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Electrodermal activity (EDA) is a popular index of mental stress. State-of-the-art EDA sensors suffer from obstructiveness on the palm or low signal fidelity off the palm. Our previous invention of sub-micron-thin imperceptible graphene e-tattoos (GET) is ideal for unobstructive EDA sensing on the palm. However, robust electrical connection between ultrathin devices and rigid circuit boards is a long missing component for ambulatory use. To minimize the well-known strain concentration at their interfaces, we propose heterogeneous serpentine ribbons (HSPR), which refer to a GET serpentine partially overlapping with a gold serpentine without added adhesive. A fifty-fold strain reduction in HSPR vs. heterogeneous straight ribbons (HSTR) has been discovered and understood. The combination of HSPR and a soft interlayer between the GET and an EDA wristband enabled ambulatory EDA monitoring on the palm in free-living conditions. A newly developed EDA event selection policy leveraging unbiased selection of phasic events validated our GET EDA sensor against gold standards.

Objective: Bioimpedance sensing is a powerful technique that measures the tissue impedance and captures important physiological parameters including blood flow, lung movements, muscle contractions, body fluid shifts, and other cardiovascular parameters. This paper presents a comprehensive analysis of the modality at different arterial (ulnar, radial, tibial, and carotid arteries) and thoracic (side-rib cage and top thoracolumbar fascia) body regions and offers insights into the effectiveness of capturing various cardiac and respiratory activities. Methods: We assess the bioimpedance performance in estimating inter-beat (IBI) and inter -breath intervals (IBrI) on six-hours of data acquired in a pilot-study from five healthy participants at rest. Results: Overall, we achieve mean errors as low as 0.003 ± 0.002 and 0.67 ± 0.28 seconds for IBI and IBrI estimations, respectively. Conclusions: The results show that bioimpedance can be effectively used to monitor cardiac and respiratory activities both at limbs and upper body and demonstrate a strong potential to be adopted by wearables that aim to provide high-fidelity physiological sensing to address precision medicine needs.

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Smart rings provide unique opportunities for continuous physiological measurement. They are easy to wear, provide little burden in comparison to other smart wearables, are suitable for nocturnal settings, and can be sized to provide ideal contact between the sensors and the skin at all times. Continuous measuring of blood pressure (BP) provides essential diagnostic and prognostic value for cardiovascular health management. However, conventional ambulatory BP measurement devices operate using an inflating cuff that is bulky, intrusive, and impractical for frequent or continuous measurements. We introduce ring-shaped bioimpedance sensors leveraging the deep tissue sensing ability of bioimpedance while introducing no sensitivity to skin tones, unlike optical modalities. We integrate unique human finger finite element model with exhaustive experimental data from participants and derive optimum design parameters for electrode placement and sizes that yields highest sensitivity to arterial volumetric changes, with no discrimination against varying skin tones. BP is constructed using machine learning algorithms. The ring sensors are used to estimate arterial BP showing peak correlations of 0.81, and low error (systolic BP: 0.11 ± 5.27 mmHg, diastolic BP: 0.11 ± 3.87 mmHg) for >2000 data points and wide BP ranges (systolic: 89–213 mmHg and diastolic: 42–122 mmHg), highlighting the significant potential use of bioimpedance ring for accurate and continuous estimation of BP.