Publication | Closed Access
A dense pressure sensitive bedsheet design for unobtrusive sleep posture monitoring
94
Citations
16
References
2013
Year
Unknown Venue
Sleep Posture CharacterizationEngineeringMachine LearningHuman Pose Estimation3D Pose EstimationBiometricsWearable TechnologyKinesiologyImage AnalysisData SciencePattern RecognitionPatient MonitoringSoft BiometricsSleepMachine VisionSleep Posture MonitoringComputer ScienceComputer VisionSleep DisorderHealth MonitoringSleep ApneaMedicineSleep PostureWearable Sensor
Sleep plays a pivotal role in the quality of life, and sleep posture is related to many medical conditions such as sleep apnea. In this paper, we design a dense pressure-sensitive bedsheet for sleep posture monitoring. In contrast to existing techniques, our bedsheet system offers a completely unobtrusive method using comfortable textile sensors. Based on high-resolution pressure distributions from the bedsheet, we develop a novel framework for pressure image analysis to monitor sleep postures, including a set of geometrical features for sleep posture characterization and three sparse classifiers for posture recognition. We run a pilot study and evaluate the performance of our methods with 14 subjects to analyze 6 common postures. The experimental results show that our proposed method enables reliable sleep posture recognition and offers better overall performance than state-of-the-art methods, achieving up to 83.0% precision and 83.2% recall on average.
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