Multi-receptor skin with highly sensitive tele-perception somatosensory.
Yan DuPenghui ShenTian-Ling RenYuyang ZhangLuyao JiaXiong PuFeiyao YangTian-Ling RenDaping ChuZhong Lin WangDi WeiPublished in: Science advances (2024)
The limitations and complexity of traditional noncontact sensors in terms of sensitivity and threshold settings pose great challenges to extend the traditional five human senses. Here, we propose tele-perception to enhance human perception and cognition beyond these conventional noncontact sensors. Our bionic multi-receptor skin employs structured doping of inorganic nanoparticles to enhance the local electric field, coupled with advanced deep learning algorithms, achieving a Δ V /Δ d sensitivity of 14.2, surpassing benchmarks. This enables precise remote control of surveillance systems and robotic manipulators. Our long short-term memory-based adaptive pulse identification achieves 99.56% accuracy in material identification with accelerated processing speeds. In addition, we demonstrate the feasibility of using a two-dimensional (2D) sensor matrix to integrate real object scan data into a convolutional neural network to accurately discriminate the shape and material of 3D objects. This promises transformative advances in human-computer interaction and neuromorphic computing.
Keyphrases
- deep learning
- endothelial cells
- convolutional neural network
- pluripotent stem cells
- machine learning
- computed tomography
- blood pressure
- working memory
- artificial intelligence
- minimally invasive
- multiple sclerosis
- soft tissue
- magnetic resonance
- fluorescent probe
- data analysis
- robot assisted
- bioinformatics analysis
- transcranial direct current stimulation