Evidence map›Paper›PMID 42730156›Full record

ArticleFrontiers in sports and active living2026

Lower limb exoskeletons for older adults: key assistance parameters and evaluation of ankle assistive strategies via musculoskeletal modelling.

Josée Mallah, Luigi G Occhipinti

Abstract read
In one paragraph

Article in Frontiers in sports and active living, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Josée MallahElectrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge, United Kingdom.
Luigi G OcchipintiElectrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aging comes with physiological changes resulting in alterations to gait, decline of muscle function, and balance that contribute to reduced mobility, increased metabolic cost of walking, and elevated fall and injury risks in older adults. Wearable lower-limb exoskeletons have emerged as a promising strategy to support healthy aging; however, identifying optimal assistance strategies remains challenging due to the complexity and cost of experimental testing. In this study, we combined musculoskeletal modelling and simulations to identify key assistance parameters for older-adult gait and evaluate different ankle exoskeleton configurations computationally, based on muscle activation, metabolic consumption, device weight and power requirement, efficiency, and performance. Motion capture, force plate, and electromyography data from younger and older adults were processed using OpenSim-based musculoskeletal simulations with age-adjusted muscle parameters. Age-related gait differences were quantified across spatiotemporal, kinematic, kinetic, and muscle activation metrics. Subsequently, unilateral and bilateral ankle assistance strategies providing plantarflexion (PF), dorsiflexion (DF), or combined plantarflexion-dorsiflexion (PFDF) support were simulated using unidirectional path actuators representative of cable-driven exoskeletons. Older adults exhibited reduced ankle and hip range of motion, decreased plantarflexion, delayed joint moments, shorter step length, and increased double support time compared with younger adults. These changes suggest that elderly gait can be improved with kinematic assistance at the ankles and hips, timed kinetic assistance at the knees and hips, as well as balance support, hence an opportunity for exoskeleton intervention. Simulated ankle assistance reduced muscle activations and metabolic expenditure, with bilateral PFDF assistance providing the greatest overall benefits. While dorsiflexion-only assistance reduced power requirements, it occasionally increased metabolic consumption. Overall, bilateral assistance outperformed unilateral configurations across most performance metrics. These findings provide biomechanical design guidelines for future lower-limb exoskeletons targeting mobility enhancement and fall-risk reduction in aging populations and demonstrate the value of computational biomechanics for screening assistive-device configurations prior to experimental implementation.

Indexed as

agingbiomechanicsexoskeletonsgait analysismusculoskeletal modelling

Identifiers

PMID42730156
PMCPMC13563653

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.