An Energy-Efficient Biomedical Signal Processing Platform
This paper presents an energy-efficient processing platform for wearable sensor nodes, designed to support diverse biological signals and algorithms. The platform features a 0.5V-1.0V 16b microcontroller, SRAM, and accelerators for biomedical signal processing. Voltage scaling and block-level power...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
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Institute of Electrical and Electronics Engineers (IEEE)
2012
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| Online Access: | http://hdl.handle.net/1721.1/72195 https://orcid.org/0000-0002-5977-2748 |
| _version_ | 1811094253328138240 |
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| author | Kwong, Joyce Chandrakasan, Anantha P. |
| author2 | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
| author_facet | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Kwong, Joyce Chandrakasan, Anantha P. |
| author_sort | Kwong, Joyce |
| collection | MIT |
| description | This paper presents an energy-efficient processing platform for wearable sensor nodes, designed to support diverse biological signals and algorithms. The platform features a 0.5V-1.0V 16b microcontroller, SRAM, and accelerators for biomedical signal processing. Voltage scaling and block-level power gating allow optimizing energy efficiency under applications of varying complexity. Programmable accelerators support numerous usage scenarios and perform signal processing tasks at 133 to 215× lower energy than the general-purpose CPU. When running complete EEG and EKG applications using both CPU and accelerators, the platform achieves 10.2× and 11.5× energy reduction respectively compared to CPU-only implementations. |
| first_indexed | 2024-09-23T15:57:09Z |
| format | Article |
| id | mit-1721.1/72195 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T15:57:09Z |
| publishDate | 2012 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | mit-1721.1/721952022-10-02T05:18:18Z An Energy-Efficient Biomedical Signal Processing Platform Kwong, Joyce Chandrakasan, Anantha P. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Chandrakasan, Anantha P. Kwong, Joyce Chandrakasan, Anantha P. This paper presents an energy-efficient processing platform for wearable sensor nodes, designed to support diverse biological signals and algorithms. The platform features a 0.5V-1.0V 16b microcontroller, SRAM, and accelerators for biomedical signal processing. Voltage scaling and block-level power gating allow optimizing energy efficiency under applications of varying complexity. Programmable accelerators support numerous usage scenarios and perform signal processing tasks at 133 to 215× lower energy than the general-purpose CPU. When running complete EEG and EKG applications using both CPU and accelerators, the platform achieves 10.2× and 11.5× energy reduction respectively compared to CPU-only implementations. Natural Sciences and Engineering Research Council of Canada (NSERC). Fellowship 2012-08-17T18:46:55Z 2012-08-17T18:46:55Z 2010-09 2010-09 Article http://purl.org/eprint/type/ConferencePaper 978-1-4244-6662-7 1930-8833 http://hdl.handle.net/1721.1/72195 Kwong, Joyce, and Anantha P. Chandrakasan. “An Energy-efficient Biomedical Signal Processing Platform.” 2010 Proceedings of the ESSCIRC, 2010. 526–529. https://orcid.org/0000-0002-5977-2748 en_US http://dx.doi.org/10.1109/ESSCIRC.2010.5619759 2010 Proceedings of the ESSCIRC Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf Institute of Electrical and Electronics Engineers (IEEE) IEEE |
| spellingShingle | Kwong, Joyce Chandrakasan, Anantha P. An Energy-Efficient Biomedical Signal Processing Platform |
| title | An Energy-Efficient Biomedical Signal Processing Platform |
| title_full | An Energy-Efficient Biomedical Signal Processing Platform |
| title_fullStr | An Energy-Efficient Biomedical Signal Processing Platform |
| title_full_unstemmed | An Energy-Efficient Biomedical Signal Processing Platform |
| title_short | An Energy-Efficient Biomedical Signal Processing Platform |
| title_sort | energy efficient biomedical signal processing platform |
| url | http://hdl.handle.net/1721.1/72195 https://orcid.org/0000-0002-5977-2748 |
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