Bridging the “Last Millimeter” Gap of Brain-Machine Interfaces via Near-Infrared Wireless Power Transfer and Data Communications
Source abstract
Abstract
Arrays of floating neural sensors with high channel count that cover an area of square centimeters and larger would be transformative for neural engineering and brain-machine interfaces. Meeting the power and wireless data communications requirements within the size constraints for each neural sensor has been elusive due to the need to incorporate sensing, computing, communications, and power functionality in a package of approximately 100 micrometers on a side. In this work, we demonstrate a near infrared optical power and data communication link for a neural recording system that satisfies size requirements to achieve dense arrays and power requirements to prevent tissue heating. The optical link is demonstrated using an integrated optoelectronic device consisting of a tandem photovoltaic cell and microscale light emitting diode. End-to-end functionality of a wireless neural link within system constraints is demonstrated using a pre-recorded neural signal between a self-powered CMOS integrated circuit and single photon avalanche photodiode.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Neuroscience and Neural Engineering · Photoreceptor and optogenetics research · Molecular Communication and Nanonetworks
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan 48109, United States
Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan 48109, United States
Department of Information Technology and Electrical Engineering, ETH Zürich, 8092 Zürich, Switzerland
Department of Electrical and Computer Engineering, University of Delaware, Newark, Delaware 19716, United States
Funding
National Eye Institute · National Institute of Child Health and Human Development
References (42)
Show source-provided references
1. 10.1016/j.jneumeth.2014.07.02510.1016/j.jneumeth.2014.07.025 ↗
2. 10.1016/j.neuron.2016.06.03410.1016/j.neuron.2016.06.034 ↗
3. 10.1038/s41551-020-0518-910.1038/s41551-020-0518-9 ↗
4. Lee, J.; Laiwalla, F.; Jeong, J.; Kilfoyle, C.; Larson, L.; Nurmikko, A.; Li, S.; Yu, S.; Leung, V. W. Wireless power and data link for ensembles of sub-mm scale implantable sensors near 1 GHz. 2018 IEEE Biomedical Circuits and Systems Conference (BioCAS); IEEE, 2018; pp 1–4.10.1109/BIOCAS.2018.8584725 ↗
5. Lee J. · bioRxiv · 2020 · na
6. 10.1007/BF0236813410.1007/BF02368134 ↗
7. 10.1016/0006-8993(96)00321-610.1016/0006-8993(96)00321-6 ↗
8. 10.1109/ACCESS.2020.300751710.1109/ACCESS.2020.3007517 ↗
9. Rabaey, J. M.; Mark, M.; Chen, D.; Sutardja, C.; Tang, C.; Gowda, S.; Wagner, M.; Werthimer, D. Powering and communicating with mm-size implants. 2011 Design, Automation and Test in Europe Conference and Exhibition; Grenoble, France, IEEE, 2011; pp 1–6.10.1109/DATE.2011.5763123 ↗
10. 10.1109/JPROC.2013.225185110.1109/JPROC.2013.2251851 ↗
11. 10.1109/TAP.2010.204431010.1109/TAP.2010.2044310 ↗
12. 10.1038/srep0353510.1038/srep03535 ↗
13. 10.1109/JSSC.2015.242733610.1109/JSSC.2015.2427336 ↗
14. 10.1227/00006123-198710000-0000310.1227/00006123-198710000-00003 ↗
15. 10.1134/1.189053010.1134/1.1890530 ↗
16. Lee, S.; Cortese, A. J.; Trexel, P.; Agger, E. R.; McEuen, P. L.; Molnar, A. C. A 330 m × 90 m opto-electronically integrated wireless system-on-chip for recording of neural activities. IEEE International Solid-State Circuits Conference (ISSCC), San Francisco, CA, IEEE, 2018; pp 292–294.10.1109/ISSCC.2018.8310299 ↗
17. 10.1109/TBCAS.2018.287606910.1109/TBCAS.2018.2876069 ↗
18. 10.1073/pnas.191967711710.1073/pnas.1919677117 ↗
19. Lim, J.; Moon, E.; Barrow, M.; Nason, S. R.; Patel, P. R.; Patil, P. G.; Oh, S.; Kim, H.S.; Sylvester, D.; Blaauw, D.; Chestek, C. A.; Phillips, J. D.; Jang, T. A 0.19 × 0.17 mm2 wireless neural recording IC for motor prediction with near-infrared-based power and data telemetry. 2020 IEEE International Solid-State Circuits Conference, San Francisco, CA, IEEE, 2020; pp 416–418.10.1109/ISSCC19947.2020.9063005 ↗
20. Lee, I.; Kim, G.; Moon, E.; Jeong, S.; Kim, D.; Phillips, J.; Blaauw, D. A 179-Lux energy-autonomous fully-encapsulated 17-mm 3 sensor node with initial charge delay circuit for battery protection. 2018 IEEE Symposium on VLSI Circuits, IEEE, 2018; pp 251–252.10.1109/VLSIC.2018.8502287 ↗
21. Yang, K.; Dong, Q.; Jung, W.; Zhang, Y.; Choi, M.; Blaauw, D.; Sylvester, D. 9.2 A 0.6 nJ 0.22/+0.19 C inaccuracy temperature sensor using exponential subthreshold oscillation dependence. 2017 IEEE International Solid-State Circuits Conference (ISSCC), San Francisco, CA, IEEE, 2017; pp 160–161.10.1109/ISSCC.2017.7870310 ↗
22. 10.1088/1741-2552/aa80bd10.1088/1741-2552/aa80bd ↗
23. Wolf P. D. · 2008
24. ANSI14 (LIo, America. American National Standard for Safe Use of Lasers (ANSI Z136.1); Laser Institute of America, Orlando, Florida, 2014.
25. 10.1152/jn.00275.201610.1152/jn.00275.2016 ↗
26. 10.1016/j.pquantelec.2017.06.00310.1016/j.pquantelec.2017.06.003 ↗
27. 10.1109/JSTQE.2014.234156210.1109/JSTQE.2014.2341562 ↗
28. AUREA Technologies Compact NIR Single Photon Detector Dual-Mode Photon Counting Solution - OEM Design (900–1700 nm); AUREA Technologies, 2020.
29. 10.1109/JPHOTOV.2020.302545010.1109/JPHOTOV.2020.3025450 ↗
30. 10.1063/1.312551410.1063/1.3125514 ↗
31. 10.1063/1.505170910.1063/1.5051709 ↗
32. 10.1002/pip.313210.1002/pip.3132 ↗
33. 10.1088/0268-1242/17/3/31110.1088/0268-1242/17/3/311 ↗
34. 10.1109/TED.2007.90067810.1109/TED.2007.900678 ↗
35. 10.1109/TED.2017.274609410.1109/TED.2017.2746094 ↗
36. 10.1523/JNEUROSCI.1321-07.200710.1523/JNEUROSCI.1321-07.2007 ↗
37. Irwin, Z. T.; Thompson, D. E.; Schroeder, K. E.; Tat, D. M.; Hassani, A.; Bullard, A. J.; Woo, S. L.; Urbanchek, M. G.; Sachs, A. J.; Cederna, P. S.; Stacey, W. C.; Patil, P. G.; Chestek, C. A. Enabling low-power, multi-modal neural interfaces through a common, low-bandwidth feature space. IEEE Transactions on Neural Systems and Rehabilitation Engineering; IEEE, 2015.10.1109/TNSRE.2015.2501752 ↗
38. 10.1038/s41551-020-0591-010.1038/s41551-020-0591-0 ↗
39. Yang, K.; Dong, Q.; Blaauw, D.; Sylvester, D. 8.3 A 553F22-transistor amplifier-based Physically Unclonable Function (PUF) with 1.67% native instability. 2017 IEEE International Solid-State Circuits Conference (ISSCC), San Francisco, CA, IEEE, 2017; pp 146–147.10.1109/ISSCC.2017.7870303 ↗
40. Elsherbini, A. A.; Liff, S. M.; Swan, J. M. Heterogeneous integration using omni-directional interconnect packaging. 2019 IEEE International Electron Devices Meeting (IEDM), San Francisco, CA, IEEE, 2019.10.1109/IEDM19573.2019.8993659 ↗
41. Ingerly, D. B. Foveros: 3D integration and the use of face-to-face chip stacking for logic devices. 2019 IEEE International Electron Devices Meeting (IEDM), San Francisco, CA, IEEE, 2019.10.1109/IEDM19573.2019.8993637 ↗
42. 10.1126/scitranslmed.abb808610.1126/scitranslmed.abb8086 ↗