M2
Scientific context
With ageing, there is an increasing incidence of balance [1] and mobility [2] impairments, causing dramatic impact on health and quality of life [3]. Despite extensive study in the last thirty years, the laboratory and clinical measures of balance that have been developed are poorly predictive of fall risk, with very disparate reported levels of sensitivity, specificity and accuracy [4]. Our previous work shows that this may be because such studies neglect older adults’ inability to adapt postural control [5]. Indeed, in typical study designs, balance is assessed by exposing participants to repeated perturbations in the laboratory. The first response is often discarded from the analysis, as it is very different (often much stronger) than the subsequent, “habituated” response [6]. This habituated response is not different between older fallers and non-fallers [7]. In daily living however, falling may occur after a single unexpected perturbation, if the person’s sensorimotor control was not adapted to the environment. The novelty in our approach is to study how participants adapt, from the first trial response to subsequent habituated responses.
Project
The goal of the project is to determine how young, healthy participants adapt sensorimotor control to alterations in the context. Our previous modelling work has shown that efficient balance requires controlling the Centre of Pressure (CoP) as a function of the position and speed of the Centre of Mass (CoM)[8]. The nervous system cannot directly measure the position of the CoM, and must instead rely on integrating feedback from visual, vestibular and proprioceptive inputs. The goal is to identify how the nervous system rapidly adjusts sensory integration to the context. When standing on solid ground, or on ground that accelerates horizontally (such as in public transport), ankle proprioception provides a clear indication of whether the CoM is above the base of support. The CoP can therefore be controlled using sensory feedback from ankle proprioception, with a large feedback gain. When the ground sways however (such as on a boat), ankle proprioception no longer provides a clear indication of CoM position, and subjects must instead rely on visual and vestibular information to control the CoP, with a low ankle proprioception feedback gain. The goal is to measure how individual subjects adapt sensory integration to context.
Environment
The project will take place at the Institut des Systèmes Intelligents et Robotique (Sorbonne University), which has internationally-renowned expertise in robotics, and will be part of a federative project uniting two teams in the laboratory around multisensory integration for balance (https://www.isir.upmc.fr/projets/integration-multi-sensorielle-pour-le-maintien-de-lequilibre/)
Applicant
The applicant is expected to have a background in engineering and neuroscience, with previous experience in data analysis in Python. We are looking for a candidate who is interested in pursuing this project for a PhD on postural adaptation and fall risk in ageing.
References
[1] T. Masud and R. O. Morris, ‘Epidemiology of falls’, Age Ageing, vol. 30 Suppl 4, pp. 3–7, Nov. 2001.
[2] J. Holmes, E. Powell-Griner, M. Lethbridge-Cejku, and K. Heyman, ‘Aging differently: Physical limitations among adults aged 50 years and over: United States, 2001-2007’, NCHS Data Brief, no. 20, pp. 1–8, Jul. 2009.
[3] J. A. Stevens, P. S. Corso, E. A. Finkelstein, and T. R. Miller, ‘The costs of fatal and non-fatal falls among older adults’, Injury Prevention, vol. 12, no. 5, pp. 290–295, 2006.
[4] L. Montesinos, R. Castaldo, and L. Pecchia, ‘Wearable Inertial Sensors for Fall Risk Assessment and Prediction in Older Adults: A Systematic Review and Meta-Analysis’, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 26, no. 3, pp. 573–582, Mar. 2018, doi: 10.1109/TNSRE.2017.2771383.
[5] C. Le Mouel, R. Tisserand, T. Robert, and R. Brette, ‘Postural adjustments in anticipation of predictable perturbations allow elderly fallers to achieve a balance recovery performance equivalent to elderly non-fallers’, Gait & Posture, vol. 71, pp. 131–137, Jun. 2019.
[6] J. H. J. Allum, K.-S. Tang, M. G. Carpenter, L. B. Oude Nijhuis, and B. R. Bloem, ‘Review of first trial responses in balance control: influence of vestibular loss and Parkinson’s disease’, Hum Mov Sci, vol. 30, no. 2, pp. 279–295, Apr. 2011, doi: 10.1016/j.humov.2010.11.009.
[7] R. W. Baloh, S. Corona, K. M. Jacobson, J. A. Enrietto, and T. Bell, ‘A Prospective Study of Posturography in Normal Older People’, Journal of the American Geriatrics Society, vol. 46, no. 4, pp. 438–443, 1998.
[8] C. Le Mouel and R. Brette, ‘Anticipatory coadaptation of ankle stiffness and sensorimotor gain for standing balance’, PLOS Computational Biology, vol. 15, no. 11, p. e1007463, Nov. 2019, doi: 10.1371/journal.pcbi.1007463.