Strength and Fatigue: Experiments and Modeling - Human Motion Simulation: Predictive Dynamics - page 131

Strength is considered to be relatively stable from the third (i.e., 20 s) to the
fifth decades of life (i.e., 40 s), but typically begins to decay sometime after the
sixth decade of life (i.e., in 50 s or 60 s) ( Stoll et al., 2000 ). This suggests DH
models of strength can be used to represent “young” adults across several decades
of age. Whereas others have suggested using linear decays in strength models
from the 20 s to the 70 s, data suggest constant strength models through the 40 s
or 50 s are reasonably well substantiated ( Bohannon, 1997; Horstmann et al.,
1999; Stoll et al., 2000 ). Future advances in DH modeling may move toward
more exact models of strength, by decade of life, but this level of fidelity does
not currently have sufficient data to suggest its usefulness. However, DHs repre-
senting the older adult population (i.e., over 65 years) clearly would benefit from
strength models specific to this cohort. This loss of strength with increasing age
is likely due to a complex array of factors such as relative inactivity, sub-
threshold disease or pathology, or age-related changes in cell health and adapta-
tion. While age-related declines in health can vary between men and women or
between muscle groups, one simple modeling approach is to reduce young-adult
strength by a constant percentage (e.g., 15%), which could also be increased with
advancing age.
Changes in strength with training can be quite large and specific to the muscle
groups involved. While this is not modeled directly by most DH strength models
today, it can be represented indirectly using population statistics. Most normative
data collected on strength will include a heterogeneous population, resulting in
observed standard deviations in the range of 20

30% of mean strength values
( Bohannon, 1997; Frey-Law et al., 2012b; Griffin, 1987; Horstmann, Maschmann
et al., 1999 ). Thus, these data sets can be used to model stronger or more highly
trained individuals using the mean plus some multiple of the observed standard
deviation (i.e., higher strength population percentiles). Conversely, untrained or
weak individuals can be modeled using the observed mean minus some multiple of
the standard deviation (i.e., lower strength population percentiles). Direct models
attempting to link training and strength are not likely to be practical anytime soon,
however, as training effects are often non-linear, occurring in proportion to the
baseline level of training, frequency and intensity of training, etc. For example,
individuals that are sedentary will see larger adaptations with training than some-
one who is already near their peak performance level.

6.3 Strength assessment
The actual assessment of strength can be accomplished in several ways, each mea-
suring different aspects of muscle strength capability. Isometric (i.e., constant
length, static) assessments are performed at specific joint angles and typically used
to evaluate torque-angle relationships. These measurements are often assessed
using isokinetic dynamometers (set to work isometrically) or load cells (force
assessments at a constant moment arm length). Isotonic (i.e., constant

load)