Comparison of different methods for estimating muscle forces in human movement

Abstract

The aim of this study was to compare muscle-force estimates derived for human locomotion using three different methods commonly reported in the literature: static optimisation (SO), computed muscle control (CMC) and neuromusculoskeletal tracking (NMT). In contrast with SO, CMC and NMT calculate muscle forces dynamically by including muscle activation dynamics. Furthermore, NMT utilises a time-dependent performance criterion, wherein a single optimisation problem is solved over the entire time interval of the task. Each of these methods was used in conjunction with musculoskeletal modelling and experimental gait data to determine lower-limb muscle forces for self-selected speeds of walking and running. Correlation analyses were performed for each muscle to quantify differences between the various muscle-force solutions. The patterns of muscle loading predicted by the three methods were similar for both walking and running. The correlation coefficient between any two sets of muscle-force solutions ranged from 0.46 to 0.99 (p < 0.001 for all muscles). These results suggest that the robustness and efficiency of static optimisation make it the most attractive method for estimating muscle forces in human locomotion.

Keywords

Inverse dynamics forward dynamics joint torque gait biomechanics walking running motion simulation

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References

Tsirakos

Baltzopoulos

Bartlett

. Inverse optimization: functional and physiological considerations related to the force-sharing problem. Crit Rev Biomed Engng 1997; 25: 371–407.

Erdemir

McLean

Herzog

Van den Bogert

. Model-based estimation of muscle forces exerted during movements. Clin Biomech (Bristol, Avon) 2007; 22: 131–154.

Pandy

Andriacchi

. Muscle and joint function in human locomotion. Ann Rev Biomed Engng 2010; 12: 401–433.

Crowninshield

. Use of optimization techniques to+predict muscle forces. J Biomech Engng 1978; 100: 88–92.

Kaufman

Chao

EYS

. Physiological considerations of muscle force through the elbow joint. J Biomech 1989; 22: 1249–1256.

Anderson

Pandy

. Static and dynamic optimization solutions for gait are practically equivalent. J Biomech 2001; 34: 153–161.

Pandy

Garner

Anderson

. Optimal control of non-ballistic muscular movements: a constraint-based performance criterion for rising from a chair. Trans ASME, J Biomech Engng 1995; 117: 15–26.

Seth

Pandy

. A neuromusculoskeletal tracking method for estimating individual muscle forces in human movement. J Biomech 2007; 40: 356–366.

Menegaldo

De Toledo Fleury

Weber

. A ‘cheap’ optimal control approach to estimate muscle forces in musculoskeletal systems. J Biomech 2006; 39: 1787–1795.

10.

Anderson

Pandy

. Dynamic optimization of human walking. Trans ASME, J Biomech Engng 2001; 123: 381–390.

11.

Davy

Audu

. A dynamic optimization technique for predicting muscle forces in the swing phase of gait. J Biomech 1987; 20: 187–201.

12.

Thelen

Anderson

. Using computed muscle control to generate forward dynamic simulations of human walking from experimental data. J Biomech 2006; 39: 1107–1115.

13.

Thelen

Anderson

Delp

. Generating dynamic simulations of movement using computed muscle control. J Biomech 2003; 36: 321–328.

14.

Chumanov

Heiderscheit

Thelen

. The effect of speed and influence of individual muscles on hamstring mechanics during the swing phase of sprinting. J Biomech 2007; 40: 3555–3562.

15.

Glitsch

Baumann

. The three-dimensional determination of internal loads in the lower extremity. J Biomech 1997; 30: 1123–1131.

16.

Hamner

Seth

Delp

. Muscle contributions to propulsion and support during running. J Biomech 2010; 43: 2709–2716.

17.

Schache

Kim

Morgan

Pandy

. Hamstring muscle forces prior to and immediately following an acute sprinting-related muscle strain injury. Gait Posture 2010; 32: 136–140.

18.

Yokozawa

Fujii

. Muscle activities of the lower limb during level and uphill running. J Biomech 2007; 40: 3467–3475.

19.

Anderson

Pandy

. A dynamic optimization solution for vertical jumping in three dimensions. Comput Methods Biomech Biomed Engng 1999; 2: 201–231.

20.

Zajac

. Muscle and tendon: properties, models, scaling, and application to biomechanics and motor control. Crit Rev Biomed Engng 1989; 17: 359–411.

21.

O’Connor

. Bone position estimation from skin marker co-ordinates using global optimisation with joint constraints. J Biomech 1999; 32: 129–134.

22.

Cappellini

Ivanenko

Poppele

Lacquaniti

. Motor patterns in human walking and running. J Neurophysiol 2006; 95: 3426–3437.

23.

Delp

Anderson

Arnold

. OpenSim: open-source software to create and analyze dynamic simulations of movement. IEEE Trans Biomed Engng 2007; 54: 1940–1950.

24.

Delp

Loan

Hoy

. An interactive graphics-based model of the lower extremity to study orthopaedic surgical procedures. IEEE Trans Biomed Engng 1990; 37: 757–767.

25.

Martin

Brown

Anderson

Spirduso

. A governing relationship for repetitive muscular contraction. J Biomech 2000; 33: 969–974.

26.

Cavagna

Komarek

Mazzoleni

. The mechanics of sprint running. J Physiol 1971; 217: 709–721.

27.

Ward-Smith

. A mathematical theory of running, based on the first law of thermodynamics, and its application to the performance of world-class athletes. J Biomech 1985; 18: 337–349.

28.

Weyand

Sternlight

Bellizzi

Wright

. Faster top running speeds are achieved with greater ground forces not more rapid leg movements. J Appl Physiol 2000; 89: 1991–1999.