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Full-body motion capture is essential for the study of body movement. Video-based, markerless, mocap systems are, in some cases, replacing marker-based systems, but hybrid systems are less explored. We develop methods for coregistration between 2D video and 3D marker positions when precise spatial relationships are not known a priori. We illustrate these methods on three-ball cascade juggling in which it was not possible to use marker-based tracking of the balls, and no tracking of the hands was possible due to occlusion. Using recorded video and motion capture, we aimed to transform 2D ball coordinates into 3D body space as well as recover details of hand motion. We proposed four linear coregistration methods that differ in how they optimize ball-motion constraints during hold and flight phases, using an initial estimate of hand position based on arm and wrist markers. We found that minimizing the error between ball and hand estimate was globally suboptimal, distorting ball flight trajectories. The best-performing method used gravitational constraints to transform vertical coordinates and ball-hold constraints to transform lateral coordinates. This method enabled an accurate description of ball flight as well as a reconstruction of wrist movements. We discuss these findings in the broader context of video/motion capture coregistration. 

Atherosclerosis is a prominent cause of coronary artery disease and broader cardiovascular diseases, the leading cause of death worldwide. Angioplasty and stenting is a common treatment, but in-stent restenosis, where the artery re-narrows, is a frequent complication. Restenosis is detected through invasive procedures and is not currently monitored frequently for patients. Here, we report an implantable vascular bioelectronic device using a newly developed miniaturized strain sensor via microneedle printing methods. A capillary-based printing system achieves high-resolution patterning of a soft, capacitive strain sensor. Ink and printing parameters are evaluated to create a fully printed sensor, while sensor design and sensing mechanism are studied to enhance sensitivity and minimize sensor size. The sensor is integrated with a wireless vascular stent, offering a biocompatible, battery-free, wireless monitoring system compatible with conventional catheterization procedures. The vascular sensing system is demonstrated in an artery model for monitoring restenosis progression. Collectively, the artery implantable bioelectronic system shows the potential for wireless, real-time monitoring of various cardiovascular diseases and stent-integrated sensing/treatments. 

Seismocardiography (SCG) is the measure of local vibrations in the chest due to heartbeats. Typically, SCG signals are measured using rigid integrated circuit (IC) accelerometers and bulky electronics. However, as alternatives, recent studies of emerging flexible sensors show promise. Here, we introduce the development of wireless soft capacitive sensors that require no battery or rigid IC components for measuring SCG signals for cardiovascular health monitoring. Both the capacitive and inductive components of the circuit are patterned with laser micromachining of a polyimide-coated copper and are encapsulated with an elastomer. The wearable soft sensor can detect small strain changes on the skin, which is wirelessly measured by examining the power reflected from the antenna at a stimulating frequency. The performance of the device is verified by comparing the fiducial points to SCG measured by a commercial accelerometer and electromyograms from a commercial electrode. Overall, the human subject study demonstrates that the fiducial points are consistent with data from commercial devices, showing the potential of the ultrathin soft sensors for ambulatory cardiovascular monitoring without bulky electronics and rigid components. 

Abstract Activities and physical effort have been commonly estimated using a metabolic rate through indirect calorimetry to capture breath information. The physical effort represents the work hardness used to optimize wearable robotic systems. Thus, personalization and rapid optimization of the effort are critical. Although respirometry is the gold standard for estimating metabolic costs, this method requires a heavy, bulky, and rigid system, limiting the system’s field deployability. Here, this paper reports a soft, flexible bioelectronic system that integrates a wearable ankle-foot exoskeleton, used to estimate metabolic costs and physical effort, demonstrating the potential for real-time wearable robot adjustments based on biofeedback. Data from a set of activities, including walking, running, and squatting with the biopatch and exoskeleton, determines the relationship between metabolic costs and heart rate variability root mean square of successive differences (HRV-RMSSD) (R = −0.758). Collectively, the exoskeleton-integrated wearable system shows potential to develop a field-deployable exoskeleton platform that can measure wireless real-time physiological signals.