During running, muscles and tendons must absorb and release mechanical work to maintain the cyclic movements of the body and limbs, while also providing enough force to support the weight of the body. Direct measurements of force and fiber length in the lateral gastrocnemius muscle of running turkeys revealed that the stretch and recoil of tendon and muscle springs supply mechanical work while active muscle fibers produce high forces. During level running, the active muscle shortens little and performs little work but provides the force necessary to support body weight economically. Running economy is improved by muscles that act as active struts rather than working machines.

The agonist-antagonist myoneural interface enables bidirectional signaling for enhanced prosthetic control and sensation.

Magnetic target tracking is a low-cost, portable, and passive method for tracking materials wherein magnets are physically attached or embedded without the need for line of sight. Traditional magnet tracking techniques use optimization algorithms to determine the positions and orientations of permanent magnets from magnetic field measurements. However, such techniques are constrained by high latencies, primarily due to the numerical calculation of the gradient. In this study, we derive the analytic gradient for multiple-magnet tracking and show a dramatic reduction in tracking latency. We design a physical system comprising an array of magnetometers and one or more spherical magnets. To validate the performance of our tracking algorithm, we compare the magnet tracking estimates with state-of-the-art motion capture measurements for each of four distinct magnet sizes. We find comparable position and orientation errors to state-of-the-art magnet tracking, but demonstrate increased maximum bandwidths of 336%, 525%, 635%, and 773% for the simultaneous tracking of 1, 2, 3, and 4 magnets, respectively. We further show that it is possible to extend the analytic gradient to account for disturbance fields, and we demonstrate the simultaneous tracking of 1 to 4 magnets with disturbance compensation. These findings extend the use of magnetic target tracking to high-speed, real-time applications requiring the tracking of one or more targets without the constraint of a fixed magnetometer array. This advancement enables applications such as low-latency augmented and virtual reality interaction, volitional or reflexive control of prostheses and exoskeletons, and simplified multi-degree-of-freedom magnetic levitation.

We live in an era of wearable sensing, where our movement through the world can be continuously monitored by devices. Yet, we lack a portable sensor that can continuously monitor muscle, tendon, and bone motion, allowing us to monitor performance, deliver targeted rehabilitation, and provide intuitive, reflexive control over prostheses and exoskeletons. Here, we introduce a sensing modality, magnetomicrometry, that uses the relative positions of implanted magnetic beads to enable wireless tracking of tissue length changes. We demonstrate real-time muscle length tracking in an in vivo turkey model via chronically implanted magnetic beads while investigating accuracy, biocompatibility, and long-term implant stability. We anticipate that this tool will lay the groundwork for volitional control over wearable robots via real-time tracking of muscle lengths and speeds. Further, to inform future biomimetic control strategies, magnetomicrometry may also be used in the in vivo tracking of biological tissues to elucidate biomechanical principles of animal and human movement.

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