Efficient use of binned data for imputing univariate time series data.

Time series data are recorded in various sectors, resulting in a large amount of data. However, the continuity of these data is often interrupted, resulting in periods of missing data. Several algorithms are used to impute the missing data, and the performance of these methods is widely varied.

Automated identification of sleep disorders using wavelet-based features extracted from electrooculogram and electromyogram signals.

Sleep is imperative for a healthy life as it rejuvenates memory, cognitive performance, cell repair and eliminates waste from the muscles. Sleep-related disorders such as insomnia, narcolepsy, sleep-disordered breathing (SDB), periodic leg movement (PLM), and bruxism lead to hormonal imbalance, slower reaction time, memory problems, depression, and headaches. This adversity of sleep disorder gained the attention of many sleep researchers.