Archives: Publications

This comprehensive review mainly analyzes and summarizes the recently published works on IEEExplore in sensor-driven smart living contexts. We have gathered over 150 research papers, especially in the past five years. We categorize them into four major research directions: activity tracker, affective computing, sleep monitoring, and ingestive behavior. We report each research direction’s summary by […]

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Sensor-Driven Achieving of Smart Living: A Review

Archives: Publications

Identifying bio-signals based-sleep stages requires time-consuming and tedious labor of skilled clinicians. Deep learning approaches have been introduced in order to challenge the automatic sleep stage classification conundrum. However, the difficulties can be posed in replacing the clinicians with the automatic system due to the differences in many aspects found in individual bio-signals, causing the […]

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MetaSleepLearner: A Pilot Study on Fast Adaptation of Bio-signals-Based Sleep Stage Classifier to New Individual Subject Using Meta-Learning

Archives: Publications

Recognizing the movements during sleep is crucial for the monitoring of patients with sleep disorders. However, the utilization of Ultra-Wideband (UWB) radar for the classification of human sleep postures has not been explored widely. This study investigates the performance of the off-the-shelf single antenna UWB in a novel application of sleep postural transition (SPT) recognition. […]

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SleepPoseNet: Multi-View for Sleep Postural Transition Recognition Using UWB

Archives: Publications

For several decades, electroencephalography (EEG) has featured as one of the most commonly used tools in emotional state recognition via monitoring of distinctive brain activities. An array of datasets has been generated with the use of diverse emotion-eliciting stimuli and the resulting brainwave responses conventionally captured with high-end EEG devices. However, the applicability of these […]

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Consumer Grade Brain Sensing for Emotion Recognition

Archives: Publications

For several decades, electroencephalography (EEG) has featured as one of the most commonly used tools in emotional state recognition via monitoring of distinctive brain activities. An array of datasets has been generated with the use of diverse emotion-eliciting stimuli and the resulting brainwave responses conventionally captured with high-end EEG devices. However, the applicability of these […]

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Deep Neural Networks with Weighted Averaged Overnight Airflow Features for Sleep Apnea-Hypopnea Severity Classification