Sel Kaan, Osman Deen, Huerta Noah, Edgar Arabella, Pettigrew Roderic I, Jafari Roozbeh
Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA.
Department of Mechanical Engineering, Texas A&M University, College Station, TX, USA.
NPJ Digit Med. 2023 Mar 30;6(1):59. doi: 10.1038/s41746-023-00796-w.
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.
智能指环为持续的生理测量提供了独特的机会。它们佩戴方便，与其他智能可穿戴设备相比负担较小，适用于夜间环境，并且尺寸合适，能始终确保传感器与皮肤之间的理想接触。持续测量血压（BP）对心血管健康管理具有重要的诊断和预后价值。然而，传统的动态血压测量设备使用的是充气袖带，体积庞大、具有侵入性，且不适合频繁或持续测量。我们推出了环形生物阻抗传感器，它利用生物阻抗的深层组织传感能力，并且与光学模式不同，对肤色不敏感。我们将独特的人体手指有限元模型与来自参与者的详尽实验数据相结合，得出电极放置和尺寸的最佳设计参数，这些参数对动脉容积变化具有最高的灵敏度，且不会因肤色不同而产生偏差。血压通过机器学习算法构建。环形传感器用于估计动脉血压，对于超过2000个数据点和较宽的血压范围（收缩压：89 - 213 mmHg，舒张压：42 - 122 mmHg），其峰值相关性为0.81，误差较低（收缩压：0.11±5.27 mmHg，舒张压：0.11±3.87 mmHg），这突出了生物阻抗指环在准确和持续估计血压方面的巨大潜在用途。
