A Novel Deep Learning Approach for Recognizing Stereotypical Motor Movements within and across Subjects on the Autism Spectrum Disorder

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static.hindawi.com/articles/cin/volume-2018/7186762/figures/7186762.fig.005a.svgz" name="7186762.fig.005a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>Time-domain</td></tr><tr class="fig-image" id="b"><td><object data="https://static.hindawi.com/articles/cin/volume-2018/7186762/figures/7186762.fig.005b.svgz" name="7186762.fig.005b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>Frequency-domain</td></tr></table>

<div>(a) and (b) show histograms and box plots which represent the frequency distribution of 30 peak lengths present within 30 randomly selected time-domain signals and 30 randomly selected frequency-domain signals, respectively.</div>

Computational Intelligence and Neuroscience

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Figure 5

Figure 5: A Novel Deep Learning Approach for Recognizing Stereotypical Motor Movements within and across Subjects on the Autism Spectrum Disorder 