The recent advances of wearable sensors are remarkable but there are still limitations that they need to be refabricated to tune the sensor for target signal. However, biological sensory systems have the inherent potential to adjust their sensitivity according to the external environment, allowing for a broad and enhanced detection. Here, we developed a Tunable, Ultrasensitive, Nature-inspired, Epidermal Sensor (TUNES) that the strain sensitivity was dramatically increased (GF ~30k) and the pressure sensitivity could be tuned (10–254 kPa−1) by preset membrane tension. The sensor adjusts the sensitivity to the pressure regime by preset tension, so it can measure a wide range (0.05 Pa–25 kPa) with the best performance: from very small signals such as minute pulse to relatively large signals such as muscle contraction and respiration. We verified its capabilities as a wearable health monitoring system by clinical trial comparing with pressure wire which is considered the current gold standard of blood pressure (r = 0.96) and home health care system by binary classification of Old’s/Young’s pulse waves via machine learning (accuracy 95%).
We thank Junggon Kim for discussion of biomimetic of spider’s tuning ability. This work is supported by funding from NRF of Korea (grant no. 2019R1H1A1080221, 2019R1F1A1063066, 2019R1C1C1007629, 2021R1A6A3A01087289, 2021R1A6A3A13045869, 2022R1A2C2093100, 2022R1A6A3A13071489). The new faculty research fund of Ajou University, and the Ajou University research fund. This work was supported by Korea Environment Industry & Technology Institute (KEITI) through Digital Infrastructure Building Project for Monitoring, Surveying, and Evaluating the Environmental Health Program, funded by Korea Ministry of Environment (MOE) (2021003330009). This research was supported by a grant of the Basic Research Program funded by the Korea Institute of Machinery and Materials (grant number: NK231A).We thank Junggon Kim for discussion of biomimetic of spider’s tuning ability. This work is supported by funding from NRF of Korea (grant no. 2019R1H1A1080221, 2019R1F1A1063066, 2019R1C1C1007629, 2021R1A6A3A01087289, 2021R1A6A3A13045869, 2022R1A2C2093100, 2022R1A6A3A13071489). The new faculty research fund of Ajou University, and the Ajou University research fund. This work was supported by Korea Environment Industry & Technology Institute (KEITI) through Digital Infrastructure Building Project for Monitoring, Surveying, and Evaluating the Environmental Health Program, funded by Korea Ministry of Environment (MOE) (2021003330009). This research was supported by a grant of the Basic Research Program funded by the Korea Institute of Machinery and Materials (grant number: NK231A).
