Predictive Musculoskeletal Simulation Using Optimal Control: Effects of Added Limb Mass on Energy Cost and Kinematics of Walking and Running

When designing sports equipment, it is often desirable to predict how certain design parameters will affect human performance. In many instances, this requires a consideration of human musculoskeletal mechanics and adaptive neuromuscular control. Current computational methods do not represent these mechanisms, and design optimization typically requires several iterations of prototyping and human testing. This paper introduces a computational method based on musculoskeletal modeling and optimal control, which has the capability to predict the effect of mechanical equipment properties on human performance. The underlying assumption is that users will adapt their neuromuscular control according to an optimality principle, which balances task performance with a minimization of muscular effort. The method was applied to the prediction of metabolic cost and limb kinematics while running and walking with weights attached to the body. A two-dimensional musculoskeletal model was used, with nine kinematic degrees of freedom and 16 muscles. The optimal control problem was solved for two walking speeds and two running speeds, and at each speed, with 200 g and 400 g masses placed at the thigh, knee, shank and foot. The model predicted an increase in energy expenditure that was proportional to the added mass and the effect was largest for a mass placed on the foot. Specifically, the model predicted an energy cost increase of 0.74% for each 100 g mass added to the foot during running at 3.60 m/s. The model also predicted that stride length would increase by several millimetres in the same condition, relative to the model without added mass. These predictions were consistent with previously published human studies. Peak force and activation remained the same in most muscles, but increased by 26% in the hamstrings and by 17% in the rectus femoris for running at 4.27 m/s with 400 g added mass at the foot, suggesting muscle-specific training effects. This work demonstrated that a musculoskeletal model with optimal control can predict the effect of mechanical devices on human performance, and could become a useful tool for design optimization in sports engineering. The theoretical background of predictive simulation also helps explain why human athletes have specific responses when exercising in an altered mechanical environment

Effect of unsupervised home based proprioceptive training on recurrences of ankle sprain: randomised controlled trial

Objective To evaluate the effectiveness of an unsupervised proprioceptive training programme on recurrences of ankle sprain after usual care in athletes who had sustained an acute sports related injury to the lateral ankle ligament

Effect of combinations of passive and active warming on muscle temperature and sprint performance

Muscle temperature (Tm) has a significant effect on muscle function, force and power production [1], hence the adoption of warm up procedures before power based events. In the majority of sprint or power based events there are periods of maximal activity interspersed with periods of low or no activity, during which Tm may decline, adversely affecting subsequent performance. We have previously shown that Tm will decline during 30 minutes of inactivity following the completion of a warm up, and that the use of passive external heating between warm up completion and sprint cycling performance reduces Tm decline and improves peak power output [2]. The aim of the present study was to follow on from our first Tm study and determine whether, apart from using the electrical heating between warm up and event, there is an additional benefit of using the electrical heating during warm up completion on muscle temperature and subsequent measures of sprint cycling performance. The secondary goal was to look at the efficacy of a redesigned heating system covering a larger area of muscle than in [2]

Reducing muscle temperature drop post warm-up improves sprint cycling performance

PURPOSE: This study aimed to determine the effect of passive insulation versus external heating during recovery following a sprint specific warm up on thigh muscle temperature and subsequent maximal sprint performance. METHODS: On three separate occasions, 11 male cyclists (age 24.7 ± 4.2 years, height 1.82 ± 0.72m, body mass 77.9 ± 9.8 kg; mean ± S.D.) completed a standardized 15 min intermittent warm up on a cycle ergometer, followed by a 30 min passive recovery period before completing a 30 sec maximal sprint test. Muscle temperature was measured in the vastus lateralis at 1, 2 and 3 cm depth prior to and following the warm up and immediately before the sprint test. Absolute and relative peak power output was determined and blood lactate concentration was measured immediately post-exercise. During the recovery period participants wore a tracksuit top and either i) standard tracksuit pants (CONT); ii) insulated athletic pants (INS) or; iii) insulated athletic pants with integrated electric heating elements (HEAT). RESULTS: Warm up increased Tm by approximately 2.5°C at all depths, with no differences between conditions. During recovery, Tm remained elevated in HEAT compared to INS and CONT at all depths (p<0.001). Both peak and relative power output were elevated by 9.6% and 9.1% respectively in HEAT compared to CONT (both p<0.05). The increase in blood lactate concentration was greater (p<0.05) post sprint in HEAT (6.3 ± 1.8 mmol/L) but not INS (4.0 ± 1.8 mmol/L) vs. CONT (4.1 ± 1.9 mmol/L). CONCLUSION: Passive heating of the thighs between warm up completion and performance execution using pants incorporating electrically heated pads can attenuate the decline in Tm and improve sprint cycling performance

The 2BFit study: is an unsupervised proprioceptive balance board training programme, given in addition to usual care, effective in preventing ankle sprain recurrences? Design of a Randomized Controlled Trial

<p>Abstract</p> <p>Background</p> <p>There is strong evidence that athletes have a twofold risk for re-injury after a previous ankle sprain, especially during the first year post-injury. These ankle sprain recurrences could result in disability and lead to chronic pain or instability in 20 to 50% of these cases. When looking at the high rate of ankle sprain recurrences and the associated chronic results, ankle sprain recurrence prevention is important.</p> <p>Objective</p> <p>To evaluate the effect of a proprioceptive balance board training programme on ankle sprain recurrences, that was applied to individual athletes after rehabilitation and treatment by usual care.</p> <p>Methods/Design</p> <p>This study was designed as a randomized controlled trial with a follow-up of one year. Healthy individuals between 12 and 70 years of age, who were actively participating in sports and who had sustained a lateral ankle sprain up to two months prior to inclusion, were eligible for inclusion in the study. The intervention programme was compared to usual care. The intervention programme consisted of an eight-week proprioceptive training, which started after finishing usual care and from the moment that sports participation was again possible. Outcomes were assessed at baseline and every month for 12 months. The primary outcome of this study was the incidence of recurrent ankle injuries in both groups within one year after the initial sprain. Secondary outcomes were severity and etiology of re-injury and medical care. Cost-effectiveness was evaluated from a societal perspective. A process evaluation was conducted for the intervention programme.</p> <p>Discussion</p> <p>The 2BFit trial is the first randomized controlled trial to study the effect of a non-supervised home-based proprioceptive balance board training programme in addition to usual care, on the recurrence of ankle sprains in sports. Results of this study could possibly lead to changes in practical guidelines on the treatment of ankle sprains. Results will become available in 2009.</p> <p>Trial registration</p> <p>ISTRCN34177180.</p

Predictive Musculoskeletal Simulation Using Optimal Control: Effects of Added Limb Mass on Energy Cost and Kinematics of Walking and Running

When designing sports equipment, it is often desirable to predict how certain design parameters will affect human performance. In many instances, this requires a consideration of human musculoskeletal mechanics and adaptive neuromuscular control. Current computational methods do not represent these mechanisms, and design optimization typically requires several iterations of prototyping and human testing. This paper introduces a computational method based on musculoskeletal modeling and optimal control, which has the capability to predict the effect of mechanical equipment properties on human performance. The underlying assumption is that users will adapt their neuromuscular control according to an optimality principle, which balances task performance with a minimization of muscular effort. The method was applied to the prediction of metabolic cost and limb kinematics while running and walking with weights attached to the body. A two-dimensional musculoskeletal model was used, with nine kinematic degrees of freedom and 16 muscles. The optimal control problem was solved for two walking speeds and two running speeds, and at each speed, with 200 g and 400 g masses placed at the thigh, knee, shank and foot. The model predicted an increase in energy expenditure that was proportional to the added mass and the effect was largest for a mass placed on the foot. Specifically, the model predicted an energy cost increase of 0.74% for each 100 g mass added to the foot during running at 3.60 m/s. The model also predicted that stride length would increase by several millimetres in the same condition, relative to the model without added mass. These predictions were consistent with previously published human studies. Peak force and activation remained the same in most muscles, but increased by 26% in the hamstrings and by 17% in the rectus femoris for running at 4.27 m/s with 400 g added mass at the foot, suggesting muscle-specific training effects. This work demonstrated that a musculoskeletal model with optimal control can predict the effect of mechanical devices on human performance, and could become a useful tool for design optimization in sports engineering. The theoretical background of predictive simulation also helps explain why human athletes have specific responses when exercising in an altered mechanical environment

Investigating the lower ambient temperature threshold for pre-cooling to be beneficial for athletic performance

Introduction: When exercising in the heat, performance is deteriorated. It has been shown that pre-cooling can counteract this deterioration in the heat [1], but it is unclear what the effects of pre-cooling on performance are in temperate environments. Thus, the current study was performed to see if there is any difference in performance with pre-cooling at 24 °C and 27 °C, and thus if there is a threshold in environmental temperature above which pre-cooling becomes beneficial to performance. We hypothesised pre-cooling to enhance performance at both environmental temperatures

Basic exercises of the 2BFit proprioceptive balance board training programme

<p><b>Copyright information:</b></p><p>Taken from "The 2BFit study: is an unsupervised proprioceptive balance board training programme, given in addition to usual care, effective in preventing ankle sprain recurrences? Design of a Randomized Controlled Trial"</p><p>http://www.biomedcentral.com/1471-2474/9/71</p><p>BMC Musculoskeletal Disorders 2008;9():71-71.</p><p>Published online 20 May 2008</p><p>PMCID:PMC2412867.</p><p></p

Predictive musculoskeletal simulation using optimal control: effects of added limb mass on energy cost and kinematics of walking and running

When designing sports equipment, it is often desirable to predict how certain design parameters will affect human performance. In many instances, this requires a consideration of human musculoskeletal mechanics and adaptive neuromuscular control. Current computational methods do not represent these mechanisms, and design optimization typically requires several iterations of prototyping and human testing. This paper introduces a computational method based on musculoskeletal modeling and optimal control, which has the capability to predict the effect of mechanical equipment properties on human performance. The underlying assumption is that users will adapt their neuromuscular control according to an optimality principle, which balances task performance with a minimization of muscular effort. The method was applied to the prediction of metabolic cost and limb kinematics while running and walking with weights attached to the body. A two-dimensional musculoskeletal model was used, with nine kinematic degrees of freedom and 16 muscles. The optimal control problem was solved for two walking speeds and two running speeds, and at each speed, with 200 g and 400 g masses placed at the thigh, knee, shank and foot. The model predicted an increase in energy expenditure that was proportional to the added mass and the effect was largest for a mass placed on the foot. Specifically, the model predicted an energy cost increase of 0.74% for each 100 g mass added to the foot during running at 3.60 m/s. The model also predicted that stride length would increase by several millimetres in the same condition, relative to the model without added mass. These predictions were consistent with previously published human studies. Peak force and activation remained the same in most muscles, but increased by 26% in the hamstrings and by 17% in the rectus femoris for running at 4.27 m/s with 400 g added mass at the foot, suggesting muscle-specific training effects. This work demonstrated that a musculoskeletal model with optimal control can predict the effect of mechanical devices on human performance, and could become a useful tool for design optimization in sports engineering. The theoretical background of predictive simulation also helps explain why human athletes have specific responses when exercising in an altered mechanical environment

Reducing Muscle Temperature Drop Post Warm-up Improves Sprint Cycling Performance.

PURPOSE: This study aimed to determine the effect of passive insulation versus external heating during recovery following a sprint specific warm up on thigh muscle temperature and subsequent maximal sprint performance. METHODS: On three separate occasions, 11 male cyclists (age 24.7 ± 4.2 years, height 1.82 ± 0.72m, body mass 77.9 ± 9.8 kg; mean ± S.D.) completed a standardized 15 min intermittent warm up on a cycle ergometer, followed by a 30 min passive recovery period before completing a 30 sec maximal sprint test. Muscle temperature was measured in the vastus lateralis at 1, 2 and 3 cm depth prior to and following the warm up and immediately before the sprint test. Absolute and relative peak power output was determined and blood lactate concentration was measured immediately post-exercise. During the recovery period participants wore a tracksuit top and either i) standard tracksuit pants (CONT); ii) insulated athletic pants (INS) or; iii) insulated athletic pants with integrated electric heating elements (HEAT). RESULTS: Warm up increased Tm by approximately 2.5°C at all depths, with no differences between conditions. During recovery, Tm remained elevated in HEAT compared to INS and CONT at all depths (p<0.001). Both peak and relative power output were elevated by 9.6% and 9.1% respectively in HEAT compared to CONT (both p<0.05). The increase in blood lactate concentration was greater (p<0.05) post sprint in HEAT (6.3 ± 1.8 mmol/L) but not INS (4.0 ± 1.8 mmol/L) vs. CONT (4.1 ± 1.9 mmol/L). CONCLUSION: Passive heating of the thighs between warm up completion and performance execution using pants incorporating electrically heated pads can attenuate the decline in Tm and improve sprint cycling performance