| Autor: |
Xuerong Liu, Cui Sun, Zhecheng Guo, Xiangling Xia, Qian Jiang, Xiaoyu Ye, Jie Shang, Yuejun Zhang, Xiaojian Zhu, Run‐Wei Li |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Advanced Science, Vol 10, Iss 15, Pp n/a-n/a (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2198-3844 |
| DOI: |
10.1002/advs.202300471 |
| Popis: |
Abstract The recent emergence of various smart wearable electronics has furnished the rapid development of human–computer interaction, medical health monitoring technologies, etc. Unfortunately, processing redundant motion and physiological data acquired by multiple wearable sensors using conventional off‐site digital computers typically result in serious latency and energy consumption problems. In this work, a multi‐gate electrolyte‐gated transistor (EGT)‐based reservoir device for efficient multi‐channel near‐sensor computing is reported. The EGT, exhibiting rich short‐term dynamics under voltage modulation, can implement nonlinear parallel integration of the time‐series signals thus extracting the temporal features such as the synchronization state and collective frequency in the inputs. The flexible EGT integrated with pressure sensors can perform on‐site gait information analysis, enabling the identification of motion behaviors and Parkinson's disease. This near‐sensor reservoir computing system offers a new route for rapid analysis of the motion and physiological signals with significantly improved efficiency and will lead to robust smart flexible wearable electronics. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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