From: Multi-sensor fusion based on multiple classifier systems for human activity identification
Feature | Formula | Feature | Formula |
---|---|---|---|
Mean (µ) | \(\overline{s} = \frac{1}{N}\sum\nolimits_{i = \,1}^{N} {s_{i} }\) | Root mean square (\(R_{ms}\)) | \(rms = \sqrt {\frac{1}{n}} \sum\nolimits_{i = 1}^{N} {\left( {s_{i} } \right)}^{2}\) |
Median (\(M_{e}\)) | \(median_{i} \left( {s_{i} } \right)\) | Peak amplitude (\(\,P_{a}\)) | \({ \hbox{max} }(s_{i} ) - { \hbox{min} }(s_{i} )\) |
Maximum (\(\,M_{a}\)) | \({ \hbox{max} }_{i} \left( {s_{i} } \right)\) | Pitch angle (\(\,P_{k}\)) | \(\arctan \left( {\frac{{x_{i} }}{{\sqrt {y^{2} + x_{i}^{2} } }}} \right)\) |
Minimum (\(\,M_{i}\)) | \({ \hbox{min} }_{i} \left( {s_{i} } \right)\) | Signal power (\(\,S_{p}\)) | \(\sum\nolimits_{i = 1}^{N} {s_{i}^{2} }\) |
Harmonic mean (\(H_{m}\)) | \(\frac{1}{N}\sum\nolimits_{i = 1}^{n} {\frac{1}{{s_{i} }}}\) | Kurtosis (\(\,K_{r}\)) | \(E\left[ {\left( {s_{i} - \overline{s} } \right)^{4} } \right]/E\left[ {\left( {s_{i} - \overline{s} } \right)^{2} } \right]^{2}\) |
Standard deviation (\(\,\sigma\)) | \(\sigma \, = \,\sqrt {\frac{1}{N}} \sum\nolimits_{i = 1}^{N} {\left( {s_{i} - \mathop s\limits^{\_} } \right)}^{2}\) | Skewness (\(\,S_{k}\)) | \(E\left[ {\left( {\frac{{s_{i} - \overline{s} }}{\sigma }} \right)^{3} } \right]\) |
Variance (\(\,\sigma^{2}\)) | \(\sigma^{2} \, = \,\frac{{\sum\nolimits_{{}}^{{}} {\left( {s_{i} - \overline{s} } \right)^{2} } }}{N}\) | Energy (\(\,E\)) | \(\frac{{\sum\nolimits_{i = 1}^{N} {\left[ {s_{i} } \right]^{2} } }}{{length(s_{i} )}}\) |
Coefficient of variation (\(\,C_{v}\)) | \(\,\frac{{\sigma_{si} }}{{\mu_{si} }}\) | Entropy (\(\,H\)) | \(\frac{{ - \sum\nolimits_{i = 1}^{N} {\left[ {S_{i} } \right]} \log \left[ {S_{i} } \right]}}{{length(S_{i} )}}\) |
Interquartile range (\(\,I_{r}\)) | \(Q_{3} (s_{i} ) - Q_{1} (s_{i} )\) | Mean frequency (µF) | \({{\sum\nolimits_{i = 1}^{N} {\left( {is_{i} (F)} \right)} } \mathord{\left/ {\vphantom {{\sum\nolimits_{i = 1}^{N} {\left( {is_{i} (F)} \right)} } {\sum\nolimits_{j = 1}^{N} {s_{j} } }}} \right. \kern-0pt} {\sum\nolimits_{j = 1}^{N} {s_{j} } }}(F)\) |