Analysis of Heart Rate Variability with an In-Ear Micro-Optic Sensor in View of Motion Artifacts
BSN '09 Proceedings of the 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks
A Flexible, Low Noise Reflective PPG Sensor Platform for Ear-Worn Heart Rate Monitoring
BSN '09 Proceedings of the 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks
Activity classification using realistic data from wearable sensors
IEEE Transactions on Information Technology in Biomedicine
IEEE Transactions on Information Technology in Biomedicine
IEEE Transactions on Information Technology in Biomedicine
An Efficient Motion-Resistant Method for Wearable Pulse Oximeter
IEEE Transactions on Information Technology in Biomedicine
Editorial note on bio, medical, and health informatics
IEEE Transactions on Information Technology in Biomedicine - Special section on new and emerging technologies in bioinformatics and bioengineering
Area-based photo-plethysmographic sensing method for the surfaces of handheld devices
Proceedings of the 24th annual ACM symposium on User interface software and technology
SpiroSmart: using a microphone to measure lung function on a mobile phone
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
Septimu2 - earphones for continuous and non-intrusive physiological and environmental monitoring
Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems
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This paper addresses the design considerations and critical evaluation of a novel embodiment for wearable photo-plethysmography (PPG) comprising a magnetic earring sensor and wireless earpiece. The miniaturized sensor can be worn comfortably on the earlobe and contains an embedded accelerometer to providemotion reference for adaptive noise cancellation. The compact wireless earpiece provides analog signal conditioning and acts as a data-forwarding device via a radio frequency transceiver. Using Bland-Altman and correlation analysis, we evaluated the performance of the proposed system against an FDA-approved ECG measurement device during daily activities. The mean ± standard deviation (SD) of the differences between heart rate measurements from the proposed device and ECG (expressed as percentage of the average between the two techniques) along with the 95% limits of agreement (LOA = ±1.96 SD) was 0.62% ± 4.51% (LOA = -8.23% and 9.46%), -0.49% ± 8.65% (-17.39% and 16.42%), and -0.32% ± 10.63% (-21.15% and 20.52%) during standing, walking, and running, respectively. Linear regression indicated a high correlation between the two measurements across the three evaluated conditions (r = 0.97, 0.82, and 0.76, respectively with p