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Biomedical subjects

William I Sellers

Publications and source records attributed to William I Sellers.

2 recordsLinked to original sources

Stride lengths, speed and energy costs in walking of Australopithecus afarensis: using evolutionary robotics to predict locomotion of early human ancestors.

This paper uses techniques from evolutionary robotics to predict the most energy-efficient upright walking gait for the early human relative Australopithecus afarensis, based on the proportions of the 3.2 million year old AL 288-1 'Lucy' skeleton, and matches predictions against the nearly contemporaneous (3.5-3.6 million year old) Laetoli fossil footprint trails. The technique creates gaits de novo and uses genetic algorithm optimization to search for the most efficient patterns of simulated muscular contraction at a variety of speeds. The model was first verified by predicting gaits for living human subjects, and comparing costs, stride lengths and speeds to experimentally determined values for the same subjects. Subsequent simulations for A. afarensis yield estimates of the range of walking speeds from 0.6 to 1.3 m s-1 at a cost of 7.0 J kg-1 m-1 for the lowest speeds, falling to 5.8 J kg-1 m-1 at 1.0 m s-1, and rising to 6.2 J kg-1 m-1 at the maximum speed achieved. Speeds previously estimated for the makers of the Laetoli footprint trails (0.56 or 0.64 m s-1 for Trail 1, 0.72 or 0.75 m s-1 for Trail 2/3) may have been underestimated, substantially so for Trail 2/3, with true values in excess of 0.7 and 1.0 m s-1, respectively. The predictions conflict with suggestions that A. afarensis used a 'shuffling' gait, indicating rather that the species was a fully competent biped.

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Evaluating alternative gait strategies using evolutionary robotics.

Evolutionary robotics is a branch of artificial intelligence concerned with the automatic generation of autonomous robots. Usually the form of the robot is predefined and various computational techniques are used to control the machine's behaviour. One aspect is the spontaneous generation of walking in legged robots and this can be used to investigate the mechanical requirements for efficient walking in bipeds. This paper demonstrates a bipedal simulator that spontaneously generates walking and running gaits. The model can be customized to represent a range of hominoid morphologies and used to predict performance parameters such as preferred speed and metabolic energy cost. Because it does not require any motion capture data it is particularly suitable for investigating locomotion in fossil animals. The predictions for modern humans are highly accurate in terms of energy cost for a given speed and thus the values predicted for other bipeds are likely to be good estimates. To illustrate this the cost of transport is calculated for Australopithecus afarensis. The model allows the degree of maximum extension at the knee to be varied causing the model to adopt walking gaits varying from chimpanzee-like to human-like. The energy costs associated with these gait choices can thus be calculated and this information used to evaluate possible locomotor strategies in early hominids.

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