Prospective Cohort Study

In order to stimulate further adaptation toward specific training goals, progressive resistance training (RT) protocols are necessary The optimal characteristics of strength-specific programs include the use of concentric (CON), eccentric (ECC), and isometric muscle actions and the performance of bilateral and unilateral single- and multiple-joint exercises In addition, it is recommended that strength programs sequence exercises to optimize the preservation of exercise intensity (large before small muscle group exercises, multiple-joint exercises before single-joint exercises, and higher-intensity before lower-intensity exercises) For novice (untrained individuals with no RT experience or who have not trained for several years) training, it is recommended that loads correspond to a repetition range of an 8-12 repetition maximum (RM) For intermediate (individuals with approximately 6 months of consistent RT experience) to advanced (individuals with years of RT experience) training, it is recommended that individuals use a wider loading range from 1 to 12 RM in a periodized fashion with eventual emphasis on heavy loading (1-6 RM) using 3- to 5-min rest periods between sets performed at a moderate contraction velocity (1-2 s CON; 1-2 s ECC) When training at a specific RM load, it is recommended that 2-10% increase in load be applied when the individual can perform the current workload for one to two repetitions over the desired number The recommendation for training frequency is 2-3 d·wk -1 for novice training, 3-4 d·wk -1 for intermediate training, and 4-5 d·wk -1 for advanced training Similar program designs are recommended for hypertrophy training with respect to exercise selection and frequency For loading, it is recommended that loads corresponding to 1-12 RM be used in periodized fashion with emphasis on the 6-12 RM zone using 1- to 2-min rest periods between sets at a moderate velocity Higher volume, multiple-set programs are recommended for maximizing hypertrophy Progression in power training entails two general loading strategies: 1) strength training and 2) use of light loads (0-60% of 1 RM for lower body exercises; 30-60% of 1 RM for upper body exercises) performed at a fast contraction velocity with 3-5 min of rest between sets for multiple sets per exercise (three to five sets) It is also recommended that emphasis be placed on multiple-joint exercises especially those involving the total body For local muscular endurance training, it is recommended that light to moderate loads (40-60% of 1 RM) be performed for high repetitions (>15) using short rest periods (<90 s) In the interpretation of this position stand as with prior ones, recommendations should be applied in context and should be contingent upon an individual's target goals, physical capacity, and training status

/pdf/progression-models-in-resistance-training-for-healthy-adults-1vkvqzcu18.pdf

Progression Models in Resistance Training for Healthy Adults

Noise — random disturbances of signals — poses a fundamental problem for information processing and affects all aspects of nervous-system function. However, the nature, amount and impact of noise in the nervous system have only recently been addressed in a quantitative manner. Experimental and computational methods have shown that multiple noise sources contribute to cellular and behavioural trial-to-trial variability. We review the sources of noise in the nervous system, from the molecular to the behavioural level, and show how noise contributes to trial-to-trial variability. We highlight how noise affects neuronal networks and the principles the nervous system applies to counter detrimental effects of noise, and briefly discuss noise's potential benefits.

/pdf/noise-in-the-nervous-system-22k10mncs2.pdf

Noise in the nervous system.

羟氨苄青霉素引起大疱性类天疱疮样疹

Mini Mental State

Neuromuscular Control Passive Mechanical Coupling Versus Active Human Finger Independence: Limitations due to

elementsprimarily from stretch of the common-elastic Nonlinear summation of force in cat soleus muscle

The effectiveness of exoskeletons could be enhanced by incorporating low back muscle fatigue estimates in their control. The aim of the present study was to evaluate whether low back muscle fatigue can be estimated using the spectral content of trunk extensor muscle high-density EMG (HDEMG) by considering the motor unit action potential conduction velocity (MUAP CV) as a reference. The HDEMG-based MUAP CV was estimated for multiple sites on the lower back consistently throughout a 30 degrees lumbar flexion endurance trial. Significant linear relationships were observed between MUAP CV and spectral content. However, MUAP CV and spectral changes over time did not show the expected decrease, probably due to additional recruitment of motor units or alternating activity of synergistic muscles. The anatomical information about the sites that allow MUAP CV estimation can be valuable for future low back muscle fatigue estimations.

Can HDEMG-Based Low Back Muscle Fatigue Estimates Be Used in Exoskeleton Control During Prolonged Trunk Bending? A Pilot Study

In human walking, power for propulsion is generated primarily via ankle and hip muscles. The addition of a ‘passive’ hip spring to simple bipedal models appears more efficient than using only push-off impulse, at least, when hip spring associated energetic costs are not considered. Hip flexion and retraction torques, however, are not ‘free’, as they are produced by muscles demanding metabolic energy. Studies evaluating the inclusion of hip actuation costs, especially during the swing phase, and the hip actuation’s energetic benefits are few and far between. It is also unknown whether these possible benefits/effects may depend on speed. We simulated a planar flat-feet model walking stably over a range of speeds. We asked whether the addition of independent hip flexion and retraction remains energetically beneficial when considering work-based metabolic cost of transport (MCOT) with different efficiencies of doing positive and negative work. We found asymmetric hip actuation can reduce the estimated MCOT relative to ankle actuation by up to 6%, but only at medium speeds. The corresponding optimal strategy is zero hip flexion and some hip retraction actuation. The reason for this reduced MCOT is a reduction in collision loss being larger than the associated increase in hip negative work. Both terms require positive mechanical work to compensate, yielding a larger reduction in metabolic work per step than the reduction in step length. Our study shows how ankle actuation, hip flexion, and retraction actuation can be coordinated to reduce MCOT.

The energetic effect of hip flexion and retraction in walking at different speeds: a modeling study

Estimation of low-back load can be used to determine the assistance to be provided by an actuated back-support exoskeleton. To this end, an EMG-driven muscle model and a regression model can be implemented. The goal of the regression model is to reduce the number of required sensors for load estimation. Both models need to be calibrated. This study aims to find the impacts of limiting calibration data on low-back loading estimation through these models.

Calibrating an EMG-Driven Muscle Model and a Regression Model to Estimate Moments Generated Actively by Back Muscles for Controlling an Actuated Exoskeleton with Limited Data

Jaap H. van Dieën

Papers

Neuromuscular Control Passive Mechanical Coupling Versus Active Human Finger Independence: Limitations due to

elementsprimarily from stretch of the common-elastic Nonlinear summation of force in cat soleus muscle

Can HDEMG-Based Low Back Muscle Fatigue Estimates Be Used in Exoskeleton Control During Prolonged Trunk Bending? A Pilot Study

The energetic effect of hip flexion and retraction in walking at different speeds: a modeling study

Calibrating an EMG-Driven Muscle Model and a Regression Model to Estimate Moments Generated Actively by Back Muscles for Controlling an Actuated Exoskeleton with Limited Data