Abstract
A hardware-efficient lowpass filter design technique based on an exponentially weighted moving average (EWMA) filter architecture is proposed for the detection of general action potentials and nerve spikes in noisy signals. The EWMA VLSI architecture is compared with a basic moving average (MA) architecture and it is found that the EWMA technique is the most economical in terms of space of the two. In addition, a rule of thumb is given for converting a MA filter to the proposed filter. In the comparison, it was found that an EWMA filter is almost 85% more hardware-efficient than an MA filter.
Original language | English |
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Title of host publication | 2010 IEEE Biomedical Circuits and Systems Conference, BioCAS 2010 |
Pages | 130-133 |
Number of pages | 4 |
DOIs | |
Publication status | Published - 1 Dec 2010 |
Externally published | Yes |
Event | 2010 IEEE Biomedical Circuits and Systems Conference, BioCAS 2010 - Paphos, Cyprus Duration: 3 Nov 2010 → 5 Nov 2010 |
Conference
Conference | 2010 IEEE Biomedical Circuits and Systems Conference, BioCAS 2010 |
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Country/Territory | Cyprus |
City | Paphos |
Period | 3/11/10 → 5/11/10 |
Keywords
- Exponentially weighted moving average filter
- Filtering
- Low-area moving average filter implementation
- Neural spike detection