Investigating the use of a spinal pattern generator (SPG) model to predict the muscular activation (EMG) patterns at the ankle joint during walking
| script | description |
|---|---|
| final_process | Processing synchronized data (from pressure |
| sensors, 3D motion data and EMG data) | |
| runtrial | Main script for the study |
| spgfit | function to tune (model) weights |
| spgmodel | function for model simulation |
| spgsim | function for getting predicted output |
| spgplot | function for plotting predicted results |
Walking is a task which most people perform effortlessly on a daily basis. For humans, the body has to utilise specific mechanisms to maintain equilibrium on the stance leg during locomotion (Dietz et al. 1986). This highly complex motor coordination may be generated by conscious direct activation of the muscles, but on the other hand, this fine tuning between motor requirements and afferent inputs may be controlled by neural networks, also known as spinal pattern generators (SPG) in the spinal cord (Grillner and Wallen, 1985).
The aim of this study was to determine whether SPG in the spinal cord can directly influence motor output. We postulate that sensory afferents, which directly affect muscular activations, are mediated at the spinal level by pattern generators. The selection and modulation of afferents are due to the internal dynamics in the spinal cord which regulate the appropriate locomotor outputs, rather than relying on commands from higher centres (brain).
3D motion data, muscular activation and pressure insoles (of the lower extremities) were collected from volunteers. An SPG model was developed. The model was tested on several datasets, mainly to determine whether the SPG can adapt to changes in sensory cues. We used the SPG model to predict muscular responses in normal walking and three different situations where temporal and spatial parameters in a gait cycle will change: -
- Normal walking
- Sudden loss in loading afferents
- Change in walking speed
- Silly walks
An SPG model was developed and validated for normal walking (Chong et al., 2012). This has strong implications into how humans possess the ability to adapt to changes to sensory afferents in our daily movements (Cognitive Systems book series).
We proposed that SPG in the spinal cord can interpret and respond accordingly to velocity-dependent afferent information. Changes in walking speed do not require a different motor control mechanism provided equilibrium is not affected and there is no disruption of the continuous rhythmic patterns produced at the ankle (Chong et al., 2013, Chong et al., 2014).
Our silly walks study was mentioned by Improbable Research, organizer of the IgNobel awards.