Simulated chainsaw injury bone fracture data.

Forensic analysis is often required to determine the cause of an injury. Data for this purpose were acquired by simulating an injury to a limb inflicted by a chainsaw. A surrogate forearm was constructed from gel and a bone simulant. A series of 10 arms were severed under different conditions of chainsaw operation, arm position and arm resistance. The bone fracture force was determined from force records acquired with a force plate which supported the test rig holding the arm. A break wire in the arm signalled the time of fracture. The data set constitutes the reaction force registered by the force plate and the break wire signal. Both signals were digitally sampled at 1000 Hz. Photographs of the proximal portion of each severed arm were taken with a digital camera and are included in the data set. This data set is of interest to forensic investigators considering injuries inflicted by power tools. The data provide a benchmark for planning tests of simulated injuries. They can also be compared to experiments carried out on cadaveric specimens to determine the accuracy of such simulations. This article is being submitted as a co-submission with the following article, G.T. Desmoulin, T.E. Milner, Methodology for determining accidental versus intentional injury afflicted by a chainsaw. Forensic Science International. https://doi.org/10.1016/j.forsciint.2021.110993.

Forensic application of inverse and reverse projection photogrammetry to determine subject location and orientation when both camera and subject move relative to the scene.

We present a case study of a mountain bicycle accident captured by the rider's chest-mounted action camera. The objective of the investigation was to determine the orientation of the bicycle relative to the ground and the location of the rider's center of gravity relative to the bicycle. The problem faced in the investigation was that the camera was moving relative to the scene and rider, and the bicycle was moving relative to the camera. Inverse photogrammetry was used to determine the location and orientation of the camera relative to the scene. Reverse projection photogrammetry applied to an exemplar bicycle provided an estimate of the location and orientation of the bicycle relative to the camera. The rider's position and orientation relative to the camera were estimated by comparing synchronized side views and chest-mounted action camera views of the rider's movements, recorded during a trail descent prior to the accident.

Methodology for determining accidental versus intentional injury afflicted by a chainsaw.

Forensic analysis is often required to determine whether an injury was inflicted intentionally or accidentally. We have developed a method for addressing this issue in the case of an injury to a limb inflicted by a chainsaw. We discuss the potential use of this methodology to the more general case of injuries inflicted by power tools.

Neural Substrates of Muscle Co-contraction during Dynamic Motor Adaptation.

As we learn to perform a motor task with novel dynamics, the central nervous system must adapt motor commands and modify sensorimotor transformations. The objective of the current research is to identify the neural mechanisms underlying the adaptive process. It has been shown previously that an increase in muscle co-contraction is frequently associated with the initial phase of adaptation and that co-contraction is gradually reduced as performance improves. Our investigation focused on the neural substrates of muscle co-contraction during the course of motor adaptation using a resting-state fMRI approach in healthy human subjects of both genders. We analyzed the functional connectivity in resting-state networks during three phases of adaptation, corresponding to different muscle co-contraction levels and found that change in the strength of functional connectivity in one brain network was correlated with a metric of co-contraction, and in another with a metric of motor learning. We identified the cerebellum as the key component for regulating muscle co-contraction, especially its connection to the inferior parietal lobule, which was particularly prominent in early stage adaptation. A neural link between cerebellum, superior frontal gyrus and motor cortical regions was associated with reduction of co-contraction during later stages of adaptation. We also found reliable changes in the functional connectivity of a network involving primary motor cortex, superior parietal lobule and cerebellum that were specifically related to the motor learning.SIGNIFICANCE STATEMENT It is well known that co-contracting muscles is an effective strategy for providing postural stability by modulating mechanical impedance and thereby allowing the central nervous system to compensate for unfamiliar or unexpected physical conditions until motor commands can be appropriately adapted. The present study elucidates the neural substrates underlying the ability to modulate the mechanical impedance of a limb as we learn during motor adaptation. Using resting-state fMRI analysis we demonstrate that a distributed cerebellar-parietal-frontal network functions to regulate muscle co-contraction with the cerebellum as its key component.

Different adaptation rates to abrupt and gradual changes in environmental dynamics.

Adaptation to an abrupt change in the dynamics of the interaction between the arm and the physical environment has been reported as occurring more rapidly but with less retention than adaptation to a gradual change in interaction dynamics. Faster adaptation to an abrupt change in interaction dynamics appears inconsistent with kinematic error sensitivity which has been shown to be greater for small errors than large errors. However, the comparison of adaptation rates was based on incomplete adaptation. Furthermore, the metric which was used as a proxy of the changing internal state, namely the linear regression between the force disturbance and the compensatory force (the adaptation index), does not distinguish between internal state inaccuracy resulting from amplitude or temporal errors. To resolve the apparent inconsistency, we compared the evolution of the internal state during complete adaptation to an abrupt and gradual change in interaction dynamics. We found no difference in the rate at which the adaptation index increased during adaptation to a gradual compared to an abrupt change in interaction dynamics. In addition, we separately examined amplitude and temporal errors using different metrics, and found that amplitude error was reduced more rapidly under the gradual than the abrupt condition, whereas temporal error (quantified by smoothness) was reduced more rapidly under the abrupt condition. We did not find any significant change in phase lag during adaptation under either condition. Our results also demonstrate that even after adaptation is complete, online feedback correction still plays a significant role in the control of reaching.

Origin of directionally tuned responses in lower limb muscles to unpredictable upper limb disturbances.

Unpredictable forces which perturb balance are frequently applied to the body through interaction between the upper limb and the environment. Lower limb muscles respond rapidly to these postural disturbances in a highly specific manner. We have shown that the muscle activation patterns of lower limb muscles are organized in a direction specific manner which changes with lower limb stability. Ankle muscles change their activity within 80 ms of the onset of a force perturbation applied to the hand which is earlier than the onset of changes in ground reaction force, ankle angle or head motion. The latency of the response is sensitive to the perturbation direction. However, neither the latency nor the magnitude of the response is affected by stiffening the arm even though this alters the magnitude and timing of motion of the body segments. Based on the short latency, insensitivity of the change in ankle muscle activation to motion of the body segments but sensitivity to perturbation direction we reason that changes in ankle muscle activation are most likely triggered by sensory signals originating from cutaneous receptors in the hand. Furthermore, evidence that the latency of changes in ankle muscle activation depends on the number of perturbation directions suggests that the neural pathway is not confined to the spinal cord.

Segmental specificity in belly dance mimics primal trunk locomotor patterns.

Belly dance was used to investigate control of rhythmic undulating trunk movements in humans. Activation patterns in lumbar erector spinae muscles were recorded using surface electromyography at four segmental levels spanning T10 to L4. Muscle activation patterns for movement tempos of 2 Hz, 3 Hz, and as fast as possible (up to 6 Hz) were compared to test the hypothesis that frequency modulates muscle timing, causing pattern changes analogous to gait transitions. Groups of trained and untrained female subjects were compared to test the hypothesis that experience modifies muscle coordination patterns and the capacity for selective motion of spinal segments. Three distinct coordination patterns were observed. An ipsilateral simultaneous pattern (S) and a diagonal synergy (D) dominated at lower frequencies. The S pattern was selected most often by novices and resembled the standing wave of activation underlying the alternating lateral trunk bending in salamander trotting. At 2 Hz, most trained subjects selected the D pattern, suggesting a greater capacity for segmental specificity compared with untrained subjects. At 3-4 Hz, there emerged an asynchronous pattern (A) analogous to the rostral-caudal traveling wave in salamander and lamprey swimming. The neural networks and mechanisms identified in primitive vertebrates, such as chains of coupled oscillators and segmental crossed inhibitory connections, could explain the patterns observed in this study in humans. Training allows modification of these patterns, possibly through improved capacity for selectively exciting or inhibiting segmental pattern generators.NEW & NOTEWORTHY Belly dance provides a novel approach for studying spinal cord neural circuits. New evidence suggests that primitive locomotor circuits may be conserved in humans. Erector spinae activation patterns during the hip shimmy at different tempos are similar to those observed in salamander walking and swimming. As movement frequency increases, a sequential pattern similar to lamprey swimming emerges, suggesting that primal involuntary control mechanisms dominate in fast lateral rhythmic spine undulations even in humans.

Control of finger forces during fast, slow and moderate rotational hand movements.

The goal of this study was to investigate the effect of speed on patterns of grip forces during twisting movement involving forearm supination against a torsional load (combined elastic and inertial load). For slow and moderate speed rotations, the grip force increased linearly with load torque. However, for fast rotations in which the contribution of the inertia to load torque was significantly greater than slower movements, the grip force-load torque relationship could be segmented into two phases: a linear ascending phase corresponding to the acceleration part of the movement followed by a plateau during deceleration. That is, during the acceleration phase, the grip force accurately tracked the combined elastic and inertial load. However, the coupling between grip force and load torque was not consistent during the deceleration phase of the movement. In addition, as speed increased, both the position and the force profiles became smoother. No differences in the baseline grip force, safety margin to secure the grasp during hold phase or the overall change in grip force were observed across different speeds.

Shared and specific independent components analysis for between-group comparison.

Independent component analysis (ICA) has been extensively used in individual and within-group data sets in real-world applications, but how can it be employed in a between-groups or conditions design? Here, we propose a new method to embed group membership information into the FastICA algorithm so as to extract components that are either shared between groups or specific to one or a subset of groups. The proposed algorithm is designed to automatically extract the pattern of differences between different experimental groups or conditions. A new constraint is added to the FastICA algorithm to simultaneously deal with the data of multiple groups in a single ICA run. This cost function restricts the specific components of one group to be orthogonal to the subspace spanned by the data of the other groups. As a result of performing a single ICA on the aggregate data of several experimental groups, the entire variability of data sets is used to extract the shared components. The results of simulations show that the proposed algorithm performs better than the regular method in both the reconstruction of the source signals and classification of shared and specific components. Also, the sensitivity to detect variations in the amplitude of shared components across groups is enhanced. A rigorous proof of convergence is provided for the proposed iterative algorithm. Thus, this algorithm is guaranteed to extract and classify shared and specific independent components across different experimental groups and conditions in a systematic way.

Independent activation in adjacent lumbar extensor muscle compartments.

The purpose of this study was to examine compartmentalization in human lumbar spine extensors. Structure and innervation of these muscles would suggest the possibility of more segmentally specific biomechanical functions than have been found in previous studies examining muscle activation patterns during simple spine bending and twisting tasks. We selected specialized tasks to more effectively investigate the degree of independent control possible within lumbar spine extensors. We recorded surface electromyograms (SEMG) from the right posterior lumbar region during performance of two segmentally specific bellydance skills by seven novice and five trained subjects. These movements were performed at two frequencies (0.5 and 1Hz). Cross-correlations were performed between pairs of rectified, low-pass filtered (6Hz) SEMG signals to determine temporal lags between rhythmic bursts. Results showed a difference in the timing of muscle activation above and below the third lumbar vertebra. Temporal asynchrony was independent of either skill level or tempo, suggesting a hard-wired capacity for independent control of adjacent muscle compartments. The results have implications for understanding trunk control in the context of postural stability and postural adaptation during locomotion, as well as for lower back functional assessment and rehabilitation.

A robotic interface to train grip strength, grip coordination and finger extension following stroke.

A two degree of freedom robotic interface was developed to assist with rehabilitation of three hand impairments following stroke: reduced grip strength, reduced finger extension, and loss of dexterity due to the lack of coordination between finger and wrist muscles. The design and performance characteristics of this interface, which takes advantage of an FPGA-based real-time platform, are discussed. The robotic interface is able to accurately render elastic and viscous loads. Preliminary trials with healthy subjects demonstrate the use of the device.

Functionally specific changes in resting-state sensorimotor networks after motor learning.

Motor learning changes the activity of cortical motor and subcortical areas of the brain, but does learning affect sensory systems as well? We examined in humans the effects of motor learning using fMRI measures of functional connectivity under resting conditions and found persistent changes in networks involving both motor and somatosensory areas of the brain. We developed a technique that allows us to distinguish changes in functional connectivity that can be attributed to motor learning from those that are related to perceptual changes that occur in conjunction with learning. Using this technique, we identified a new network in motor learning involving second somatosensory cortex, ventral premotor cortex, and supplementary motor cortex whose activation is specifically related to perceptual changes that occur in conjunction with motor learning. We also found changes in a network comprising cerebellar cortex, primary motor cortex, and dorsal premotor cortex that were linked to the motor aspects of learning. In each network, we observed highly reliable linear relationships between neuroplastic changes and behavioral measures of either motor learning or perceptual function. Motor learning thus results in functionally specific changes to distinct resting-state networks in the brain.

Effects of a robot-assisted training of grasp and pronation/supination in chronic stroke: a pilot study.

BACKGROUND: Rehabilitation of hand function is challenging, and only few studies have investigated robot-assisted rehabilitation focusing on distal joints of the upper limb. This paper investigates the feasibility of using the HapticKnob, a table-top end-effector device, for robot-assisted rehabilitation of grasping and forearm pronation/supination, two important functions for activities of daily living involving the hand, and which are often impaired in chronic stroke patients. It evaluates the effectiveness of this device for improving hand function and the transfer of improvement to arm function. METHODS: A single group of fifteen chronic stroke patients with impaired arm and hand functions (Fugl-Meyer motor assessment scale (FM) 10-45/66) participated in a 6-week 3-hours/week rehabilitation program with the HapticKnob. Outcome measures consisted primarily of the FM and Motricity Index (MI) and their respective subsections related to distal and proximal arm function, and were assessed at the beginning, end of treatment and in a 6-weeks follow-up. RESULTS: Thirteen subjects successfully completed robot-assisted therapy, with significantly improved hand and arm motor functions, demonstrated by an average 3.00 points increase on the FM and 4.55 on the MI at the completion of the therapy (4.85 FM and 6.84 MI six weeks post-therapy). Improvements were observed both in distal and proximal components of the clinical scales at the completion of the study (2.00 FM wrist/hand, 2.55 FM shoulder/elbow, 2.23 MI hand and 4.23 MI shoulder/elbow). In addition, improvements in hand function were observed, as measured by the Motor Assessment Scale, grip force, and a decrease in arm muscle spasticity. These results were confirmed by motion data collected by the robot. CONCLUSIONS: The results of this study show the feasibility of this robot-assisted therapy with patients presenting a large range of impairment levels. A significant homogeneous improvement in both hand and arm function was observed, which was maintained 6 weeks after end of the therapy.

Concurrent adaptation of force and impedance in the redundant muscle system.

This article examines the validity of a model to explain how humans learn to perform movements in environments with novel dynamics, including unstable dynamics typical of tool use. In this model, a simple rule specifies how the activation of each muscle is adapted from one movement to the next. Simulations of multijoint arm movements with a neuromuscular plant that incorporates neural delays, reflexes, and signal-dependent noise, demonstrate that the controller is able to compensate for changing internal or environment dynamics and noise properties. The computational model adapts by learning both the appropriate forces and required limb impedance to compensate precisely for forces and instabilities in arbitrary directions with patterns similar to those observed in motor learning experiments. It learns to regulate reciprocal activation and co-activation in a redundant muscle system during repeated movements without requiring any explicit transformation from hand to muscle space. Independent error-driven change in the activation of each muscle results in a coordinated control of the redundant muscle system and in a behavior that reduces instability, systematic error, and energy.

Modulation of arm stiffness in relation to instability at the beginning or the end of goal-directed movements.

In reaching to a target, stability near the target may be more critical for success than stability far from the target. Consequently, we postulated that high instability near the start would evoke less compensation than high instability near the target. Three stability conditions were implemented using a robot manipulandum: neutral stability everywhere (null field); high instability along the first half of the trajectory decreasing as the target was approached (start unstable); and instability increasing along the first half of the trajectory and remaining high as the target was approached (end unstable). Under the start unstable condition, the stiffness of the arm in the region of highest instability was significantly less than under the end unstable condition. Furthermore, the stability of the system (manipulandum plus arm) was much lower under the start unstable condition than under the null field condition whereas it was similar under the end unstable and null field conditions.

A protocol for measuring the direct effect of cycling on neuromuscular control of running in triathletes.

The direct effects of cycling on movement and muscle recruitment patterns (neuromuscular control) during running are unknown but critical to success in triathlon. We outline and test a new protocol for investigating the direct influence of cycling on neuromuscular control during running. Leg movement (three-dimensional kinematics) and muscle recruitment (surface electromyography, EMG) were compared between a control run (no prior exercise) and a 30-min transition run that was preceded by 20 min of cycling. We conducted three experiments investigating: (a) the repeatability (between-day reliability) of the protocol; (b) the ability of the protocol to investigate, in highly trained national or international triathletes, the direct influence of cycling on neuromuscular control during running independent of neuromuscular fatigue; and (c) the ability of the protocol to provide a control, or baseline, measure of neuromuscular control (determined using a measure of stability) without causing fatigue. Kinematic and EMG measures of neuromuscular control during running showed moderate to high repeatability: mean coefficients of multiple correlation for repeatability of EMG and kinematics were 0.816 +/- 0.014 and 0.911 +/- 0.031, respectively. The protocol provided a robust baseline measure of neuromuscular control during running without causing neuromuscular fatigue (coefficients of multiple correlation for stability of EMG and kinematics were 0.827 +/- 0.023 and 0.862 +/- 0.054), while EMG and force data provided no evidence of fatigue. The protocol outlined here is repeatable and can be used to measure any direct influence of cycling on neuromuscular control during running.

A technique for conditioning and calibrating force-sensing resistors for repeatable and reliable measurement of compressive force.

Miniature sensors that could measure forces applied by the fingers and hand without interfering with manual dexterity or range of motion would have considerable practical value in ergonomics and rehabilitation. In this study, techniques have been developed to use inexpensive pressure-sensing resistors (FSRs) to accurately measure compression force. The FSRs are converted from pressure-sensing to force-sensing devices. The effects of nonlinear response properties and dependence on loading history are compensated by signal conditioning and calibration. A fourth-order polynomial relating the applied force to the current voltage output and a linearly weighted sum of prior outputs corrects for sensor hysteresis and drift. It was found that prolonged (>20h) shear force loading caused sensor gain to change by approximately 100%. Shear loading also had the effect of eliminating shear force effects on sensor output, albeit only in the direction of shear loading. By applying prolonged shear loading in two orthogonal directions, the sensors were converted into pure compression sensors. Such preloading of the sensor is, therefore, required prior to calibration. The error in compression force after prolonged shear loading and calibration was consistently <5% from 0 to 30N and <10% from 30 to 40N. This novel method of calibrating FSRs for measuring compression force provides an inexpensive tool for biomedical and industrial design applications where measurements of finger and hand force are needed.

CNS learns stable, accurate, and efficient movements using a simple algorithm.

We propose a new model of motor learning to explain the exceptional dexterity and rapid adaptation to change, which characterize human motor control. It is based on the brain simultaneously optimizing stability, accuracy and efficiency. Formulated as a V-shaped learning function, it stipulates precisely how feedforward commands to individual muscles are adjusted based on error. Changes in muscle activation patterns recorded in experiments provide direct support for this control scheme. In simulated motor learning of novel environmental interactions, muscle activation, force and impedance evolved in a manner similar to humans, demonstrating its efficiency and plausibility. This model of motor learning offers new insights as to how the brain controls the complex musculoskeletal system and iteratively adjusts motor commands to improve motor skills with practice.

How is somatosensory information used to adapt to changes in the mechanical environment?

Recent studies examining adaptation to unexpected changes in the mechanical environment highlight the use of position error in the adaptation process. However, force information is also available. In this chapter, we examine adaptation processes in three separate studies where the mechanical environment was changed intermittently. We compare the expected consequences of using position error and force information in the changes to motor commands following a change in the mechanical environment. In general, our results support the use of position error over force information and are consistent with current computational models of motor learning. However, in situations where the change in the mechanical environment eliminates position error the central nervous system does not necessarily respond as would be predicted by these models. We suggest that it is necessary to take into account the statistics of prior experience to account for our observations. Another deficiency in these models is the absence of a mechanism for modulating limb mechanical impedance during adaptation. We propose a relatively simple computational model based on reflex responses to perturbations which is capable of accounting for iterative changes in temporal patterns of muscle co-activation.

Rapid adaptation to scaled changes of the mechanical environment.

We investigated adaptation to simple force field scaling to determine whether the same strategy is used as during adaptation to more complex changes in the mechanical environment. Subjects initially trained in a force field, consisting of a rightward lateral force with a parabolic spatial profile (PF). The field strength was then unexpectedly increased or decreased (DeltaPF) for repeated sets of five consecutive trials, with intervening PF trials. Stiff elastic walls, which prevented lateral movement of the arm, randomly replaced 25% of DeltaPF trials. Lateral deviation on DeltaPF trials and lateral force against the elastic walls were used to assess the extent to which feedforward adaptations could be attributed to changes in lateral force or increased stiffness of the arm. When force field strength was increased or decreased hand paths were perturbed to the right or left, respectively. Performance error was significantly reduced between the first and second DeltaPF trial positions of the set, whereas the lateral force impulse exerted against the elastic walls did not change until the third trial position. The lateral force was scaled upward or downward in response to the change in force field strength, suggesting a gradual change in the internal model. The results support a dual strategy of cocontraction (increased stiffness) and internal model modification. The development of an accurate internal model is a slower process than cocontraction and error reduction. This may explain the need to represent motor learning as two parallel processes with varying timescales, as recently proposed by Smith and colleagues.