J
Julien Penders
Researcher at IMEC
Publications - 114
Citations - 3730
Julien Penders is an academic researcher from IMEC. The author has contributed to research in topics: Wireless sensor network & Body area network. The author has an hindex of 32, co-authored 112 publications receiving 3357 citations. Previous affiliations of Julien Penders include Katholieke Universiteit Leuven & Samsung.
Papers
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Journal ArticleDOI
Energy Harvesting for Autonomous Wireless Sensor Networks
TL;DR: The typical power requirements of some current portable devices, including a body sensor network, are shown in Figure 1.
Journal ArticleDOI
3D gait assessment in young and elderly subjects using foot-worn inertial sensors
TL;DR: The validation of a new wearable system based on the detection of temporal parameters, coupled to optimized fusion and de-drifted integration of inertial signals that allows to analyze various aspects of gait, including turns, gait initiation and termination, or inter-cycle variability is described.
Journal ArticleDOI
Wearable, Wireless EEG Solutions in Daily Life Applications: What are we Missing?
TL;DR: This work discussed state-of-the-art in wireless and wearable EEG solutions and a number of aspects where such solutions require improvements when handling electrical activity of the brain, including personal traits and sensory inputs, brain signal generation and acquisition, brain sign analysis, and feedback generation.
Proceedings ArticleDOI
Towards mental stress detection using wearable physiological sensors
TL;DR: A promising feature subset was found for future development of a personalized stress monitor and a consistent classification accuracy between stress and non stress conditions of almost 80% was found.
Journal ArticleDOI
Estimating Energy Expenditure Using Body-Worn Accelerometers: A Comparison of Methods, Sensors Number and Positioning
TL;DR: It is concluded that choosing the best performing single sensor does not reduce EE estimation accuracy compared to a five sensors system and can reliably be used, however, EE estimation errors can increase up to 80% if a nonoptimal sensor location is chosen.