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. 2024 Jun 21;21(1):105.
doi: 10.1186/s12984-024-01394-x.

The ankle dorsiflexion kinetics demand to increase swing phase foot-ground clearance: implications for assistive device design and energy demands

Affiliations

The ankle dorsiflexion kinetics demand to increase swing phase foot-ground clearance: implications for assistive device design and energy demands

Soheil Bajelan et al. J Neuroeng Rehabil. .

Abstract

Background: The ankle is usually highly effective in modulating the swing foot's trajectory to ensure safe ground clearance but there are few reports of ankle kinetics and mechanical energy exchange during the gait cycle swing phase. Previous work has investigated ankle swing mechanics during normal walking but with developments in devices providing dorsiflexion assistance, it is now essential to understand the minimal kinetic requirements for increasing ankle dorsiflexion, particularly for devices employing energy harvesting or utilizing lighter and lower power energy sources or actuators.

Methods: Using a real-time treadmill-walking biofeedback technique, swing phase ankle dorsiflexion was experimentally controlled to increase foot-ground clearance by 4 cm achieved via increased ankle dorsiflexion. Swing phase ankle moments and dorsiflexor muscle forces were estimated using AnyBody modeling system. It was hypothesized that increasing foot-ground clearance by 4 cm, employing only the ankle joint, would require significantly higher dorsiflexion moments and muscle forces than a normal walking control condition.

Results: Results did not confirm significantly increased ankle moments with augmented dorsiflexion, with 0.02 N.m/kg at toe-off reducing to zero by the end of swing. Tibialis Anterior muscle force incremented significantly from 2 to 4 N/kg after toe-off, due to coactivation with the Soleus. To ensure an additional 4 cm mid swing foot-ground clearance, an estimated additional 0.003 Joules/kg is required to be released immediately after toe-off.

Conclusion: This study highlights the interplay between ankle moments, muscle forces, and energy demands during swing phase ankle dorsiflexion, offering insights for the design of ankle assistive technologies. External devices do not need to deliver significantly greater ankle moments to increase ankle dorsiflexion but, they should offer higher mechanical power to provide rapid bursts of energy to facilitate quick dorsiflexion transitions before reaching Minimum Foot Clearance event. Additionally, for ankle-related bio-inspired devices incorporating artificial muscles or humanoid robots that aim to replicate natural ankle biomechanics, the inclusion of supplementary Tibialis Anterior forces is crucial due to Tibialis Anterior and Soleus co-activation. These design strategies ensures that ankle assistive technologies are both effective and aligned with the biomechanical realities of human movement.

Keywords: Ankle assistive devices; Ankle dorsiflexion energy; Ankle dorsiflexion moment; Ankle dorsiflexion muscle forces; Ankle foot orthoses; Minimum foot clearance; Swing biomechanics.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
The Percentage normalized Swing sub-phases (Initial Swing ≈ 0–35%, Mid-Swing ≈ 35–65%, Terminal Swing ≈ 65–100%), versus event time-normalized sub-phases: Impulsive (Toe-off to Mx1), Maintaining (Mx1 to MFC), and Releasing (MFC to Mx2)
Fig. 2
Fig. 2
(a) The real marker, placed above the big toe, to control real-time monitoring of Minimum Toe Clearance (MTC) (b) The virtual marker, defined by adding the constant distance between the surface of the shoe and sole, to represent Minimum Foot Clearance (MFC)
Fig. 3
Fig. 3
Dual belt tandem force-sensing treadmill walking task with motion captured from thirty-one Vicon reflective markers and muscles activities recorded by EMG electrodes, as described in the Methods. (a) Normal walking mean MTC was computed and each participant’s target MTC defined by adding 4.5 cm, using Visual 3D. (b) Real-time sagittal trajectory of the toe marker presented on a monitor with participants asked to match their dominant limb MTC with the displayed target using ankle dorsiflexion. (c) AnyBody musculoskeletal modelling with experimental markers (blue) matched to the model virtual markers (red) using an inverse kinematics simulation
Fig. 4
Fig. 4
One swing cycle with successive foot-ground contacts on a dual belt tandem force-sensing treadmill, showed from toe-off of right foot (a) to heel-contact (d). Two grey shaded tandem plates are shown with their local origins (red) in which blue lines illustrate the ground reaction force vectors of each plate. Four challenging events of GRF assignment to each limb with the correct timing of foot contact with each plate assignment are shown (a, b, c and d). Figures (a) and (d) demonstrate events at which each foot contacts the anterior or posterior plate separately. The developed model algorithm detected which foot (right or left) touches anterior or posterior plate continuously. Figures (b) and (c) show events when a foot (right or left) travelling from the anterior to the posterior plate during mid-stance and the algorithm could assigned both force plates to one foot only
Fig. 5
Fig. 5
The mean (with shaded areas +/- 1 SD) lower limb joint angles for normal and Ankle strategy conditions with positive angles assigned to dorsiflexion, flexion and abduction. Shaded area SPM paired t-test analysis and dashed-line critical thresholds t values
Fig. 6
Fig. 6
Top panels: mean +/- 1 SD swing phase time-normalised foot vertical displacement (left) and ankle moment (right) for normal walking and the Ankle strategy. Lower panels: paired t-test SPM analysis with grey shading indicating time intervals of significant (p < 0.05) difference between normal walking and Ankle strategy conditions. The critical threshold t values are shown with dashed lines
Fig. 7
Fig. 7
The mean + SD time-histories of TA and Soleus swing force during normal walking and the Ankle strategy compared with EMG signals normalized to maximum activation. The paired samples t-test statistic SPM {t} results indicate timing periods showing significant (p < 0.05) differences of TA and Soleus muscle forces (grey shaded areas). The critical thresholds (t values) are shown with a blue dashed line
Fig. 8
Fig. 8
The mean + SD time-histories of average EDL and EHL swing phase muscle forces during normal walking and the Ankle strategy. The paired samples t-test statistic SPM {t} results indicate timing periods showing significant (p < 0.05) differences (grey shaded areas). The critical thresholds (t values) are shown with a blue dashed line
Fig. 9
Fig. 9
Mean (+ SD) ankle and TA work generated and absorbed within the Impulsive, Maintaining and Releasing sub-phases and whole swing with significant differences between normal walking and Ankle strategy conditions starred (*)

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