Sensory rehabilitation in pediatric patients with traumatic spinal cord injury is challenging due to the ongoing development of their nervous systems. However, these sensory problems often result in nonuse of the impaired limb, which disturbs impaired limb rehabilitation and leads to overuse of the contralateral limb and other physical or psychological issues that may persist. Here, we introduce a soft nanomembrane sensor-enabled wearable glove system that wirelessly delivers a haptic sensation from the hand with tactile feedback responses for sensory impairment assistance. The smart glove system uses gold nanomembranes, copper-elastomer composites, and laser-induced graphene for the sensitive detection of pressure, temperature, and strain changes. The nanomaterial sensors are integrated with low-profile tactile actuators and wireless flexible electronics to offer real-time sensory feedback. The wearable system's thin-film sensors demonstrate 98% and 97% accuracy in detecting pressure and finger flexion, respectively, along with a detection coverage of real-life temperature changes as an effective rehabilitation tool. Collectively, the upper-limb sensory impairment assistance system embodies the latest in soft materials and wearable technology to incorporate soft sensors and miniaturized actuators and maximize its compatibility with human users, offering a promising solution for patient sensory rehabilitation.

Soft, stretchable sensors, such as artificial skins or tactile sensors, are attractive for numerous soft robotic applications due to the low material compliance. Conductive polymers are a necessary component of many soft sensors, and this work presents the electromechanical characterization of 3D-printable conductive polymer composites. Dog-bone shaped samples were 3D printed using a digital light processing (DLP)-based 3D printer for characterization. The 3D printable resin consists of monomer, crosslinker, conductive nano-filler, and a photo-initiator. The characterization was performed in two tracks. First, the effect of two different crosslinkers was investigated with different compositions and second, the effect of concentration of conductive nano-fillers was explored. Crosslinkers were chosen by referring to previous studies, and carbon nanotubes (CNTs) were utilized as conductive nano-fillers. The samples were 3D printed and characterized using an electromechanical test setup. To demonstrate utility for 3D printed soft robotics, a capacitance-based joystick sensor composed of both conductive and non-conductive resins was 3D printed.

Stenosis and dissection of carotid arteries are life threatening conditions that can lead to stroke, hence requiring early detection. In this work, we propose the use of a wearable seismometer patch, StethX's Seismic Patch, to capture and analyze carotid artery vibrations for non-invasive diagnosis. The patch uses a hermetically sealed wideband seismometer with out-of-plane sensitivity to detect subtle blood-flow-induced vibrations. We validated our approach using a phantom model simulating varying carotid arterial constrictions and then collected data from multiple patients with clinically confirmed carotid conditions. Wavelet-based spectral analysis revealed distinct acoustic signatures correlating with stenosis severity and dissection, demonstrating the Seismic Patch potential as a fast, accessible, and reliable diagnostic tool.

Carotid artery disease, including atherosclerotic stenosis and non-atherosclerotic abnormalities, substantially increases ischemic stroke risk and motivates accessible tools for early screening. Current diagnostic pathways rely on clinic-based imaging and skilled operators, creating barriers to frequent monitoring and scalable deployment. We present a non-invasive diagnostic approach using a wearable MEMS accelerometer patch to capture mechano-acoustic vibrations generated by carotid blood flow at the neck. The miniature device integrates a hermetically sealed wideband accelerometer with out-of-plane sensitivity and micro-g resolution to detect subtle flow-induced vibrations. We validated the approach in a carotid flow phantom and a clinical study of 74 patients. Time–frequency representations were computed using the continuous wavelet transform (CWT), from which interpretable spectral and scalogram-derived candidate biomarkers were extracted. Six non-redundant features were then selected for multivariate classification, distinguishing pathology, defined as 50% or greater stenosis or a non-atherosclerotic abnormality, from non-pathology, defined as less than 50% stenosis. Finally, model interpretability was assessed using SHapley Additive exPlanations (SHAP) to quantify the contribution of each biomarker to predicted disease probability. These findings resulted in an AUROC of 0.97 and AUPR of 0.947, with 81.7% sensitivity and 93.6% specificity at the prespecified threshold (precision 85.4%, F1 83.5%, accuracy 89.8%), highlighting the potential of wearable seismic sensing combined with interpretable machine learning for fast screening and longitudinal monitoring of the right and left carotid arteries.

A wearable multimodal sensory feedback device (SFD) was developed to communicate proprioceptive information from a robotic grasper onto the operator’s forearm. The robotic grasper could pick up objects through a pinching motion and was composed of two fingers, each able to open and close in a mirror of the other. The aperture amount of each of the grasper’s fingers was mapped onto the SFD which uses two separate actuators that induced skin-stretch and implemented vibrotactile stimuli to communicate this information to the user. This paper evaluates the extent to which the SFD can effectively communicate the grasper’s proprioceptive information using skin stretch feedback that is maintained with vibrations. Subjects were asked to manipulate the grasper blindly guided by their natural proprioceptive feedback only (NO), their natural proprioceptive feedback and skin-stretch feedback (NS), skin-stretch feedback only (SS), and skin-stretch and vibrotactile stimulation (SV). The experiments’ results indicate that the SFD can effectively communicate proprioceptive sensory information and enhance the body’s natural proprioceptive sense.