Hierarchically resistive skins as specific and multimetric on-throat wearable biosensors

Gong, Shu Ping; Zhang, Xin; Nguyen, Xuan Anh; Shi, Qianqian; Lin, Fenge; Chauhan, Sunita; Ge, Zongyuan; Cheng, Wenlong

doi:10.1038/s41565-023-01383-6

Cited by 56 publications

(31 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A proper encapsulation is necessary to improve the durability. 160 To monitor the complex movements of the human body, ultrasensitive 515 and specific 516 strain sensors based on nanocracks were also proposed, and it is possible to distinguish multiple types of movements with the help of machine learning.…”

Section: Strain Sensorsmentioning

confidence: 99%

“…675 Machine learning algorithms offer promising solutions to extract valuable insights from these signals, enabling accurate recognition, classification, and decision making. A number of biophysical and physiological signals, including ECG, 676 heart rate, 677 blood pressure, 260 hand gestures, 177 speech, 519 body motion, 516 and more, have been powered with machine learning techniques for automated analysis, recognition, and classification purposes. ECG signals are widely used for cardiac monitoring and analysis.…”

Section: Machine Learning and Algorithm Developmentmentioning

confidence: 99%

See 1 more Smart Citation

Materials-Driven Soft Wearable Bioelectronics for Connected Healthcare

Gong,

Lu,

Yin

et al. 2024

Chem. Rev.

Self Cite

View full text Add to dashboard Cite

In the era of Internet-of-things, many things can stay connected; however, biological systems, including those necessary for human health, remain unable to stay connected to the global Internet due to the lack of soft conformal biosensors. The fundamental challenge lies in the fact that electronics and biology are distinct and incompatible, as they are based on different materials via different functioning principles. In particular, the human body is soft and curvilinear, yet electronics are typically rigid and planar. Recent advances in materials and materials design have generated tremendous opportunities to design soft wearable bioelectronics, which may bridge the gap, enabling the ultimate dream of connected healthcare for anyone, anytime, and anywhere. We begin with a review of the historical development of healthcare, indicating the significant trend of connected healthcare. This is followed by the focal point of discussion about new materials and materials design, particularly low-dimensional nanomaterials. We summarize material types and their attributes for designing soft bioelectronic sensors; we also cover their synthesis and fabrication methods, including top-down, bottom-up, and their combined approaches. Next, we discuss the wearable energy challenges and progress made to date. In addition to front-end wearable devices, we also describe back-end machine learning algorithms, artificial intelligence, telecommunication, and software. Afterward, we describe the integration of soft wearable bioelectronic systems which have been applied in various testbeds in real-world settings, including laboratories that are preclinical and clinical environments. Finally, we narrate the remaining challenges and opportunities in conjunction with our perspectives.

show abstract

Section: Strain Sensorsmentioning

confidence: 99%

Section: Machine Learning and Algorithm Developmentmentioning

confidence: 99%

Materials-Driven Soft Wearable Bioelectronics for Connected Healthcare

Gong,

Lu,

Yin

et al. 2024

Chem. Rev.

Self Cite

View full text Add to dashboard Cite

show abstract

“…The plasticity of these synapses, meaning their ability to change their strength and connectivity over time, is crucial for learning and memory. − Neuromorphic electronic systems, proposed by Carver Mead in the late 1980s to early 1990s, aim to design electronic systems that mimic the structure, function, and plasticity of biological neural networks (Figure ). While neuromorphic circuits based on silicon complementary metal-oxide-semiconductor (CMOS) technology have been developed to replicate synaptic functionalities, classical computing systems traditionally relied on the von Neumann computing architecture and suffered from limitations due to the separation of memory from processing, leading to issues such as speed latency, high energy consumption, and limited communication bandwidth. ,,, To overcome these drawbacks, researchers have developed novel artificial synapses based on a variety of materials and structures, typically implemented with 2-terminal memristors or 3-terminal transistors. ,,, These devices are capable of achieving neuromorphic functions, such as short-term and long-term plasticity (STP and LTP), similar to the synapses in biological systems. ,, In recent years, there has been growing interest in using flexible electronics for the development of artificial neuron devices. ,, Flexible electronics refer to electronic devices and systems that can bend, stretch, and conform to their surroundings without breaking or losing their functionality. ,− Flexible electronics possess mechanical properties similar to human organs and tissues, showing great advantages for the development of artificial neuron devices. ,,− They can be easily integrated with biological tissues and structures, allowing for seamless interaction with the nervous system and the development of biointerfaces and biohybrid systems. − …”

Section: Introductionmentioning

confidence: 99%

Artificial Neuron Devices

He,

Wang,

et al. 2023

Chem. Rev.

View full text Add to dashboard Cite

Efforts to design devices emulating complex cognitive abilities and response processes of biological systems have long been a coveted goal. Recent advancements in flexible electronics, mirroring human tissue’s mechanical properties, hold significant promise. Artificial neuron devices, hinging on flexible artificial synapses, bioinspired sensors, and actuators, are meticulously engineered to mimic the biological systems. However, this field is in its infancy, requiring substantial groundwork to achieve autonomous systems with intelligent feedback, adaptability, and tangible problem-solving capabilities. This review provides a comprehensive overview of recent advancements in artificial neuron devices. It starts with fundamental principles of artificial synaptic devices and explores artificial sensory systems, integrating artificial synapses and bioinspired sensors to replicate all five human senses. A systematic presentation of artificial nervous systems follows, designed to emulate fundamental human nervous system functions. The review also discusses potential applications and outlines existing challenges, offering insights into future prospects. We aim for this review to illuminate the burgeoning field of artificial neuron devices, inspiring further innovation in this captivating area of research.

show abstract

“…With the rapid development of artificial intelligence (AI) and the Internet of things (IoT) on a global scale, wearable electronics have significantly changed our daily life and extensively applied in biomimetic skin, , human-computer interaction, healthcare management, soft robotics, and medical diagnosis . One of the paramount challenges in the development of next-generation wearable devices is to fabricate advanced flexible sensors capable of transforming weak or imperceptible external stimuli into easily recognizable electronic signals .…”

Section: Introductionmentioning

confidence: 99%