A wireless fully-passive acquisition of biopotentials

Shiyi Liu, Xueling Meng, Jianwei Zhang, Junseok Chae

Research output: Contribution to journalArticle

Abstract

Biopotential signals contain essential information for assessing functionality of organs and diagnosing diseases. We present a flexible sensor, capable of measuring biopotentials, in real time, in wireless and fully-passive manner. The flexible sensor collects and transmits biopotentials to an external reader without wire, battery, or harvesting/regulating element. The sensor is fabricated on a 90 μm-thick polyimide substrate with footprint of 18 × 15 × 0.5 mm3. The wireless fully-passive acquisition of biopotentials is enabled by the RF (Radio Frequency) microwave backscattering effect where the biopotentials are modulated by an array of varactors with incoming RF carrier that is backscattered to the external reader. The flexile sensor is verified and validated by emulated signal and Electrocardiogram (ECG), Electromyogram (EMG), and Electrooculogram (EOG), respectively. A deep learning algorithm analyzes the signal quality of wirelessly acquired data, along with the data from commercially-available wired sensor counterparts. Wired and wireless data shows <3% discrepancy in deep learning testing accuracy for ECG and EMG up to the wireless distance of 240 mm. Wireless acquisition of EOG further demonstrates accurate tracking of horizontal eye movement with deep learning training and testing accuracy reaching up to 93.6% and 92.2%, respectively, indicating successful detection of biopotentials signal as low as 250 μVPP. These findings support that the real-time wireless fully-passive acquisition of on-body biopotentials is indeed feasible and may find various uses for future clinical research.

Original languageEnglish (US)
Article number111336
JournalBiosensors and Bioelectronics
Volume139
DOIs
StatePublished - Aug 15 2019

Fingerprint

Electrooculography
Learning
Electromyography
Radio
Electrocardiography
Eye Movements
Sensors
Microwaves
Research
Varactors
Eye movements
Microwave frequencies
Testing
Backscattering
Polyimides
Learning algorithms
Wire
Substrates
Deep learning
Psychological Signal Detection

Keywords

  • Backscattering
  • Deep learning
  • ECG
  • EMG
  • EOG
  • Fully-passive

ASJC Scopus subject areas

  • Biotechnology
  • Biophysics
  • Biomedical Engineering
  • Electrochemistry

Cite this

A wireless fully-passive acquisition of biopotentials. / Liu, Shiyi; Meng, Xueling; Zhang, Jianwei; Chae, Junseok.

In: Biosensors and Bioelectronics, Vol. 139, 111336, 15.08.2019.

Research output: Contribution to journalArticle

Liu, Shiyi ; Meng, Xueling ; Zhang, Jianwei ; Chae, Junseok. / A wireless fully-passive acquisition of biopotentials. In: Biosensors and Bioelectronics. 2019 ; Vol. 139.
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