[HTML][HTML] Neural interface systems with on-device computing: machine learning and neuromorphic architectures
Highlights•Neural interfaces continue to improve in channel count and form factor.•Low-
power machine learning and neuromorphic processors can be integrated onto neural …
power machine learning and neuromorphic processors can be integrated onto neural …
Closed-loop neural prostheses with on-chip intelligence: A review and a low-latency machine learning model for brain state detection
The application of closed-loop approaches in systems neuroscience and therapeutic
stimulation holds great promise for revolutionizing our understanding of the brain and for …
stimulation holds great promise for revolutionizing our understanding of the brain and for …
NeuralTree: A 256-channel 0.227-μJ/class versatile neural activity classification and closed-loop neuromodulation SoC
Closed-loop neural interfaces with on-chip machine learning can detect and suppress
disease symptoms in neurological disorders or restore lost functions in paralyzed patients …
disease symptoms in neurological disorders or restore lost functions in paralyzed patients …
A patient-specific closed-loop epilepsy management SoC with one-shot learning and online tuning
Epilepsy treatment in clinical practices with surface electroencephalogram (EEG) often faces
training dataset shortage issue, which is aggravated by seizure pattern variation among …
training dataset shortage issue, which is aggravated by seizure pattern variation among …
RISC-V CNN coprocessor for real-time epilepsy detection in wearable application
SY Lee, YW Hung, YT Chang, CC Lin… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
Epilepsy is a common clinical disease. Severe epilepsy can be life-threatening in certain
unexpected conditions, so it is important to detect seizures instantly with a wearable device …
unexpected conditions, so it is important to detect seizures instantly with a wearable device …
A 256-Channel 0.227µJ/class Versatile Brain Activity Classification and Closed-Loop Neuromodulation SoC with 0.004mm2-1.51 µW/channel Fast-Settling Highly …
Closed-loop neuromodulation can alleviate disease symptoms and provide sensory
feedback in various neurological disorders and injuries [1]. Energy-efficient realization of …
feedback in various neurological disorders and injuries [1]. Energy-efficient realization of …
SciCNN: A 0-shot-retraining patient-independent epilepsy-tracking SoC
Patient-specific seizure-detection SoCs targeting ambulatory seizure treatment [1–8]
achieve outstanding accuracy and low energy consumption for monitoring over an extended …
achieve outstanding accuracy and low energy consumption for monitoring over an extended …
A highly energy-efficient hyperdimensional computing processor for biosignal classification
Hyperdimensional computing (HDC) is a brain-inspired computing paradigm that operates
on pseudo-random hypervectors to perform high-accuracy classifications for biomedical …
on pseudo-random hypervectors to perform high-accuracy classifications for biomedical …
SOUL: An energy-efficient unsupervised online learning seizure detection classifier
Implantable devices that record neural activity and detect seizures have been adopted to
issue warnings or trigger neurostimulation to suppress epileptic seizures. Typical seizure …
issue warnings or trigger neurostimulation to suppress epileptic seizures. Typical seizure …
Closed-Loop Implantable Neurostimulators for Individualized Treatment of Intractable Epilepsy: A Review of Recent Developments, Ongoing Challenges, and Future …
Driven by its proven therapeutic efficacy in treating movement disorders and psychiatric
conditions, neurostimulation has emerged as a promising intervention for intractable …
conditions, neurostimulation has emerged as a promising intervention for intractable …