DISTRIBUTED MOMENT HISTOGRAM - A NEUROPHYSIOLOGY BASED METHOD OF AGONIST AND ANTAGONIST TRUNK MUSCLE-ACTIVITY PREDICTION

A neurocortical-based technique of muscle recruitment is presented to solve the muscle indeterminacy problem for lumbar torso modeling. Cort ical recordings from behaving primates have established motor cortex c ells that respond to a wide range of task directions, bur are tuned to a preferred direction. A characteristic activity pattern of these neu rons seems to be associated with effort direction. It was hypothesized that a model which recruits muscles based on a similar distribution w ould predict antagonistic muscle activity with greater realism than a widely referenced optimization formulation. The predictions of the Dis tributed Moment Histogram (DMH) method were evaluated under common spe ed (< 30 degrees s(-1)) sagittal plane lifting conditions using five s ubjects. The predicted forces showed high correspondence with agonist and antagonist myoelectric patterns. The mean coefficient of determina tion for the erector spinae was r(2) = 0.91, and 0.41 for the latissim us. For the antagonistic muscles, the rectus abdominus was found to be electrically silent (< 3% MVC) and no activity was predicted by the m ethod. The external oblique muscle was observed to be minimally active (< 16% MVC), and the DMH method predicted its mostly constant activit y with a mean standard error of 1.6% MVC. The realistic antagonistic p redictions supported the hypothesis and justify this cortical based te chnique as an alternative for muscle tension estimation in biomechanic al torso modeling. A primary advantage of this method is its computati onal simplicity and direct physiologic analogy. Copyright (C) 1996 Els evier Science Ltd.