The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
A Minimally Invasive 64-Channel Wireless μECoG Implant
Open accessAbstract
Emerging applications in brain–machine interface systems require high-resolution, chronic multisite cortical recordings, which cannot be obtained with existing technologies due to high power consumption, high invasiveness, or inability to transmit data wirelessly. In this paper, we describe a microsystem based on electrocorticography (ECoG) that overcomes these difficulties, enabling chronic recording and wireless transmission of neural signals from the surface of the cerebral cortex. The device is comprised of a highly flexible, high-density, polymer-based 64-channel electrode array and a flexible antenna, bonded to 2.4 mm × 2.4 mm CMOS integrated circuit (IC) that performs 64-channel acquisition, wireless power and data transmission. The IC digitizes the signal from each electrode at 1 kS/s with 1.2 μV input referred noise, and transmits the serialized data using a 1 Mb/s backscattering modulator. A dual-mode power-receiving rectifier reduces data-dependent supply ripple, enabling the integration of small decoupling capacitors on chip and eliminating the need for external components. Design techniques in the wireless and baseband circuits result in over 16× reduction in die area with a simultaneous 3× improvement in power efficiency over the state of the art. The IC consumes 225 μW and can be powered by an external reader transmitting 12 mW at 300 MHz, which is over 3× lower than IEEE and FCC regulations.
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Cites
Attentional stimulus selection through selective synchronization between monkey visual areas
Bosman, C. A., Schoffelen, J.-M., Brunet, N., Oostenveld, R., Bastos, A. M., Womelsdorf, T., Rubehn, B., Stieglitz, T., De Weerd, P., & Fries, P. (2012) · Neuron · doi:10.1016/j.neuron.2012.06.037 · Cited by 720
Muller, R., Gambini, S., & Rabaey, J. M. (2012) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2011.2163552 · Cited by 338
Self-citation
Cited by
Neural recording and modulation technologies
Chen, R., Canales, A., & Anikeeva, P. (2017) · Nature Reviews Materials · doi:10.1038/natrevmats.2016.93 · Cited by 655
Wireless Recording in the Peripheral Nervous System with Ultrasonic Neural Dust
Seo, D., Neely, R. M., Shen, K., Singhal, U., Alon, E., Rabaey, J. M., Carmena, J. M., & Maharbiz, M. M. (2016) · Neuron · doi:10.1016/j.neuron.2016.06.034 · Cited by 557
Self-citationInter-Technology Backscatter: Towards Internet Connectivity for Implanted Devices
Iyer, V., Talla, V., Kellogg, B., Gollakota, S., & Smith, J. (2016) · Proceedings of the 2016 ACM SIGCOMM Conference · doi:10.1145/2934872.2934894 · Cited by 367
Zhang, M., Tang, Z., Liu, X., & Van der Spiegel, J. (2020) · Nature Electronics · doi:10.1038/s41928-020-0390-3 · Cited by 231
A mm-Sized Wireless Implantable Device for Electrical Stimulation of Peripheral Nerves
Charthad, J., Chang, T. C., Liu, Z., Sawaby, A., Weber, M. J., Baker, S., Gore, F., Felt, S. A., & Arbabian, A. (2018) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2018.2799623 · Cited by 230
Metadata
- Authors
- Muller, R., Le, H.-P., Li, W., Ledochowitsch, P., Gambini, S., Bjorninen, T., Koralek, A., Carmena, J. M., Maharbiz, M. M., Alon, E., & Rabaey, J. M.
- Venue
- IEEE Journal of Solid-State Circuits
- Published
- 2015-01
- Volume
- 50
- Issue
- 1
- Pages
- 344-359
- ISSN
- 0018-9200 (ISSN-L)
- 1558-173X
- OpenAlex
- W1967356008
- Cited by
- 372
- References
- 2
- FWCI
- 14.24
- Type
- journal article
- Language
- en
- Open access
- green
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- Muller, R., Le, H.-P., Li, W., Ledochowitsch, P., Gambini, S., Bjorninen, T., Koralek, A., Carmena, J. M., Maharbiz, M. M., Alon, E., & Rabaey, J. M. (2015). A Minimally Invasive 64-Channel Wireless μECoG Implant. IEEE Journal of Solid-State Circuits. https://doi.org/10.1109/jssc.2014.2364824
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