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Abstract Objective . Brain–machine interfaces (BMIs) have the potential to restore motor function but are currently limited by electrode count and long-term recording stability. These challenges may be solved through the use of free-floating ‘motes’ which wirelessly transmit recorded neural signals, if power consumption can be kept within safe levels when scaling to thousands of motes. Here, we evaluated a pulse-interval modulation (PIM) communication scheme for infrared (IR)-based motes that aims to reduce the wireless data rate and system power consumption. Approach . To test PIM’s ability to efficiently communicate neural information, we simulated the communication scheme in a real-time closed-loop BMI with non-human primates. Additionally, we performed circuit simulations of an IR-based 1000-mote system to calculate communication accuracy and total power consumption. Main results . We found that PIM at 1 kb/s per channel maintained strong correlations with true firing rate and matched online BMI performance of a traditional wired system. Closed-loop BMI tests suggest that lags as small as 30 ms can have significant performance effects. Finally, unlike other IR communication schemes, PIM is feasible in terms of power, and neural data can accurately be recovered on a receiver using 3 mW for 1000 channels. Significance. These results suggest that PIM-based communication could significantly reduce power usage of wireless motes to enable higher channel-counts for high-performance BMIs.
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Adaptive Wireless Power Transfer and Backscatter Communication for Perpetual Operation of Wireless Brain–Computer Interfaces
Brain–computer interfaces (BCIs) are neural prosthetics that enable closed-loop electrophysiology procedures. These devices are currently used in fundamental neurophysiology research, and they are moving toward clinical viability for neural rehabilitation. State-of-the-art BCI experiments have often been performed using tethered (wired) setups in controlled laboratory settings. Wired tethers simplify power and data interfaces but restrict the duration and types of experiments that are possible, particularly for the study of sensorimotor pathways in freely behaving animals. To eliminate tethers, there is significant ongoing research to develop fully wireless BCIs having wireless uplink of broadband neural recordings and wireless recharging for long-duration deployment, but significant challenges persist. BCIs must deliver complex functionality while complying with tightly coupled constraints in size, weight, power, noise, and biocompatibility. In this article, we provide an overview of recent progress in wireless BCIs and a detailed presentation of two emerging technologies that are advancing the state of the art: ultralow-power wireless backscatter communication and adaptive inductive resonant (AIR) wireless power transfer (WPT).
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- Award ID(s):
- 1823148
- PAR ID:
- 10503540
- Publisher / Repository:
- IEEE
- Date Published:
- Journal Name:
- Proceedings of the IEEE
- Volume:
- 110
- Issue:
- 1
- ISSN:
- 0018-9219
- Page Range / eLocation ID:
- 89 to 106
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1109/JPROC.2021.3130059
