A Biomedical Sensor System With Stochastic A/D Conversion and Error Correction by Machine Learning
| Autor: | Shodai Isami, Toshimasa Matsuoka, Sadahiro Tani, Yusaku Hirai, Keiji Tatsumi, Masayuki Ueda, Takatsugu Kamata |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
error correction
stochastic A/D conversion General Computer Science Comparator Computer science 02 engineering and technology Hardware_PERFORMANCEANDRELIABILITY Flash ADC Machine learning computer.software_genre 01 natural sciences Noise (electronics) Sampling (signal processing) 0202 electrical engineering electronic engineering information engineering Hardware_INTEGRATEDCIRCUITS General Materials Science 0101 mathematics Hardware_ARITHMETICANDLOGICSTRUCTURES Hardware_REGISTER-TRANSFER-LEVELIMPLEMENTATION business.industry ECG 020208 electrical & electronic engineering 010102 general mathematics Bandwidth (signal processing) General Engineering machine learning Filter (video) SAR-ADC Biomedical sensor Artificial intelligence lcsh:Electrical engineering. Electronics. Nuclear engineering Error detection and correction business computer lcsh:TK1-9971 |
| Zdroj: | IEEE Access, Vol 7, Pp 21990-22001 (2019) |
| ISSN: | 2169-3536 |
| Popis: | This paper presents a high-precision biomedical sensor system with a novel analog-frontend (AFE) IC and error correction by machine learning. The AFE IC embeds an analog-to-digital converter (ADC) architecture called successive stochastic approximation ADC. The proposed ADC integrates a stochastic flash ADC (SF-ADC) into a successive approximation register ADC (SAR-ADC) to enhance its resolution. The SF-ADC is also used as a digitally controlled variable threshold comparator to provide error correction of the SAR-ADC. The proposed system also calibrates the ADC error using the machine learning algorithm on an external PC without additional power dissipation at a sensor node. Due to the flexibility of the system, the design complexity of an AFE IC can be relaxed by using these techniques. The target resolution is 18 bits, and the target bandwidth (without digital low-pass filter) is about 5 kHz to deal with several types of biopotential signals. The design is fabricated in a 130-nm CMOS process and operates at 1.2-V supply. The fabricated ADC achieves the SNDR of 88 dB at a sampling frequency of 250 kHz by using the proposed calibration techniques. Due to the high-resolution ADC, the input-referred noise is 2.52 μVrms with a gain of 28.5 dB. |
| Databáze: | OpenAIRE |
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