Biomedical subjects

Bernard J Martin

Publications and source records attributed to Bernard J Martin.

6 recordsLinked to original sources

PubMed2006

Head movement control in visually guided tasks: postural goal and optimality.

This work investigates the control of horizontal head movements in the context of unconstrained visually guided head and arm/finger aiming tasks. In a first experiment, the head was free to move while gaze was directed at randomly presented eccentric targets distributed horizontally (0 degrees-120 degrees) at eye level. In a second experiment, the horizontal head orientation was constrained to predetermined positions (0 degrees, 15 degrees, 30 degrees, 45 degrees or 60 degrees rightward) while the right index finger aimed at targets with the arm fully extended. Kinematics of head movements in gaze displacements exhibits an initial component weakly correlated with target position, followed by multiple corrections. Since the eyes are assumed to already be aimed at the target when the corrections occur, it is suggested that one goal of head movement control is to achieve a desired final orientation (posture). This hypothesis is supported by results from the second experiment that reveal an association between eye/head orientation angles and errors exhibited in the visuo-spatial representation of the environment. The minimization of error then underlies the control of head movement as a postural response optimized for a given target and task condition.

Adult↗

PubMed2006

The relationship between shoulder torques and the perception of muscular effort in loaded reaches.

The objective of this study was to define the quantitative relationship between external dynamic shoulder torques and calibrated perceived muscular effort levels for load delivery tasks, for application in job analyses. Subjects performed a series of loaded reaches and, following each exertion, rated their perceived shoulder muscular effort. Motion and task physical requirements data were processed with a biomechanical upper extremity model to calculate external dynamic shoulder torques. Calculated torque values were then statistically compared to reported calibrated perceived muscular effort scores. Individual subject torque profiles were significantly positively correlated with perceived effort scores (r2 = 0.45-0.77), with good population agreement (r2 = 0.50). The accuracy of the general regression model improved (r2 = 0.72) with inclusion of factors specific to task geometry and individual subjects. This suggests two major conclusions: 1) that the perception of muscular shoulder effort integrates several factors and this interplay should be considered when evaluating tasks for their impact on the shoulder region; 2) the torque/perception relationship may be usefully leveraged in job design and analysis.

Biomechanical Phenomena↗

PubMed2005

Representing and identifying alternative movement techniques for goal-directed manual tasks.

Differences in motion patterns subserving the same movement goal can be identified qualitatively. These alternatives, which may characterize 'movement techniques' (e.g., the stoop and the squat lifting technique), may be associated with significantly different biomechanical constraints and physiological responses. Despite the widely shared understanding of the significance of alternative movement techniques, quantitative representation and identification of movement techniques have received little attention, especially for three-dimensional whole-body motions. In an attempt to systematically differentiate movement techniques, this study introduces a quantitative index termed joint contribution vector (JCV) representing a motion in terms of contributions of individual joint degrees-of-freedom to the achievement of the task goal. Given a set of uncharacterized (unlabeled) motions represented by joint angle trajectories (motion capture data), the JCV and statistical clustering methods enable automated motion classification to uncover a taxonomy of alternative movement techniques. The results of our motion data analyses show that the JCV was able to characterize and discern stoop and squat lifting motions, and also to identify movement techniques for a three-dimensional, whole-body, one-handed load-transfer task. The JCV index would facilitate consideration of alternative movement techniques in a variety of applications, including work method comparison and selection, and human motion modeling and simulation.

Cluster Analysis↗

PubMed2004

A computer algorithm for representing spatial-temporal structure of human motion and a motion generalization method.

Inspired by the generalized motor program (GMP) theory, this study presents a symbolic motion structure representation (SMSR) algorithm that identifies a basic spatial-temporal structure of a human motion. The algorithm resolves each joint angle-time trajectory of a multi-joint motion into a sequence of elemental motion segments and labels each motion segment with a symbol representing its shape ("U": monotonically increasing; "D": monotonically decreasing; "S": stationary). By concatenating symbols according to their order in time, the spatial-temporal structure of a joint angle-time trajectory is represented as a symbolic string. The structure of a multi-joint motion is then represented as a set of symbolic strings. A sample motion, whose structure is identified by the SMSR algorithm, can be generalized to produce an infinite number of similar motion variants. To generate a variant of a sample motion, segment boundary points of the sample motion are first relocated to new locations in the angle-time space, and then individual motion segments of the original joint angle trajectories are shifted and proportionally rescaled to fit the new segment boundary points. This motion generalization method provides a basis for developing GMP-based motion simulation models, and exploring ideas and hypotheses related to the GMP theory through simulation. As an application of the motion generalization method, a motion modification (MoM) algorithm is presented, which adapts existing reach motions for new target locations. Some examples generated by the MoM algorithm are illustrated.

Algorithms↗

PubMed2002

Vibration-induced muscle fatigue, a possible contribution to musculoskeletal injury.

Localized muscle fatigue resulting from 30-min sustained and intermittent grip exertions of 5% maximal voluntary contraction (MVC) with and without hand-vibration exposure (10 Hz, 7 mm displacement amplitude) was investigated. Muscle fatigue was quantified by the magnitude of the twitch force elicited in the right flexor digitorum superficialis muscle of the long finger using the low-frequency fatigue (LFF) method. The influence of vibration in the sustained grip exertion condition exacerbates fatigue as seen with the reduction in twitch force 30-60 min post-work task. Intermittent low grip force exertion conditions with and without vibration exposure show negligible fatigue, suggesting the benefit of rest in the work cycle. Perception of muscle fatigue was dissociated from the objective measure of twitch force, suggesting that LFF was not perceived. The presence of LFF and the lack of perception of LFF may increase the risk for the development of musculoskeletal disorders. The findings of this study may apply to the design of the work cycles and tasks that require the use of vibratory tools.

Adult↗

PubMed2002

The effects of work pace on within-participant and between-participant keying force, electromyography, and fatigue.

A laboratory study was conducted to determine the effects of work pace on typing force, electromyographic (EMG) activity, and subjective discomfort. We found that as participants typed faster, their typing force and finger flexor and extensor EMG activity increased linearly. There was also an increase in subjective discomfort, with a sharp threshold between participants' self-selected pace and their maximum typing speed. The results suggest that participants self-select a typing pace that maximizes typing speed and minimizes discomfort. The fastest typists did not produce significantly more finger flexor EMG activity but did produce proportionately less finger extensor EMG activity compared with the slower typists. We hypothesize that fast typists may use different muscle recruitment patterns that allow them to be more efficient than slower typists at striking the keys. In addition, faster typists do not experience more discomfort than slow typists. These findings show that the relative pace of typing is more important than actual typing speed with regard to discomfort and muscle activity. These results suggest that typists may benefit from skill training to increase maximum typing speed. Potential applications of this research includes skill training for typist.

Adult↗