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A multi-objective optimal control approach to motor strategy changes in older people with mild cognitive impairment
Tung-Wu Lu1,2,3, Shiuan-Huei Lu1, Cheng-Hao Yu1
1Department of Biomedical Engineering, National Taiwan University, Taipei, Taiwan.
Background:
Mild cognitive impairment (MCI) may lead to difficulty maintaining postural stability and balance during locomotion. This heightened susceptibility to falls is particularly evident during tasks such as obstacle negotiation, which demands efficient motor planning and reallocation of attentional resources. This study proposed a multi-objective optimal control (MOOC) technique to assess the changes in motor control strategies during obstacle negotiation in older people affected by amnestic MCI.
Methods:
Motion data from 12 older adults with MCI and 12 controls when crossing obstacles were measured using a motion capture system, and used to obtain the control strategy of obstacle-crossing as the best compromise between the conflicting objectives of the MOOC problem, i.e., minimising mechanical energy expenditure and maximising foot-obstacle clearance. Comparisons of the weighting sets between groups and obstacle heights were performed using a two-way analysis of variance with a significance level of 0.05.
Results:
Compared to the controls, the MCI group showed significantly lower best-compromise weightings for mechanical energy expenditure but greater best-compromise weightings for both heel- and toe-obstacle clearances. This altered strategy involved a trade-off, prioritising maximising foot-obstacle clearance at the expense of increased mechanical energy expenditure. The MCI group could successfully navigate obstacles with a normal foot-obstacle clearance but at the cost of higher mechanical energy expenditure.
Conclusions:
MCI alters the best-compromise strategy between minimising mechanical energy expenditure and maximising foot-obstacle clearances for obstacle-crossing in older people. These findings provide valuable insights into how MCI impacts motor tasks and offer potential strategies for mitigating fall risks in individuals with MCI. Moreover, this approach could serve as an assessment tool for early diagnosis and a more precise evaluation of disease progression. It may also have applications for individuals with impairments in other cognitive domains.
