journal article·2022-01-25Open access

Skin-Inspired Flexible and Stretchable Electrospun Carbon Nanofiber Sensors for Neuromorphic Sensing

Debarun Sengupta, Michele Mastella, Elisabetta Chicca, Ajay Giri Prakash Kottapalli

Abstract

During the past few decades, a significant amount of research effort has been dedicated toward developing skin-inspired sensors for real-time human motion monitoring and next-generation robotic devices. Although several flexible and wearable sensors have been developed in the past, the need of the hour is developing accurate, reliable, sophisticated, facile yet inexpensive flexible sensors coupled with neuromorphic systems or spiking neural networks to encode tactile information without the need for complex digital architectures, thus achieving true skin-like sensing with limited resources. In this work, we propose an approach entailing carbon nanofiber-polydimethylsiloxane composite-based piezoresistive sensors, coupled with spiking neural networks, to mimic skin-like sensing. The strain and pressure sensors have been combined with appropriately designed neural networks to encode analog voltages to spikes to recreate bioinspired tactile sensing and proprioception. To further validate the proprioceptive capability of the system, a gesture tracking smart glove, combined with a spiking neural network, was demonstrated. Wearable and flexible sensors with accompanying neural networks such as the ones proposed in this work will pave the way for a future generation of skin-mimetic sensors for advanced prosthetic devices, apparel integrable smart sensors for human motion monitoring, and human-machine interfaces.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Advanced Memory and Neural Computing · Tactile and Sensory Interactions

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Advanced Production Engineering (APE), Engineering and Technology Institute Groningen (ENTEG), University of Groningen, Groningen 9747 AG, The Netherlands

Groningen Cognitive Systems and Materials Center (CogniGron), University of Groningen, Groningen 9747 AG, The Netherlands

Bio-Inspired Circuits and Systems (BICS) Laboratory, Zernike Institute for Advanced Materials (Zernike Inst Adv Mat), University of Groningen, Nijenborgh 4, Groningen NL-9747 AG, Netherlands

MIT Sea Grant College Program, Massachusetts Institute of Technology (MIT), 77 Massachusetts Avenue, NW98-151, Cambridge, Massachusetts 02139, United States

Funding

Rijksuniversiteit Groningen · Horizon 2020 Framework Programme

References (33)

Show source-provided references
1. 10.1088/0957-4484/26/37/37550110.1088/0957-4484/26/37/375501 ↗
2. 10.1021/acsnano.5b0278110.1021/acsnano.5b02781 ↗
3. 10.1021/acsami.6b0817210.1021/acsami.6b08172 ↗
4. 10.1021/nn503454h10.1021/nn503454h ↗
5. 10.1021/acsami.0c0581910.1021/acsami.0c05819 ↗
6. 10.1002/adfm.20190373210.1002/adfm.201903732 ↗
7. 10.1038/s41528-020-0072-210.1038/s41528-020-0072-2 ↗
8. 10.3390/nano1002021110.3390/nano10020211 ↗
9. 10.1111/j.2044-835x.1987.tb01056.x10.1111/j.2044-835x.1987.tb01056.x ↗
10. 10.1016/j.neuron.2013.07.05110.1016/j.neuron.2013.07.051 ↗
11. 10.1016/j.sna.2017.09.03510.1016/j.sna.2017.09.035 ↗
12. 10.1186/1743-0003-9-4510.1186/1743-0003-9-45 ↗
13. 10.1088/1741-2560/10/4/04601910.1088/1741-2560/10/4/046019 ↗
14. Lee, W. W.; Cabibihan, J.; Thakor, N. V. Bio-Mimetic Strategies for Tactile Sensing. SENSORS, 2013 IEEE, 2013.10.1109/ICSENS.2013.6688260 ↗
15. 10.1016/j.proeng.2012.09.09710.1016/j.proeng.2012.09.097 ↗
16. 10.1016/j.neuron.2009.01.00810.1016/j.neuron.2009.01.008 ↗
17. Lee, W. W.; Yu, H.; Thakor, N. V. Gait Event Detection through Neuromorphic Spike Sequence Learning. Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics, 2014.10.1109/BIOROB.2014.6913895 ↗
18. 10.3389/fnbot.2015.0000610.3389/fnbot.2015.00006 ↗
19. 10.1038/s41598-020-80132-410.1038/s41598-020-80132-4 ↗
20. Dabbous, A.; Mastella, M.; Natarajan, A.; Chicca, E.; Valle, M.; Barolozzi, C. Artificial Bio-Inspired Tactile Receptive Fields for Edge Orientation Classification. 2021 IEEE International Symposium on Circuits and Systems (ISCAS); IEEE, 2021; pp 1–5.
21. 10.1126/scirobotics.aat381810.1126/scirobotics.aat3818 ↗
22. 10.1063/1.170268210.1063/1.1702682 ↗
23. 10.1063/1.349962810.1063/1.3499628 ↗
24. Boujamaa, E. M.; Alandry, B.; Hacine, S.; Latorre, L.; Mailly, F.; Nouet, P. A Low Power Interface Circuit for Resistive Sensors with Digital Offset Compensation. ISCAS 2010: 2010 IEEE International Symposium on Circuits and Systems, Nano-Bio Circuit Fabrics and Systems, 2010; pp 3092–3095.10.1109/ISCAS.2010.5537970 ↗
25. 10.1016/j.sna.2008.10.01310.1016/j.sna.2008.10.013 ↗
26. 10.1016/s0361-9230(99)00161-610.1016/s0361-9230(99)00161-6 ↗
27. Cassidy, A.; Andreou, A. G. Dynamical Digital Silicon Neurons. 2008 IEEE-BIOCAS Biomedical Circuits and Systems Conference, BIOCAS 2008, 2008; pp 289–292.10.1109/BIOCAS.2008.4696931 ↗
28. 10.26599/tst.2019.901001910.26599/tst.2019.9010019 ↗
29. 10.1162/106454605327890010.1162/1064546053278900 ↗
30. 10.1109/jproc.2014.231395410.1109/jproc.2014.2313954 ↗
31. Rubino, A.; Payvand, M.; Indiveri, G. Ultra-Low Power Silicon Neuron Circuit for Extreme-Edge Neuromorphic Intelligence. 2019 26th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2019, 2019; pp 458–461.10.1109/ICECS46596.2019.8964713 ↗
32. 10.3389/fnins.2011.0007310.3389/fnins.2011.00073 ↗
33. 10.7554/eLife.4731410.7554/eLife.47314 ↗