2024-03-29T00:14:52Zhttp://digital.csic.es/dspace-oai/requestoai:digital.csic.es:10261/1575702017-12-18T14:35:59Zcom_10261_90com_10261_4col_10261_343
2017-11-22T12:06:24Z
urn:hdl:10261/157570
System-Level Design of a 64-Channel Low Power Neural Spike Recording Sensor
Delgado-Restituto, Manuel
Rodríguez-Pérez, Alberto
Darie, Ángela
Soto-Sánchez, Cristina
Fernández-Jover, Eduardo
Rodríguez-Vázquez, Ángel
Spike detection
Neural recording
Feature extraction
Neural prosthesi
Brain-Machine Interfaces (BMI)
This paper reports an integrated 64-channel neural spike recording sensor, together with all the circuitry to process and configure the channels, process the neural data, transmit via a wireless link the information and receive the required instructions. Neural signals are acquired, filtered, digitized and compressed in the channels. Additionally, each channel implements an auto-calibration algorithm which individually configures the transfer characteristics of the recording site. The system has two transmission modes; in one case the information captured by the channels is sent as uncompressed raw data; in the other, feature vectors extracted from the detected neural spikes are released. Data streams coming from the channels are serialized by the embedded digital processor. Experimental results, including in vivo measurements, show that the power consumption of the complete system is lower than 330 μW.
2017-11-22T12:06:24Z
2017-11-22T12:06:24Z
2017
2017-11-22T12:06:24Z
artículo
IEEE Transactions on Biomedical Circuits and Systems 11: 420- 433 (2017)
http://hdl.handle.net/10261/157570
10.1109/TBCAS.2016.2618319
eng
Postprint
Sí
openAccess