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Probabilistic modelling of gait for robust passive monitoring in daily life
2020
IEEE journal of biomedical and health informatics
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To locate and characterize stationary gait segments in free living using accelerometers, we present an unsupervised probabilistic framework designed to segment signals into differing gait and non-gait ...
This framework incorporates empirical assumptions about gait into a principled graphical model with all of its merits. ...
ACKNOWLEDGMENT The authors wish to thank all participants for their enthusiasm to contribute to this study, and for welcoming us in their own homes. ...
doi:10.1109/jbhi.2020.3037857
pmid:33180738
fatcat:ceojeklcdnbrlbhxj4bqrpnbyu
Plants Don't Walk on the Street: Common-Sense Reasoning for Reliable Semantic Segmentation
[article]
2021
arXiv
pre-print
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We present an initial study adapting the well-established Probabilistic Soft Logic (PSL) framework to validate and improve on the problem of semantic segmentation. ...
We propose to use a partly human-designed, partly learned set of rules to describe relations between objects of a traffic scene on a high level of abstraction. ...
The research of S.H. was partly funded by the Federal Ministry of Education and Research of Germany as part of the competence center for machine learning ML2R (01IS18038B). ...
arXiv:2104.09254v1
fatcat:udu4x6hqyrg5bbowkkyvrzvlpy
Dynamic factor graphs: A novel framework for multiple features data fusion
2010
2010 IEEE International Conference on Acoustics, Speech and Signal Processing
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The Dynamic Tree [1] (DT) Bayesian Network is a powerful analytical tool for image segmentation and object segmentation tasks. ...
In this paper, we propose a novel framework, dynamic factor graphs (DFG), where data segmentation and fusion are combined in the same framework. ...
Tory Cobb for the helpful discussion during the project and Office of Naval Research for financial support. ...
doi:10.1109/icassp.2010.5495145
dblp:conf/icassp/KampaPS10
fatcat:zhqhexp3lzdhphhycclpcteloa
Probabilistic modelling of gait for robust passive monitoring in daily life
[article]
2020
arXiv
pre-print
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Our flexible probabilistic framework combines empirical assumptions about gait into a principled graphical model with all of its merits. ...
To locate and characterize stationary gait segments in free living using accelerometers, we present an unsupervised statistical framework designed to segment signals into differing gait and non-gait patterns ...
In this work, we propose a unified framework for gait detection and gait pattern analysis. ...
arXiv:2004.03047v1
fatcat:jpd5noij6fhofjnvoh54br6fza
Activity recognition via user-trace segmentation
2008
ACM transactions on sensor networks
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From the traces we discover primitive signal segments that can be used for building a probabilistic activity model to recognize goals directly. ...
We present our theoretical framework for activity recognition, and demonstrate the effectiveness of our new approach using the data collected in an indoor wireless environment. ...
ACKNOWLEDGMENT We thank the anonymous referees for their valuable comments. ...
doi:10.1145/1387663.1387665
fatcat:hjwdsmxs35e6xj7cgwv5xfa6fi
Probabilistic Rail Vehicle Localization With Eddy Current Sensors in Topological Maps
2011
IEEE transactions on intelligent transportation systems (Print)
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We outline an onboard localization system within a probabilistic framework, with special attention on signal processing for speed estimation and pattern recognition. ...
The precise localization of rail vehicles is fundamental for the development and employment of more efficient train control systems in security, logistics and disposition applications. ...
ACKNOWLEDGMENT The authors would like to thank the German Federal Ministry of Economics and Technology (BMWi), Bombardier Sweden, and the Karlsruher Verkehrsbetriebe. ...
doi:10.1109/tits.2011.2161291
fatcat:4gjeu3omardjvieicwcednupvy
Mobile Robot Localization: A Review of Probabilistic Map-Based Techniques
2015
IAES International Journal of Robotics and Automation
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This work presents a comprehensive review of current probabilistic developments used to calculate position by mobile robots in indoor environments. ...
The research community has devoted a considerable amount of time to provide solutions for the localization problem. ...
ACKNOWLEDGEMENTS The authors want to thank for their finantial support to: -Consejo Nacional de Ciencia y Tecnolgia, Mexico. -FOFI, Universidad Autonoma de Queretaro, Mexico. ...
doi:10.11591/ijra.v4i1.pp73-81
fatcat:45nv2jsddvg43pkxduzpk3vfpi
A Probabilistic Representation for Dynamic Movement Primitives
[article]
2016
arXiv
pre-print
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Because of this they have become a popular represen- tation for motor primitives. ...
We show that inference in this probabilistic model automatically leads to a feedback term to online modulate the execution of a DMP. ...
An interesting component of probabilistic DMPs is the fact that -given a reference signal to track -sensor feedback is automatically considered when executing a desired behavior. ...
arXiv:1612.05932v1
fatcat:ata7urwtrvfxhacfk467fxo22i
Extracting data from human manipulation of objects towards improving autonomous robotic grasping
2012
Robotics and Autonomous Systems
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This will enable modelling a class of tasks from sets of repeated demonstrations of the same task, so that a generalised probabilistic representation is derived to be used for task planning in artificial ...
Humans excel in manipulation tasks, a basic skill for our survival and a key feature in our manmade world of artefacts and devices. ...
ICT 231640; by the Portuguese Foundation for Science and Technology (FCT), with scholarships for Ricardo Martins (SFRH/BD/65990/2009) and Diego Faria (SFRH/BD/30655/2006); and by the Institute of Systems ...
doi:10.1016/j.robot.2011.07.020
fatcat:nlnage3pefamnmry4hqwgdl23q
The social signal interpretation (SSI) framework
2013
Proceedings of the 21st ACM international conference on Multimedia - MM '13
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The paper at hand introduces Social Signal Interpretation (SSI), a framework for real-time recognition of social signals. ...
Automatic detection and interpretation of social signals carried by voice, gestures, mimics, etc. will play a key-role for next-generation interfaces as it paves the way towards a more intuitive and natural ...
CONCLUSION We introduced Social Signal Interpretation (SSI), a framework for real-time recognition of social signals. ...
doi:10.1145/2502081.2502223
dblp:conf/mm/WagnerLBDKA13
fatcat:3s3k4bfapva5jdmwg43t7mmkha
Gaussian Mixture Models for Detecting Sleep Apnea Events Using Single Oronasal Airflow Record
2020
Applied Sciences
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In this paper, we propose a new probabilistic algorithm based on (only) oronasal respiration signal for automated detection of apnea events during sleep. ...
The proposed approach contributes a new probabilistic framework for detecting sleep apnea events using a single airflow record with an improved capability to generalize over different apnea severity conditions ...
For automatic detection of apneic events, we considered classification based on a probabilistic view using a GMM-based modeling framework. ...
doi:10.3390/app10217889
fatcat:v24rzi6jtzajjepg7dxrqf64qe
Probabilistic modelling of gait for remote passive monitoring applications
[article]
2019
arXiv
pre-print
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We have developed a probabilistic framework for unsupervised analysis of the gait, clustering it into different types, which can be used to evaluate gait abnormalities occurring in daily life. ...
In this work we have studied the problem of modelling real-life gait which is a very indicative behaviour for multiple movement disorders including Parkinson's disease (PD). ...
Probabilistic modelling of gait In this section we layout the minimalistic assumptions that we embed in our probabilistic model for analysis of gait data from wearable accelerometer sensors. ...
arXiv:1812.02585v2
fatcat:6xlbxeezhzhppg23i4pxqtkorq
Learning Motion Patterns from Multiple Observations along the Actions Phases of Manipulative Tasks
2010
Zenodo
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In this work we present a probabilistic approach to find motion patterns in manipulative tasks by looking for similarities among the relevant features along of the actions phases of a trajectories dataset ...
From multiples observations of human movements we can align all signals temporally to perform a learning process based on selection of relevant features by analyzing their probability distribution and ...
In previous work [10] we developed a probabilistic framework for hand trajectory classification where curvatures and hand orientation where detected in 3D space. ...
doi:10.5281/zenodo.4553420
fatcat:evakh4fjbnhznk4rpk7uqtvv4i
Anomaly Detection in Elderly Daily Behavior in Ambient Sensing Environments
[chapter]
2016
Lecture Notes in Computer Science
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For this purpose, we first introduce an abstraction layer to create a common ground for home sensor configurations. Next, we build a probabilistic spatio-temporal model to summarize daily behavior. ...
Among the target groups of people, elderly are a population eager for "choices for living arrangements", which would allow them to continue living in their homes but at the same time provide the health ...
We would also like to thank Hieu Pham (DomoSafety) and Florent Monay (Idiap) for technical discussions. ...
doi:10.1007/978-3-319-46843-3_4
fatcat:3vs5glv5tnfd7ldtoqxhfqg2am
A Survey of Model-based Sensor Data Acquisition and Management
[chapter]
2012
Managing and Mining Sensor Data
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In recent years, due to the proliferation of sensor networks, there has been a genuine need of researching techniques for sensor data acquisition and management. ...
We, then, discuss the application of models in sensor data cleaning; followed by a discussion on model-based methods for querying sensor data. ...
The segment estimation continues until the new data tuple falls out of the upper and lower lines for a segment. ...
doi:10.1007/978-1-4614-6309-2_2
fatcat:v4ztge3vjvdltfnywl2riqemou
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