Your therapists and doctors should understand this extremely well and update your stroke protocol on reaching and grabbing to take this into account.
http://neurosciencenews.com/grip-force-neuroscience-2332/
It’s been a long day. You open your fridge and grab a nice,
cold beer. A pretty simple task, right? Wrong. While you’re debating
between an IPA and a lager, your nervous system is calculating a complex
problem: how hard to grasp the can.
We never know exactly how heavy or slippery an object will be until
we grab it; we need a way of predicting those things so that objects
don’t slip out of our hands. For years, researchers thought that grip
force — how hard we grab an object — parallels the expected load force —
the weight — of the object.
Now, researchers at the Harvard John A. Paulson School of Engineering
and Applied Science (SEAS) have shown that the most important factor in
determining grip force isn’t what you can estimate about the object but
rather what you can’t. Maurice Smith, the Gordon McKay Professor of
Bioengineering, and postdoctoral fellow Alkis Hadjiosif have shown that
the amount of variability associated with estimating an object’s
physical dynamics, such as its weight, is the most important factor in
determining grip force. They described their findings in the Journal of Neuroscience.
Take the can of cold beer. When you grab it, the minimum grip force
required depends on the weight of the beer and the friction coefficient
between its surface and your fingers. On top of that minimal force, your
nervous system implicitly factors in a safety margin to protect against
miscalculations, such as if the can is heavier or more slippery than
you may have expected.Previous research assumed this safety margin was a
fixed fraction of the minimum required grip force, like the safety
factors widely used in engineering design, but Smith and his team
wondered if this was the most effective approach.
“Wouldn’t it be more efficient for the motor system to reduce the
safety margin when variability or uncertainty was low and increase it
when variability was high,” Smith asked. “This line of thinking leads to
the idea that the safety margin should be determined not by the nervous
system’s estimate of the minimum required force but by its estimate of
the uncertainty about that force. As it turns out, that’s exactly what
happens.”
“It turns out that by making the safety margin proportional to
variability, it’s possible to maintain control over the probability of
failure in a uniform manner in both high and low uncertainty
environments. This achieves a fixed statistical confidence against
failures like slip,” added Hadjiosif.
If you’re grabbing a clear glass of beer that you’re familiar with,
the amount of uncertainty is low. You know the weight of the glass
itself, how slippery it is, what’s in it, how much and whether or not
it’s sloshing around. From this, your motor system can make a pretty
precise estimate about the glass’s dynamics and safely use a grip force
just above the minimum required force, with only a small safety margin.
But if you’re grabbing an opaque cup or an object you’re unfamiliar
with, the higher uncertainty about required grip force would necessitate
a stronger grasp with a higher safety margin to minimize the chance of
slip.
Dynamical variability in the environment also comes into play. You
hold your beer more tightly standing in a crowded bar, where someone
might bump into you and your beer, than sitting in your living room at
home.
Understanding the mechanisms behind grip force control could result
in a better understanding of how neurological disorders affect the
neural calculations that underlie this control.
“We are still in our in the infancy in understanding how the nervous
system goes about making many of the calculations it needs. For example,
we don’t know how neurons compute estimates of variability and
uncertainty. Grip force control may be a good model system for answering
that question,” said Smith.
Smith and Hadjiosif observed that grip forces are three times more
sensitive to the standard deviation of the load force than to the
expected load force.
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