Desktop inkjet printers are ubiquitous and relatively inexpensive among the variety of available printers.These inkjet printers use an array of micro fluidic pumps, nozzles based on piezoelectric actuation, to dispense individual picoliter volume ink droplets at high speed. In this paper, we show that individual pumps in desktop printers can be accessed to dispense droplets on demand. Access was obtained using the printer's command language programming. A detailed description of the access procedure is discussed. Droplets were printed on a paper as it rolled underneath the printhead, and with a minor hardware modification, they were also printed on a glass substrate. With this access, individual droplets were deposited, the smallest having an average diameter of 62 mm with a standard deviation of 6.9 mm, with a volume of $4 pL. From the intended position, the droplets had a standard deviation of 5.4 mm and 8.4 mm in the vertical and horizontal directions, respectively. The ink droplets were dispensed at a rate of 7.1 kHz. A circularity factor of 0.86 was obtained indicating that the dispensed droplets are of good quality. By replacing the ink in the cartridges with liquids of choice (e.g. cells, proteins, nanoparticles etc.), we believe it provides an opportunity for low-cost, high-speed, high-precision, picoliter volume printing for a variety of applications.

Skeletal muscles generate force, enabling movement through a series of fast electromechanical activations coordinated by the central nervous system. Understanding the underlying mechanism of such fast muscle dynamics is essential in neuromuscular diagnostics, rehabilitation medicine and sports biomechanics. The unique combination of electromyography (EMG) and ultrafast ultrasound imaging (UUI) provides valuable insights into both electrical and mechanical activity of muscle fibers simultaneously, the excitation-contraction (E-C) coupling. In this feasibility study we propose a novel non-invasive method to simultaneously track the propagation of both electrical and mechanical waves in muscles using highdensity electromyography and ultrafast ultrasound imaging (5000 fps). Mechanical waves were extracted from the data through an axial tissue velocity estimator based on one-lag autocorrelation. The E-C coupling in electrically evoked twitch contractions of the Biceps Brachii in healthy participants could successfully be tracked. The excitation wave (i.e. action potential) had a velocity of 3.9 ± 0.5 m s −1 and the subsequent mechanical (i.e. contraction) wave had a velocity of 3.5 ± 0.9 m s −1. The experiment showed evidence that contracting sarcomeres that were already activated by the action potential (AP) pull on sarcomeres that were not yet reached by the AP, which was corroborated by simulated contractions of a newly developed multisegmental muscle fiber model, consisting of 500 sarcomeres in series. In conclusion, our method can track the electromechanical muscle dynamics with high spatio-temporal resolution. Ultimately, characterizing E-C coupling in patients with neuromuscular diseases (e.g. Duchenne or Becker muscular dystrophy) may assess contraction efficiency, monitor the progression of the disease, and determine the efficacy of new treatment options.

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