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Collaboration networkThis graph maps the connections between all the collaborators of {}'s publications listed on this page.
Each link represents a collaboration on the same publication. The thickness of the link represents the number of collaborations.
Use the mouse wheel or scroll gestures to zoom into the graph.
You can click on the nodes and links to highlight them and move the nodes by dragging them.
Hold down the "Ctrl" key or the "⌘" key while clicking on the nodes to open the list of this person's publications.
Word cloudA word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Chen, F., Cao, L., Wu, D., Zhang, E., Wang, T., Jiang, X., Chen, J., Wu, H., Lin, S., Hou, Q., Zhu, J., Yang, J., Sawan, M., & Zhang, Y. (2025). Acoustic inspired brain-to-sentence decoder for logosyllabic language. Cyborg and Bionic Systems, 0257 (35 pages). External link
Chen, J., Wu, H., Tian, F., Hou, Q., Lin, S., Yang, J., & Sawan, M. (2024, May). A Low-Power Level-Crossing Analog-to-Spike Converter Intended for Neuromorphic Biomedical Applications [Paper]. IEEE International Symposium on Circuits and Systems (ISCAS 2024), Singapore, Singapore. External link
Chen, J., Wu, H., Eskandari, R., Liu, X., Lin, S., Hou, Q., Tian, F., Zou, W., Yang, J., & Sawan, M. (2024, April). A Neuron-Inspired 0.0032mm2−1.38μW/Ch Wireless Implantable Neural Interface with Direct Multiplexing Front-End and Event-Driven Spike Detection and Transmission [Paper]. IEEE Custom Integrated Circuits Conference (CICC 2024), Denver, CO, USA. External link
Wu, H., Tan, Z., Liu, X., Chen, J., Zou, W., Hou, Q., Lin, S., Mao, Y., Kuang, X., Yang, J., & Sawan, M. (2025, May). Efficient Self-Adaptive Pseudo-Resistor with Rapid Settling and High Linearity for Neurorecording Front-End Circuits [Paper]. IEEE International Symposium on Circuits and Systems (ISCAS 2025), London, United Kingdom. External link
Wu, H., Tan, Z., Liu, X., Chen, J., Zou, W., Hou, Q., Liu, S., Mao, Y., Kuang, X., Yang, J., & Sawan, M. (2025). Self-Adaptive Pseudo-Resistors Enabling Millisecond-Level Artifact Recovery and High-Linearity for Neural Recording Front-Ends. IEEE Transactions on Biomedical Circuits and Systems, PP, 12 pages. External link
Xia, F., Li, H., Li, Y., Liu, X., Xu, Y., Fang, C., Hou, Q., Lin, S., Zhang, Z., Yang, J., & Sawan, M. (2023). Minimally Invasive Hypoglossal Nerve Stimulator Enabled by ECG Sensor and WPT to Manage Obstructive Sleep Apnea. Sensors, 23(21), 8882-8882. External link
Yang, J., Zhao, S., Lin, S., Hou, Q., Wang, J., & Sawan, M. (2024). Precise and low-power closed-loop neuromodulation through algorithm-integrated circuit co-design. Frontiers in Neuroscience, 18, 13 pages. Available
