Elsevier

Journal of Biomechanics

Volume 48, Issue 2, 21 January 2015, Pages 324-331
Journal of Biomechanics

Analysis of gait within the uncontrolled manifold hypothesis: Stabilisation of the centre of mass during gait

https://doi.org/10.1016/j.jbiomech.2014.11.024Get rights and content

Abstract

This study investigated the feasibility of the uncontrolled manifold approach (UCM) to analyse gait data variability in relation to the control of the centre of mass (COM) in adults with and without neuropathology.

The proposed method was applied to six able-bodied subjects to characterise mechanisms of normal postural control during stance phase. This approach was repeated on an early stroke patient, who attended the laboratory three times at three monthly intervals, to characterise the variability of COM movement during walking with and without an orthosis. Both able-bodied subjects and the stroke participant controlled COM movement during stance but utilized a different combination of lower limb joint kinematics to ensure that the COM trajectory was not compromised. Interestingly, the stroke subject, despite a higher variability in joint kinematics, was able to maintain a stable COM position throughout stance phase. The stabilisation of the COM decreased when the patient walked unaided without the prescribed orthosis but increased over the six months of study. The UCM analysis demonstrated how a stroke patient used a range of lower limb motion pattern to stabilise the COM trajectory. It is suggested that this analysis can be used to track changes in these movement patterns in response to rehabilitation. As such we propose that this approach could have clinical utility to evaluate and prescribe rehabilitation in stroke patients.

Introduction

Many stroke survivors present with an altered ability to walk. Compensatory actions and gait strategies are often adopted to achieve a safe walking activity. Motor control is a key issue for those people who have suffered from a stroke and for whom limited joint coordination impairs their mobility. An understanding of how the central nervous system (CNS) compensates to control motion following a stroke may inform subsequent therapy.

The theory of the uncontrolled manifold (UCM) has been recently introduced (Latash et al., 2007, Scholz and Scho¨ner, 1999) to investigate how the CNS acts with respect to selected motor tasks by choosing combinations of different musculoskeletal elements that are involved in the performance of the task. That is to say the CNS may employ a variety of different approaches to achieve a task. Exploiting this approach it may be possible to predict which motor variables the CNS controls and what are the elements/degree of freedoms (DOFs) that it has to organise for that particular motor task to be performed. This theory can thus be seen as an analysis of the variability of a selected functional task in a multi-degree of freedom system. The variability can either be “good”, if the task goal remains unaltered, or “bad”, if deviations from it occur. The UCM itself is a subspace of all possible combinations of motor elements (elemental variables) that lead to a consistent value of a performance variable. For example all the different combinations of lower limb joint angles that together place the centre of mass (COM) in a certain position in 3D space define a UCM subspace. It is defined “uncontrolled” because the control of the variability within it is unnecessary as all the combinations (i.e., set of lower limb joint angles) within that subspace preserve the performance variable value (i.e., 3D position of the COM) (Scholz and Scho¨ner, 1999). Thereby, the UCM approach can also be seen as a method to quantify synergies. In this context, a synergy refers to an organization of elemental variables that stabilises a performance variable (Latash and Anson, 2006). A practical example could be to use the UCM approach to understand how the CNS organises joint angles (elemental variables) to allow a smooth COM movement (performance variable) and thus produce safe locomotion. It is important to mention that variability across trials is partitioned into two components: one that lies within the UCM and one that is perpendicular to the UCM. These two variabilities, expressed as indexes of variance across repetitions of the same task, are used to verify the hypothesis about the aspects of movement that are controlled. If the variance within the UCM is bigger than the one perpendicular to it, the hypothesis about the stabilisation of the selected motor task is accepted.

This analysis can provide clinicians with a better understanding of motor coordination and its relationship to rehabilitation approaches providing an explanation as to how different dynamic resources can lead to a successful motor performance. Having information on the behaviour of the system will allow a more specific and individualised treatment to accelerate recovery as the target of intervention (musculoskeletal elements) can be identified. Which movement variations should be encouraged and which discouraged? An answer to this question will advance clinical practice and outcomes for stroke survivors.

The UCM analysis method has recently been used to verify the control of motor task predominately related to the upper extremity, sit-to-stand, standing and hopping performances of able-bodied and impaired subjects (Auyang et al., 2009, Domkin et al., 2002, Freitas et al., 2006, Hsu et al., 2007, Reisman and Scholz, 2003, Scholz et al., 2003, Scholz and Scho¨ner, 1999, Yang et al., 2007, Yen and Chang, 2010). Less consideration has been given to gait and the relative motor redundancy it contains. Five papers were found that used the UCM (or covariation analysis similar to UCM) in the analysis of gait. Only two (Black et al., 2007, Verrel et al., 2010) considered the COM trajectory as a performance variable but only at heel strike. Three studies (Krishnan et al., 2013, Robert et al., 2009, Rosenblatt et al., 2014) analysed the temporal evolution of the UCM approach through the gait cycle but none did this with the COM movement as the performance variable.

The exploratory study reported here, therefore, investigated the potential usefulness of UCM analysis of postural control during the stance phase of walking using the COM as the performance variable. It is known that stabilisation of the COM is key to walking ability so that was the rationale for selecting the COM trajectory as the relevant performance variable.

We hypothesised that different combinations of lower limb joint angles (kinematic synergy) can be used to control the COM movement while walking. The specific aims of this study were to (a) determine the feasibility of undertaking UCM analysis of stabilisation of the COM during the stance phase of gait, (b) to find out if such analysis could provide more knowledge of COM stabilisation than ‘standard’ biomechanical analysis techniques, (c) explore whether the UCM analysis could identify differences between a stroke survivor with walking difficulty and adults without a brain lesion and the stroke survivor walking with and without a custom-made ankle-foot orthosis (AFO).

Section snippets

Participants

Six adults (three female, three male; height: 168.9 (± 10.5) cm, mass: 68.2 (± 9.9) kg, age: 29.8 (± 6.7) years ) with no known neurological pathology participated in the study. In addition, one 81 years old male (80 kg, 180 cm) was recruited two months after experiencing a stroke. He presented a left side hemiplegia of the upper and lower body. He was prescribed a 5mm polypropylene AFO with carbon fibre reinforcement at the malleoli level. The AFO and shoes combination were tuned at 10° of

Results

Overall sagittal joint kinematic mean pattern and variability (standard deviations bars) are shown in Fig. 3 for each able-bodied subject. In Fig. 4 they are shown for the hemiplegic leg of the stroke participant during three assessments of walking with AFO and without AFO. Higher variability in joint kinematics is observed for the stroke participant and in particular during baseline test.

COM displacements in the x and y directions are illustrated in Fig. 5 for able-bodied participants and Fig.

Interpretation of UCM method findings

The UCM hypothesis proposes that variability in movement patterns is essential for the performance of everyday functional tasks in a variety of environmental contexts. In other words, what was termed DOF problem might actually be a DOF advantage especially in the presence of a stroke lesion in the brain. Availability of different movement patterns to achieve the same functional goal enables achievement of that goal albeit with what is consider sub-optimal movement. Utilising the UCM approach,

Conclusion

The feasibility of the application of the UCM method to gait data time series was shown in both adults with and without neuropathology. Further research on a larger population group is required to strengthen the clinical meaning of the findings. However, this approach shows great promise with respect to understanding postural control mechanism during walking and the relation to rehabilitation approaches.

The UCM analysis allows a classification of the variability of a selected control variable

Conflict of interest

We declare that we have no conflict of interest.

Acknowledgement

Nonthing to declare.

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