Robot-Based Assessment of Sitting Balance: Muscular Responses to Self- and Externally-Controlled Perturbations in Seated Position
Abstract:
In the field of rehabilitation, traditional methods for assessing and training core stability and trunk control involve exercises targeting breathing, muscle strengthening, and both static and dynamic balance. Recently, a novel approach using robotic platforms has emerged.
These systems provide comprehensive quantitative balance assessment, covering static, voluntary, and reactive components. By offering precise measurements of voluntary movement control and automatic postural adjustments, these platforms offer valuable insights into the complex mechanisms of postural control, both in standing and sitting.
In this study, we present a comprehensive characterization of two different sitting balance tasks performed with hunova, a medical robotic device equipped with two electromechanical platforms: one beneath the feet and one beneath the seat.
Sixteen unimpaired subjects participated in the study, divided into two groups based on the assessment protocol: Group1 underwent an assessment testing performance when the sitting platform moved in response to the users’ weight shift; Group2 underwent an assessment testing postural responses to preprogrammed predictable continuous perturbations imposed by the device.
We analyzed upper trunk motion, weight shift, and muscular activations, also in terms of spinal maps and muscle synergies, to investigate muscle recruitment mechanisms and motor control strategies.
We found that subjects adopted different muscular strategies in the two assessments, and that arm position, visual feedback, and adjustable task parameters impacted on the stability as measured by the upper trunk motion.
Through this comprehensive evaluation, we not only characterized sitting balance in response to self-induced and externally imposed perturbations but also gained insights into the potential of these tasks for assessment and rehabilitation applications.
Published:
11 February 2025
RAISE Affiliate:
Spoke 2
Name of the Journal:
IEEE Access
Publication type:
Contribution in journal
DOI:
