Nanowire FET Based Neural Element for Robotic Tactile Sensing Skin
Open accessAbstract
This paper presents novel Neural Nanowire Field Effect Transistors (υNWFETs) based hardware-implementable neural network (HNN) approach for tactile data processing in electronic skin (e-skin). The viability of Si nanowires (NWs) as the active material for υNWFETs in HNN is explored through modelling and demonstrated by fabricating the first device. Using υNWFETs to realize HNNs is an interesting approach as by printing NWs on large area flexible substrates it will be possible to develop a bendable tactile skin with distributed neural elements (for local data processing, as in biological skin) in the backplane. The modeling and simulation of υNWFET based devices show that the overlapping areas between individual gates and the floating gate determines the initial synaptic weights of the neural network - thus validating the working of υNWFETs as the building block for HNN. The simulation has been further extended to υNWFET based circuits and neuronal computation system and this has been validated by interfacing it with a transparent tactile skin prototype (comprising of 6x6 ITO based capacitive tactile sensors array) integrated on the palm of a 3D printed robotic hand. In this regard, a tactile data coding system is presented to detect touch gesture and the direction of touch. Following these simulation studies, a four-gated υNWFET is fabricated with Pt/Ti metal stack for gates, source and drain, Ni floating gate, and Al2O3 high-k dielectric layer. The currentvoltage characteristics of fabricated υNWFET devices confirm the dependence of turnoff voltages on the (synaptic) weight of each gate. The presented υNWFET approach is promising for a neuro-robotic tactile sensory system with distributed computing as well as numerous futuristic applications such as prosthetics, and electroceuticals.
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Estimates of tactile fiber innervation in the current literature are few, often incomplete and inconsistent, and range from around 45,000 fibers to millions.
“Estimates of tactile fiber innervation in the current literature are few, often incomplete and inconsistent, and range from a total innervation of around 45,000 fibers (Taube Navaraj et al. 2017) into the millions (Grunwald 2017).”
From Tactile innervation densities across the whole body (2020) · cites this paper as Taube Navaraj et al. 2017
The Introduction estimates that about 45,000 mechanoreceptors would be needed across 1.5 m² of human-inspired robotic e-skin. That supports the approximate number attributed to this source, but it is an estimate of sensors needed to mimic touch, not a count of tactile fiber innervation. The claim about estimates reaching millions is attributed to a different source. (LLM, conf=0.85)
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Spiking Neural Network Pressure Sensor
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Self-citation
- Authors
- Taube Navaraj, W., García Núñez, C., Shakthivel, D., Vinciguerra, V., Labeau, F., Gregory, D. H., & Dahiya, R.
- Affiliations
- University of Glasgow (GB)
- STMicroelectronics (Italy) (IT)
- McGill University (CA)
- Corresponding author
- Dahiya, Ravinder
- Venue
- Frontiers in Neuroscience
- Publisher
- Frontiers Media SA
- Published
- 2017-09-20
- Volume
- 11
- Pages
- 501-501
- ISSN
- 1662-453X (ISSN-L)
- PMC
- PMC5611376
- OpenAlex
- W2755222108
- Cited by
- 127
- References
- 70
- Citations by year
- 2026: 4 · 2025: 9 · 2024: 10 · 2023: 7 · 2022: 16 · 2021: 21 · 2020: 28 · 2019: 15 · 2018: 13 · 2017: 4
- FWCI
- 6.82
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Frontiers in Neuroscience (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Nottingham Trent University's Institutional Repository (Nottingham Trent Repository) (acceptedVersion)
- ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (acceptedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- eScholarship@McGill (McGill) (submittedVersion, cc-by)
- Funders
- Engineering and Physical Sciences Research Council (EP/M002527/1)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Memory and Neural Computing
- Physical Sciences › Engineering › Biomedical Engineering › Nanowire Synthesis and Applications
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advancements in Semiconductor Devices and Circuit Design
- Keywords
- nanowire field-effect transistors, silicon nanowires, electronic skin, tactile sensing, robotic hand, synaptic weights, floating gate, capacitive tactile sensor, neurorobotics, flexible electronics, high-k dielectrics
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