Table 3.
Musculoskeletal: state-of-the-art and future directions
State-of-the-art | a. Predictive models of motion under different musculoskeletal and environmental |
conditions, ranging from changes due to age and walking over uneven terrains. | |
b. Modelling musculoskeletal conditions and injury, such as osteoarthritis. | |
c. Evaluating surgical outcomes, such as hamstring lengthening for crouch gait. | |
d. Modelling human-assistive device interactions with integrated real-time control. | |
Future directions | a. Consider plausible objectives in cost functions that relate to patient goals, |
including stability, fatigue, and comfort. | |
b. Inclusion of neurological details that become impacted with neurological | |
conditions, such as sensory feedback and other neural dynamics. | |
c. Incorporating learning and neuroplasticity principles, which are important | |
when recovering from a neural condition or interacting with an assistive device. | |
d. Advancing models to accommodate various neural condition and injury. |