Goldilocks Biomechanics

I’m working on a variety of learning materials to teach clinical gait analysis at the moment. Our masters programme in clinical gait analysis should start in 8 months time. One thing I find really depressing is how little of our clinical reasoning for individual patients is based on biomechanics. Most of the interpretation we do is essentially learned and largely subjective pattern recognition. We don’t really understand the data in a way that approaches science.


There are numerous reasons for this but one of the issues is that the biomechanics of walking is not being developed at the right level. On the one hand we have a group of researchers, coalescing under the Dynamic Walking Group, who are developing extremely simple and often non-physiological models to explore very basic principles. On the other hand are researchers typified by (but not restricted to) the OpenSim project who are developing really complex computer models. Neither group, as far as I can see is having a significant impact on the clinical understanding of gait or affecting how we manage our patient’s conditions.

To my mind the simple models are just too simple – how do you use a model without muscles to understand the consequences of a spastic gasttrocnemius? Equally the complex models are too complex- it’s impractical to perform a full CMC analysis for every patient. Even if we did we wouldn’t know which results are robust indications of the biomechanics of the patient and which are consequences of modelling assumptions and parameters.

What we really need is models that are neither too simple nor too complex – borrowing from modern astrophysics we need them to inhabit the Goldilocks zone – Goldilocks biomechanics.



  1. Nice thought Richard. I guess academic research tools like OpenSim are designed for just that – academic research. As the science increases in complexity you need ever more complex tools to undertake the next step in our world of incremental science.

    Clinical tools on the other had serve a different need. Prior to starting my PhD with Prof Pandy I used to work in management consulting – and perhaps there needs to be a consulting/software-lifecycle approach to the development of clinical tools – the same way business and enterprise software tools are developed and implemented, as distinct to the open-ended nature by which academic tools are developed. In other words, the first step for any potential software vendor is to understand the requirements of the client (i.e. the clinician) and use that to design new tools or configure existing tools to suit the needs. Sound like an opportunity for an enterprising biomechanical engineer with a consulting background 😛

    But ultimately, the problem is I guess we don’t yet know enough about the basic biomechanics science, particularly when dealing with deviations from the “normal” healthy gait condition. Furthermore, with current modelling strategies, you can develop a musculoskeletal model to answer any question in you want – because you can always tweak the model to answer the question the way you want it answered. EMG-driven models should help us move the our basic science forward but this is still a new area of academic research

    As you have mentioned, we can never be sure whether our results are consequences of the subject biomechanics or modelling parameters. In clinical practice the potential consequences could be disastrous. So until we shore up our modelling capabilities, I think Goldilocks models for clinical application are still some way off – I think we need to get more complex before we can return to simpler models. But we’ll get there eventually.

  2. Fair points and excellent post. I think you are absolutely right that there seems to be no middle ground. There are extremely technical and highly scientific approaches that completely baffle biomechanics’ foot soldiers like clinicians. However, many of the same clinicians recognize that the approaches they employ are not delivering quality data, and are either leading to poor medical decisions, or simply being disregarded because medical staff have very little faith in the low level biomechanics.

    My experience says that once the obvious shortcomings of these simplistic models are made clear to the clinicians, they are more than willing to switch, but quickly find that they don’t really have alternatives.

    Perhaps the solution is to synthesize the highly technical research into a form that can operate behind the scenes in a clinical model!

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