Adaptive Extreme Edge Computing for Wearable Devices.
edge computing
learning algorithms
memristive devices
neuromorphic computing
wearable devices
Journal
Frontiers in neuroscience
ISSN: 1662-4548
Titre abrégé: Front Neurosci
Pays: Switzerland
ID NLM: 101478481
Informations de publication
Date de publication:
2021
2021
Historique:
received:
28
09
2020
accepted:
24
03
2021
entrez:
28
5
2021
pubmed:
29
5
2021
medline:
29
5
2021
Statut:
epublish
Résumé
Wearable devices are a fast-growing technology with impact on personal healthcare for both society and economy. Due to the widespread of sensors in pervasive and distributed networks, power consumption, processing speed, and system adaptation are vital in future smart wearable devices. The visioning and forecasting of how to bring computation to the edge in smart sensors have already begun, with an aspiration to provide adaptive extreme edge computing. Here, we provide a holistic view of hardware and theoretical solutions toward smart wearable devices that can provide guidance to research in this pervasive computing era. We propose various solutions for biologically plausible models for continual learning in neuromorphic computing technologies for wearable sensors. To envision this concept, we provide a systematic outline in which prospective low power and low latency scenarios of wearable sensors in neuromorphic platforms are expected. We successively describe vital potential landscapes of neuromorphic processors exploiting complementary metal-oxide semiconductors (CMOS) and emerging memory technologies (e.g., memristive devices). Furthermore, we evaluate the requirements for edge computing within wearable devices in terms of footprint, power consumption, latency, and data size. We additionally investigate the challenges beyond neuromorphic computing hardware, algorithms and devices that could impede enhancement of adaptive edge computing in smart wearable devices.
Identifiants
pubmed: 34045939
doi: 10.3389/fnins.2021.611300
pmc: PMC8144334
doi:
Types de publication
Journal Article
Review
Langues
eng
Pagination
611300Informations de copyright
Copyright © 2021 Covi, Donati, Liang, Kappel, Heidari, Payvand and Wang.
Déclaration de conflit d'intérêts
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer JE declared a past co-authorship with one of the authors MP to the handling editor.
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