Residual force enhancement due to active muscle lengthening allows similar reductions in neuromuscular activation during position-and force-control tasks

Background:Residual torque enhancement(rTE)is the increase in torque observed during the isometric steady state following active muscle lengthening when compared with a fixed-end isometric contraction at the same muscle length and level of neuromuscular activation.In the rTE state,owing to an elevated contribution of passive force to total force production,less active force is required,and there is a subsequent reduction in activation.In vivo studies of rTE reporting an activation reduction are often performed using a dynamometer,where participants contract against a rigid restraint,resisting a torque motor.rTE has yet to be investigated during a position task,which involves the displacement of an inertial load with positional control.Methods:A total of 12 participants(6 males,6 females;age=22.8±1.1 years,height=174.7±8.6 cm,mass=82.1±37.7 kg;mean±SD)completed torque-and position-matching tasks at 60%maximum voluntary contraction for a fixed-end isometric contraction and an isometric contraction following active lengthening of the ankle dorsiflexors.Results:There were no significant differences in activation between torque-and position-matching tasks(p=0.743),with^27%activation reduction following active lengthening for both task types(p<0.001).Conclusion:These results indicate that rTE is a feature of voluntary,position-controlled contractions.These findings support and extend previous findings of isometric torque-control conditions to position-controlled contractions that represent different tasks of daily living.

A concurrent optimization approach for energy efficient multiple axis positioning tasks

Automated production systems typically comprise numerous electrical servo drives,many of which conduct positioning motions,e.g.for handling or manipulation tasks.The power electronics of modern multi-axis systems often comprise coupled DC-links,enabling for internal exchange of recuperative brake energy.However,the motion sequences of manipulators are often commanded at maximum dynamics for minimum time motion,neglecting possible optimization potential,e.g.available idle time,leading to inefficient energy management.A robust trajectory optimization approach based on the particle swarm algorithm and well-established path planning methods is presented for the adaption of multi-axis positioning tasks with only two parameters per axis and positioning motion during system run-time.Experimental results prove that,depending on the positioning task and chosen optimization constraints,energy demands are distinctly reduced.The approach is applicable to diverse multi-axis configurations and enables for considerable energy savings without additional hardware invest.