Forces Evaluated in Wheelchair-Related Activities of Daily Living in Able-Bodied Subjects Versus Subjects With Paraplegia and Tetraplegia

OBJECTIVE To estimate the differences in glenohumeral contact forces and shoulder muscle forces between able-bodied subjects and subjects with paraplegia and tetraplegia during wheelchair-related activities of daily living (ADLs). DESIGN Kinematics and external forces were measured during wheelchair ADLs (level propulsion, weight-relief lifting, reaching) and processed by using an inverse dynamics 3-dimensional biomechanical model. SETTING Biomechanics laboratory. PARTICIPANTS Five able-bodied subjects, 8 subjects with paraplegia, and 4 subjects with tetraplegia (N = 17). INTERVENTIONS Not applicable. MAIN OUTCOME MEASURES Glenohumeral contact forces and shoulder muscle forces. RESULTS Peak contact forces were significantly higher for weight-relief lifting compared with reaching and level propulsion (P < .001). High relative muscle force of the rotator cuff was seen, apparently needed to stabilize the joint. For weight-relief lifting, total relative muscle force was significantly higher for the tetraplegia group than for the able-bodied group (P = .022). CONCLUSIONS Glenohumeral contact forces were significantly higher for weight-relief lifting and highest over the 3 tasks for the tetraplegia group. Without taking paralysis into account, more muscle force was estimated for the subjects with tetraplegia during weight-relief lifting.

Muscle oxygen consumption, determined by NIRS, in relation to external force and EMG.

Local oxygen consumption in a muscle (VO(2)) can be determined by near infrared spectroscopy (NIRS). In principle it should be possible to use this measure to validate musculoskeletal models. However, the relationship between VO(2) and external force, or between VO(2) and surface EMG, as a measure for muscle activity, is hardly known. The aim of this study was: (1) to evaluate the characteristics of the relationship between VO(2) and external moments and (2) to determine whether differences exist between the EMG-moment relationship and the VO(2)-moment relationship. Subjects (n=5) were asked to perform isometric contractions exerting combinations of elbow flexion and pro/supination moments at force levels up to 70% of their maximum. Simultaneous surface-EMG and NIRS measurements were performed on the m. biceps breve (BB) and the m. brachioradialis (BR). A linear relationship was found between EMG and VO(2). For the BB VO(2) and EMG were linearly related to both the flexion moment and the pro/supination moment. However, for the BR only a linear relationship with flexion moment was found. As expected, based on the findings above, the relationship between VO(2) and elbow flexion moment can be described by a linear equation, under the conditions of this study (isometric, and force levels up to 70%). These findings suggest that load sharing is independent of force level and that next to EMG, VO(2) can be used for the validation of musculoskeletal models.

Elbow and wrist joint contact forces during occupational pick and place activities

A three-dimensional, mathematical model of the elbow and wrist joints, including 15 muscle units, 3 ligaments and 4 joint forces, has been developed. A new strain gauge transducer has been developed to measure functional grip forces. The device measures radial forces divided into six components and forces of up to 250N per segment can be measured with an accuracy of +/-1%. Ten normal volunteers were asked to complete four tasks representing occupational activities, during which time their grip force was monitored. Together with kinematic information from the six-camera Vicon data, the moment effect of these loads at the joints was calculated. These external moments are assumed to be balanced by the internal moments, generated by the muscles, passive soft tissue and bone contact. The effectiveness of the bodys internal structures in generating joint moments was assessed by studying the geometry of a simplified model of the structures, where information about the lines of action and moment arms of muscles, tendons and ligaments is contained. The assumption of equilibrium between these external and internal joint moments allows formulation of a set of equations from which muscle and joint forces can be calculated. A two stage, linear optimisation routine minimising the overall muscle stress and the sum of the joint forces has been used to overcome the force-sharing problem. Humero-ulnar forces of up to 1600N, humero-radial forces of up to 800N and wrist joint forces of up to 2800N were found for moderate level activity. The model was validated by comparison with other studies.

Biomechanics of knife stab attacks

Equipment, materials and methods for the measurement of the biomechanical parameters governing knife stab attacks have been developed and data have been presented that are relevant to the improvement of standards for the testing of stab-resistant materials. A six-camera Vicon motion analysis system was used to measure velocity, and derive energy and momentum during the approach phase of the attack and a specially developed force-measuring knife was used to measure three-dimensional forces and torque during the impact phase. The body segments associated with the knife were modelled as a series of rigid segments: trunk, upper arm, forearm and hand. The velocities of these segments, together with knowledge of the mass distribution from biomechanical tables, allowed the calculation of the individual segment energy and momentum values. The instrumented knife measured four components of load: axial force (along the length of the blade), cutting force (parallel to the breadth of the blade), lateral force (across the blade) and torque (twisting action) using foil strain gauges. Twenty volunteers were asked to stab a target with near maximal effort. Three styles of stab were used: a short thrust forward, a horizontal style sweep around the body and an overhand stab. These styles were chosen based on reported incidents, providing more realistic data than had previously existed. The 95th percentile values for axial force and energy were 1885 N and 69 J, respectively. The ability of current test methods to reproduce the mechanical parameters measured in human stab attacks has been assessed. It was found that current test methods could reproduce the range of energy and force values measured in the human stab attacks, although the simulation was not accurate in some respects. Non-axial force and torque values were also found to be significant in the human tests, but these are not reproduced in the standard mechanical tests.

Continuous neuronal ensemble control of simulated arm reaching by a human with tetraplegia

Functional electrical stimulation (FES), the coordinated electrical activation of multiple muscles, has been used to restore arm and hand function in people with paralysis. User interfaces for such systems typically derive commands from mechanically unrelated parts of the body with retained volitional control, and are unnatural and unable to simultaneously command the various joints of the arm. Neural interface systems, based on spiking intracortical signals recorded from the arm area of motor cortex, have shown the ability to control computer cursors, robotic arms and individual muscles in intact non-human primates. Such neural interface systems may thus offer a more natural source of commands for restoring dexterous movements via FES. However, the ability to use decoded neural signals to control the complex mechanical dynamics of a reanimated human limb, rather than the kinematics of a computer mouse, has not been demonstrated. This study demonstrates the ability of an individual with long-standing tetraplegia to use cortical neuron recordings to command the real-time movements of a simulated dynamic arm. This virtual arm replicates the dynamics associated with arm mass and muscle contractile properties, as well as those of an FES feedback controller that converts user commands into the required muscle activation patterns. An individual with long-standing tetraplegia was thus able to control a virtual, two-joint, dynamic arm in real time using commands derived from an existing human intracortical interface technology. These results show the feasibility of combining such an intracortical interface with existing FES systems to provide a high-performance, natural system for restoring arm and hand function in individuals with extensive paralysis.

Combined feedforward and feedback control of a redundant, nonlinear, dynamic musculoskeletal system

A functional electrical stimulation controller is presented that uses a combination of feedforward and feedback for arm control in high-level injury. The feedforward controller generates the muscle activations nominally required for desired movements, and the feedback controller corrects for errors caused by muscle fatigue and external disturbances. The feedforward controller is an artificial neural network (ANN) which approximates the inverse dynamics of the arm. The feedback loop includes a PID controller in series with a second ANN representing the nonlinear properties and biomechanical interactions of muscles and joints. The controller was designed and tested using a two-joint musculoskeletal model of the arm that includes four mono-articular and two bi-articular muscles. Its performance during goal-oriented movements of varying amplitudes and durations showed a tracking error of less than 4° in ideal conditions, and less than 10° even in the case of considerable fatigue and external disturbances.

A Real-Time, 3-D Musculoskeletal Model for Dynamic Simulation of Arm Movements

Neuroprostheses can be used to restore movement of the upper limb in individuals with high-level spinal cord injury. Development and evaluation of command and control schemes for such devices typically require real-time, ldquopatient-in-the-looprdquo experimentation. A real-time, 3-D, musculoskeletal model of the upper limb has been developed for use in a simulation environment to allow such testing to be carried out noninvasively. The model provides real-time feedback of human arm dynamics that can be displayed to the user in a virtual reality environment. The model has a 3-DOF glenohumeral joint as well as elbow flexion/extension and pronation/supination and contains 22 muscles of the shoulder and elbow divided into multiple elements. The model is able to run in real time on modest desktop hardware and demonstrates that a large-scale, 3-D model can be made to run in real time. This is a prerequisite for a real-time, whole-arm model that will form part of a dynamic arm simulator for use in the development, testing, and user training of neural prosthesis systems.

A musculoskeletal model of the upper extremity for use in the development of neuroprosthetic systems

Upper extremity neuroprostheses use functional electrical stimulation (FES) to restore arm motor function to individuals with cervical level spinal cord injury. For the design and testing of these systems, a biomechanical model of the shoulder and elbow has been developed, to be used as a substitute for the human arm. It can be used to design and evaluate specific implementations of FES systems, as well as FES controllers. The model can be customized to simulate a variety of pathological conditions. For example, by adjusting the maximum force the muscles can produce, the model can be used to simulate an individual with tetraplegia and to explore the effects of FES of different muscle sets. The model comprises six bones, five joints, nine degrees of freedom, and 29 shoulder and arm muscles. It was developed using commercial, graphics-based modeling and simulation packages that are easily accessible to other researchers and can be readily interfaced to other analysis packages. It can be used for both forward-dynamic (inputs: muscle activation and external load; outputs: motions) and inverse-dynamic (inputs: motions and external load; outputs: muscle activation) simulations. Our model was verified by comparing the model calculated muscle activations to electromyographic signals recorded from shoulder and arm muscles of five subjects. As an example of its application to neuroprosthesis design, the model was used to demonstrate the importance of rotator cuff muscle stimulation when aiming to restore humeral elevation. It is concluded that this model is a useful tool in the development and implementation of upper extremity neuroprosthetic systems.

A novel force transducer for the measurement of grip force

A new strain gauge transducer has been developed to measure functional grip forces. The gripping area is a cylinder of diameter 30 mm and length 150 mm and simulates the handle of a number of devices, allowing a range of activities to be studied. The device measures radial forces divided into six components and forces of up to 250 N per segment can be measured with an accuracy of +/- 1%. The device therefore gives information about the magnitude and distribution of force around the cylinder during gripping, and has been shown to be a valuable research tool in a study of four different types of grip, providing valuable input data for biomechanical models.

Clinical applications of musculoskeletal modelling for the shoulder and upper limb

Musculoskeletal models have been developed to estimate internal loading on the human skeleton, which cannot directly be measured in vivo, from external measurements like kinematics and external forces. Such models of the shoulder and upper extremity have been used for a variety of purposes, ranging from understanding basic shoulder biomechanics to assisting in preoperative planning. In this review, we provide an overview of the most commonly used large-scale shoulder and upper extremity models and categorise the applications of these models according to the type of questions their users aimed to answer. We found that the most explored feature of a model is the possibility to predict the effect of a structural adaptation on functional outcome, for instance, to simulate a tendon transfer preoperatively. Recent studies have focused on minimising the mismatch in morphology between the model, often derived from cadaver studies, and the subject that is analysed. However, only a subset of the parameters that describe the model’s geometry and, perhaps most importantly, the musculotendon properties can be obtained in vivo. Because most parameters are somehow interrelated, the others should be scaled to prevent inconsistencies in the model’s structure, but it is not known exactly how. Although considerable effort is put into adding complexity to models, for example, by making them subject-specific, we have found little evidence of their superiority over current models. The current trend in development towards individualised, more complex models needs to be justified by demonstrating their ability to answer questions that cannot already be answered by existing models.