A Light-Tolerant Wireless Neural Recording IC for Motor Prediction With Near-Infrared-Based Power and Data Telemetry

Lim, Jongyup; Lee, Jungho; Moon, Eunseong; Barrow, Michael; Atzeni, Gabriele; Letner, Joseph G; Costello, Joseph; Nason, Samuel R.; Patel, Paras R.; Sun, Yi; Patil, Parag G.; Kim, Hun-Seok; Chestek, Cynthia A.; Phillips, Jamie; Blaauw, David; Sylvester, Dennis; Jang, Taekwang

doi:10.1109/jssc.2022.3141688

Cited by 23 publications

(19 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition to the aforementioned processing power, the receiver also provides downlink power to the motes through IR light. To achieve the required 0.73 μW of operating power for each mote [23], given a 190 × 204 µm and 25% efficient photovoltaic cell, and a conservative tissue transmittance of 22%, the receiver needs to produce an illumination intensity of 342 μW/mm2. Given an LED efficiency of 75%, the receiver would use an estimated 456 μW/mm2, or 274 mW for a 2×3 cm craniotomy.…”

Section: Resultsmentioning

confidence: 99%

“…Our group has proposed an alternative communication scheme for IR-based communications, pulse-interval modulation (PIM), in which neural data is encoded by the transmission rate of data packets. PIM is asynchronous (Figure 1b), meaning motes would not have specific transmission times, and could then function with clock speeds on the order of 10 kHz regardless of the number of devices [23]. Since PIM encodes neural data in the analog domain, power-hungry analog-to-digital converters are not required.…”

Section: Introductionmentioning

confidence: 99%

“…(a) Proposed Michigan Mote system (figure adapted from [23]). Motes sit beneath the dura and are powered by near-infrared (NIR) light.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A low-power communication scheme for wireless, 1000 channel brain-machine interfaces

Costello

Nason²,

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

ObjectiveBrain-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.ApproachTo 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 ResultsWe found that PIM at 1kb/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 3mW for 1000 channels.SignificanceThese results suggest that PIM-based communication could significantly reduce power usage of wireless motes to enable higher channel-counts for high-performance BMIs.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A low-power communication scheme for wireless, 1000 channel brain-machine interfaces

Costello

Nason²,

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…The brain-machine interface used the 300-1,000Hz spiking band power, a low-power neural feature that is specific to single-unit activity despite a ten-fold reduction in processing requirements. We have already demonstrated SBP's efficacy on embedded and integrated systems [45][46][47][48][49] , and others have used it in similar brain-machine interface and BCFES applications 28,50,51 . While much work remains in system integration and safety validation, BCFES has a strong potential for full-time use in people with paralysis.…”

Section: Discussionmentioning

confidence: 99%

Brain-Controlled Electrical Stimulation Restores Continuous Finger Function

Nason

Mender

Kennedy

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

Brain-machine interfaces have shown promise in extracting upper extremity movement intention from the thoughts of nonhuman primates and people with tetraplegia. Attempts to restore a user's own hand and arm function have employed functional electrical stimulation (FES), but most work has restored discrete grasps. Little is known about how well FES can control continuous finger movements. Here, we use a low-power brain-controlled functional electrical stimulation (BCFES) system to restore continuous volitional control of finger positions to a monkey with a temporarily paralyzed hand. In a one-dimensional, continuous, finger-related target acquisition task, the monkey improved his success rate to 83% (1.5s median acquisition time) when using the BCFES system during temporary paralysis from 8.8% (9.5s median acquisition, equivalent to chance) when attempting to use his temporarily paralyzed hand. With two monkeys under general anesthesia, we found FES alone could control the monkeys' fingers to rapidly reach targets in a median 1.1s but caused oscillation about the target. Finally, when attempting to perform a virtual two-finger continuous target acquisition task in brain-control mode following temporary hand paralysis, we found performance could be completely recovered by executing recalibrated feedback-intention training one time following temporary paralysis. These results suggest that BCFES can restore continuous finger function during temporary paralysis using existing low-power technologies and brain-control may not be the limiting performance factor in a BCFES neuroprosthesis.

show abstract

“…Unlike threshold-crossings, SBP does not require setting a channel-specific threshold, or any other commands to be processed by the device, reducing circuitry and communication needed for thresholds. We previously published the integrated-chip design of PIM-motes [23], [24], but we did not investigate performance using significantly lower data-rates in a closed-loop BMI or the feasibility of receiver complexity.…”

Section: Introductionmentioning

confidence: 99%

A low-power communication scheme for wireless, 1000 channel brain–machine interfaces

Costello

Nason

et al. 2022

J. Neural Eng.

Self Cite

View full text Add to dashboard Cite

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 1kb/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 3mW 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.

show abstract

A Light-Tolerant Wireless Neural Recording IC for Motor Prediction With Near-Infrared-Based Power and Data Telemetry

Cited by 23 publications

References 28 publications

A low-power communication scheme for wireless, 1000 channel brain-machine interfaces

A low-power communication scheme for wireless, 1000 channel brain-machine interfaces

Brain-Controlled Electrical Stimulation Restores Continuous Finger Function

A low-power communication scheme for wireless, 1000 channel brain–machine interfaces

Contact Info

Product

Resources

About