چکیده

Spike detection is a necessary first step in the qualitative analysis of neural recordings. The extracellular spikes recording has been largely used in different fields limiting from essential neuroscientific research to clinical benefits. Moreover, the structure of the extracellular recording system, how to exactly detect spikes from the recorded data in real-time is yet a main challenging issue. Also, the existing methods for online spike detection have made big evolution, there remain many regions for betterment in terms of resolution. In this work, we propose a novel algorithm that while simple to implement, has high precision and real-time spike detection. The differential operator is at first employed to emphasize spikes in the signal for its simplicity and powerful capacity to detect important changes. Hence, by exploiting the constructional features of spikes, the resolution parameter is described to amend the efficiency of the differential operator. Then, effective and simple computing is used to further decrease the influence of background noise, where makes spike detection more accurate. The outcomes of simulated and real signals illustrate that the presented algorithm can precisely find spikes while sustaining low computational complexity. finally, A prototype 4-channel (tetrode) spike detector was designed and tested in a Xilinx Spartan-6 XC6SLX9 field-programmable gate array (FPGA).

کليدواژه ها

Spike detection, K-Differential operator, Spike Sorting

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پیام پاکروان , 1400 , یک الگوریتم جدید برای تشخیص بی درنگ اسپایکهای نورونی در FPGA , بیستمین کنفرانس ملی دانشجویی مهندسی برق ایران