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Wearable barometric pressure sensor to improve postural transition recognition of mobility-impaired stroke patients
Related publications (49)
Suitability of commercial barometric pressure sensors to distinguish sitting and standing activities for wearable monitoring
Kamiar Aminian, Anisoara Ionescu, Julien Chardonnens, Fabien Massé, Alan Kevin Bourke
Despite its medical relevance, accurate recognition of sedentary (sitting and lying) and dynamic activities (e.g. standing and walking) remains challenging using a single wearable device. Currently, trunk-worn wearable systems can differentiate sitting fro ...
Elsevier2014A system to measure the kinematics during the entire ski jump sequence using inertial sensors
Kamiar Aminian, Julien Favre, Julien Chardonnens
Three-dimensional analysis of the entire sequence in ski jumping is recommended when studying the kinematics or evaluating performance. Camera-based systems which allow three-dimensional kinematics measurement are complex to set-up and require extensive po ...
Elsevier2013Inertial measurement unit and biomechanical analysis of swimming: an update
Kamiar Aminian, Grégoire Millet, Farzin Dadashi
The biomechanical analysis of swimming always faced impeding factors of measurement in the aquatic environment. Our current knowledge of swimming locomotion is very much owing to employing video cameras to capture the body kinematics. Nevertheless, the rec ...
2013An algorithm for automatic inertial sensor calibration
Jan Skaloud, Stéphane Guerrier
We present an algorithm for determining the nature of stochastic processes together with its parameters based on the analysis of time series of inertial errors. The algorithm is suitable mainly (but not only) for situations when several stochastic processe ...
2013Automatic Front-Crawl Temporal Phase Detection Using Adaptive Filtering of Inertial Signals
Kamiar Aminian, Grégoire Millet, Farzin Dadashi, Florent Crettenand
This study introduces a novel approach for automatic temporal phase detection and inter-arm coordination estimation in front-crawl swimming using inertial measurement units (IMUs). We examined the validity of our method by comparison against a video-based ...
Taylor & Francis2013A Hidden Markov Model of the Breaststroke Swimming Temporal Phases Using Wearable Inertial Measurement Units
Kamiar Aminian, Arash Arami, Grégoire Millet, Farzin Dadashi, Florent Crettenand
The recent advances in wearable inertial sensors opened a new horizon for pervasive measurement of human locomotion even in aquatic environment. In this paper we proposed an automatic approach of detecting the key temporal events of breaststroke swimming a ...
IEEE2013A Hidden Markov Model of the Breaststroke Swimming Temporal Phases Using Wearable Inertial Measurement Units
Kamiar Aminian, Arash Arami, Grégoire Millet, Farzin Dadashi, Florent Crettenand
The recent advances in wearable inertial sensors opened a new horizon for pervasive measurement of human locomotion even in aquatic environment. In this paper we proposed an automatic approach of detecting the key temporal events of breaststroke swimming a ...
Ieee2013On-line anomaly detection and resilience in classifier ensembles
José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Hesam Sagha, Hamidreza Bayati
Detection of anomalies is a broad field of study, which is applied in different areas such as data monitoring, navigation, and pattern recognition. In this paper we propose two measures to detect anomalous behaviors in an ensemble of classifiers by monitor ...
Elsevier2013Distinguishing Sitting and Standing Activities Using a Wearable Barometric Pressure Monitor
Kamiar Aminian, Anisoara Ionescu, Julien Chardonnens, Fabien Massé, Alan Kevin Bourke
Recent advancements in wearable inertial sensor technology have enabled extensive research into activity classification. However, the distinction between the sitting and standing activities using trunk-worn wearable monitoring systems remains challenging, ...
2013An exploration with online complex activity recognition using cellphone accelerometer
Karl Aberer, Zhixian Yan, Dipanjan Chakraborty, Sumit Mittal
We investigate the problem of online detection of complex activities (such as cooking, lunch, work at desk), i.e., recognizing them while the activities are being performed using parts of the sensor data. In contrast to prior work, where complex activity r ...
ACM2013