Recently, it became possible to detect single motor units (MUs) noninvasively via the use of spatial filtering electrode arrays. With these arrays, weighted combinations of monopolar electrode signals recorded from the skin surface provide spatial selectivity of the underlying electrical activity. Common spatial filters include the bipolar electrode, the longitude double differentiating (LDD) filter and the normal double differentiating (NDD) filter. In general, the spatial filtering is implemented in hardware and the performance of the spatial filtering apparatus is measured by its common mode rejection ratio (CMRR). High precision hardware differential amplifiers are used to perform the channel weighting in order to achieve high CMRR. But, this hardware is expensive and all channel weightings must be predetermined. Hence, only a few spatially filtered channels are typically derived. In this project, a distinct software equalization filter was cascaded with each of the hardware monopolar signal conditioning circuits to achieve accurate weighting and high CMRR. The simplest technique we explored was to design an equalization filter by dividing the frequency response of a“reference" (or“ideal") channel by the measured frequency response of the channel being equalized, producing the desired equalization filter in the frequency domain (conventional technique). Simulation and experimental results showed that the conventional technique is very sensitive to broadband background noise, producing poor CMRR. Thus, a technique for signal denoising that is based on signal mixing was pursued and evaluated both in simulation and laboratory experiments. The purpose of the mixing technique is to eliminate the noise as much as possible prior to equalization filter design. The simulation results show that without software equalization, CMRR is only around 30 dB; with conventional technique CMRR is around 50~60 dB. By using mixing technique, CMRR can be around 70~80 dB.
Identifer | oai:union.ndltd.org:wpi.edu/oai:digitalcommons.wpi.edu:etd-theses-1810 |
Date | 12 May 2005 |
Creators | Xia, Hongfang |
Contributors | Edward A. Clancy, Advisor, Donald Richard Brown III, Committee Member, Brian M. King, Committee Member |
Publisher | Digital WPI |
Source Sets | Worcester Polytechnic Institute |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Masters Theses (All Theses, All Years) |
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