{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:01:30Z","timestamp":1760241690685,"version":"build-2065373602"},"reference-count":16,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2018,7,30]],"date-time":"2018-07-30T00:00:00Z","timestamp":1532908800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper presents an ultralow power 0.6 V 116 nW neural spike acquisition integrated circuit with analog spike extraction. To reduce power consumption, an ultralow power self-biased current-balanced instrumentation amplifier (IA) is proposed. The passive RC lowpass filter in the amplifier acts as both DC servo loop and self-bias circuit. The spike detector, based on an analog nonlinear energy operator consisting of a low-voltage open-loop differentiator and an open-loop gate-bulk input multiplier, is designed to emphasize the high frequency spike components nonlinearly. To reduce the spike detection error, the adjacent spike merger is also proposed. The proposed circuit achieves a low IA current consumption of 46.4 nA at 0.6 V, noise efficiency factor (NEF) of 1.81, the bandwidth from 102 Hz to 1.94 kHz, the input referred noise of 9.37 \u03bcVrms, and overall power consumption of 116 nW at 0.6 V. The proposed circuit can be used in the ultralow power spike pulses acquisition applications, including the neurofeedback systems on peripheral nerves with low neuron density.<\/jats:p>","DOI":"10.3390\/s18082460","type":"journal-article","created":{"date-parts":[[2018,7,30]],"date-time":"2018-07-30T11:55:08Z","timestamp":1532951708000},"page":"2460","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["0.6 V, 116 nW Neural Spike Acquisition IC with Self-Biased Instrumentation Amplifier and Analog Spike Extraction"],"prefix":"10.3390","volume":"18","author":[{"given":"Jong Pal","family":"Kim","sequence":"first","affiliation":[{"name":"Multimedia Processing Lab., Samsung Advanced Institute of Technology (SAIT), Suwon 16678, Korea"}]},{"given":"Hankyu","family":"Lee","sequence":"additional","affiliation":[{"name":"Multimedia Processing Lab., Samsung Advanced Institute of Technology (SAIT), Suwon 16678, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5348-3585","authenticated-orcid":false,"given":"Hyoungho","family":"Ko","sequence":"additional","affiliation":[{"name":"Department of Electronics Engineering, Chungnam National University, Daejeon 34134, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2018,7,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Kim, S., Liu, L., Yao, L., Goh, W., Gao, Y., and Je, M. (2014, January 10\u201312). A 0.5-V sub-\u03bcW\/channel neural recording IC with delta-modulation-based spike detection. Proceedings of the 2014 IEEE Asian Solid-State Circuits Conference (A-SSCC), KaoHsiung, Taiwan.","DOI":"10.1109\/ASSCC.2014.7008892"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"735","DOI":"10.1109\/TBCAS.2014.2298860","article-title":"A 0.45 V 100-Channel Neural-Recording IC with Sub-\u03bcW Channel Consumption in 0.18 \u03bcm CMOS","volume":"7","author":"Han","year":"2013","journal-title":"IEEE Trans. Biomed. Circuits Syst."},{"key":"ref_3","unstructured":"Liu, L., Yao, L., Zou, X., Goh, W., and Je, M. (2013, January 3\u20137). Neural recording front-end IC using action potential detection and analog buffer with digital delay for data compression. Proceedings of the 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Osaka, Japan."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1109\/TNSRE.2009.2018103","article-title":"An ultra low-power CMOS automatic action potential detector","volume":"17","author":"Gosselin","year":"2009","journal-title":"IEEE Trans. Neural. Syst. Rehabil. Eng."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1109\/JSSC.2006.886567","article-title":"A low-power integrated circuit for a wireless 100-electrode neural recording system","volume":"42","author":"Harrison","year":"2007","journal-title":"IEEE J. Solid-State Circuits"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1109\/JSSC.2014.2359962","article-title":"A 345 \u00b5W multi-sensor biomedical SoC with bio-impedance, 3-channel ECG, motion artifact reduction, and integrated DSP","volume":"50","author":"Konijnenburg","year":"2015","journal-title":"IEEE J. Solid-State Circuits"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1109\/TBCAS.2013.2278659","article-title":"A fully reconfigurable low-noise biopotential sensing amplifier with 1.96 noise efficiency factor","volume":"8","author":"Wang","year":"2014","journal-title":"IEEE Trans. Biomed. Circuits Syst."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"946","DOI":"10.1109\/TNSRE.2015.2425736","article-title":"Adaptive threshold neural spike detector using stationary wavelet transform in CMOS","volume":"23","author":"Yang","year":"2015","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1109\/10.661266","article-title":"A new interpretation of nonlinear energy operator and its efficacy in spike detection","volume":"45","author":"Mukhopadhyay","year":"1998","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"474","DOI":"10.1109\/TBME.2011.2174992","article-title":"Setting adaptive spike detection threshold for smoothed TEO based on robust statistics theory","volume":"59","author":"Semmaoui","year":"2012","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Cao, W., and Li, H. (2013, January 20\u201323). Ultra-low-power neural recording microsystem for implantable brain machine interface. Proceedings of the IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, Beijing, China.","DOI":"10.1109\/GreenCom-iThings-CPSCom.2013.178"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1109\/TBCAS.2009.2013718","article-title":"A Mixed-Signal Multichip Neural Recording Interface with Bandwidth Reduction","volume":"3","author":"Gosselin","year":"2009","journal-title":"IEEE Trans. Biomed. Circuits Syst."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1109\/TBCAS.2012.2187352","article-title":"A Low-Power Programmable Neural Spike Detection Channel with Embedded Calibration and Data Compression","volume":"6","year":"2012","journal-title":"IEEE Trans. Biomed. Circuits Syst."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"479","DOI":"10.1049\/el.2012.0685","article-title":"800 nW 43 nV\/\u221aHz neural recording amplifier with enhanced noise efficiency factor","volume":"48","author":"Liu","year":"2012","journal-title":"Electron. Lett."},{"key":"ref_15","first-page":"351","article-title":"A 2-\u00b5W 45-nV\/\u221aHz readout front end with multiple-chopping active-high-pass ripple reduction loop and pseudofeedback DC servo loop","volume":"63","author":"Wu","year":"2016","journal-title":"IEEE Trans. Circuits Syst. II Exp. Briefs"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"729","DOI":"10.1109\/TBCAS.2016.2622738","article-title":"Design of a closed-loop, bidirectional brain machine interface system with energy efficient neural feature extraction and PID control","volume":"11","author":"Liu","year":"2017","journal-title":"IEEE Trans. Biomed. Circuits Syst."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/8\/2460\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:15:08Z","timestamp":1760195708000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/8\/2460"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,7,30]]},"references-count":16,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2018,8]]}},"alternative-id":["s18082460"],"URL":"https:\/\/doi.org\/10.3390\/s18082460","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2018,7,30]]}}}