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A Survey on Context-Aware Sensing for Body Sensor Networks

Barbara T. Korel, Simon G. M. Koo
2010 Wireless Sensor Network  
The context information derived from a BSN can be used in pervasive healthcare monitoring for relating importance to events and specifically for accurate episode detection.  ...  In this paper, we address the issue of context-aware sensing in BSNs, and survey different techniques for deducing context awareness.  ...  Thus metric, non-exponential time is added to the system resulting in the hierarchical hidden semi-Markov Model.  ... 
doi:10.4236/wsn.2010.28069 fatcat:gpjsipwqb5g2bdpx3pr7s53osq

A Real-Time, Multiview Fall Detection System: A LHMM-Based Approach

N. Thome, S. Miguet, S. Ambellouis
2008 IEEE transactions on circuits and systems for video technology (Print)  
In this paper, we propose a multiview approach to achieve this goal, where motion is modeled using a layered hidden Markov model (LHMM).  ...  Index Terms-Fall detection, layered hidden Markov model (LHMM), metric rectification, multiview pose classification. 1051-8215/$25.00 © 2008 IEEE Authorized licensed use limited to: IEEE Xplore.  ...  It has been accomplished by the development of abstract hidden Markov models, hierarchical hidden Markov models and layered hidden mMarkov models [10] . C.  ... 
doi:10.1109/tcsvt.2008.2005606 fatcat:hu77jtr45rcqlm3fyreprwgaxu

A Review on Video-Based Human Activity Recognition

Shian-Ru Ke, Hoang Thuc, Yong-Jin Lee, Jenq-Neng Hwang, Jang-Hee Yoo, Kyoung-Ho Choi
2013 Computers  
In the third stage of the core technology, the activity detection and classification algorithms are used to recognize various human activities based on the represented features.  ...  Finally the domains of applications are discussed in detail, specifically, on surveillance environments, entertainment environments and healthcare systems.  ...  [114] model human motions with HMMs, and fuse audio channel data with the results of HMMs to detect a falling event.  ... 
doi:10.3390/computers2020088 fatcat:zb3wlmwjjvbfne2ck6uyjtffdq

SensCare: Semi-automatic Activity Summarization System for Elderly Care [chapter]

Pang Wu, Huan-Kai Peng, Jiang Zhu, Ying Zhang
2012 Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering  
hierarchical way.  ...  SensCare also demonstrates that unsupervised hierarchical activity segmentation and semi-automatic summarization can be achieved with reasonably good accuracy (average F1 score 0.65) and the system is  ...  difficult to deal with [6] , variations of HMM were developed such as Layered HMM [19] , Switching Hidden Semi-Markov Model (HSMM) [6] and Hierarchical Hidden Markov Model (HHMM) [7] for sensor-based  ... 
doi:10.1007/978-3-642-32320-1_1 fatcat:24jtv55v5rcmregtapnkpas6oy

Formal Modeling Techniques for Ambient Assisted Living

Guido Parente, Christopher D. Nugent, Xin Hong, Mark P. Donnelly, Liming Chen, Enrico Vicario
2010 Ageing International  
We consider the following formal modeling tools and techniques: fault trees, evidential reasoning, evidential ontology networks, temporal logic, hidden Markov models and partially observable Markov models  ...  In the development of systems of ambient assisted living (AAL), formalized models and analysis techniques can provide a ground that makes development amenable to a systematic approach.  ...  Acknowledgements This work has been supported in part by the Centre for Intelligent Point of Care Sensors, funded by the Department for Education and Learning within Northern Ireland.  ... 
doi:10.1007/s12126-010-9086-8 fatcat:4wiolhbmuvd63grtfrec5klmbu

Research Trends in Environmental Sound Analysis and Anomalous Sound Detection

Keisuke IMOTO, Yohei KAWAGUCHI
2022 IEICE ESS FUNDAMENTALS REVIEW  
Environmental sound analysis and anomalous sound detection have seen extensive development, and they are becoming an established field of acoustic and audio processing.  ...  In this review paper, we outline the research topics addressed in environmental sound analysis and anomalous sound detection, and we introduce the challenges and recent research trends, as well as our  ...  Tsai, "Healthcare audio event classification using hidden Markov models and hierarchical hidden Markov models," Proc.  ... 
doi:10.1587/essfr.15.4_268 fatcat:nptrkgbv25fovdzduercd55cxe

Exploiting Prosody Hierarchy and Dynamic Features for Pitch Modeling and Generation in HMM-Based Speech Synthesis

Chi-Chun Hsia, Chung-Hsien Wu, Jung-Yun Wu
2010 IEEE Transactions on Audio, Speech, and Language Processing  
Index Terms-Dynamic features, hidden Markov model (HMM)-based speech synthesis, pitch modeling and generation, prosody hierarchy.  ...  This paper proposes a method for modeling and generating pitch in hidden Markov model (HMM)-based Mandarin speech synthesis by exploiting prosody hierarchy and dynamic pitch features.  ...  Frame Layer Modeling Dynamic features at the frame layer are modeled using hidden Markov models, as (13) where is the set of HMM parameters, and is the state sequence. and represent the observation  ... 
doi:10.1109/tasl.2010.2040791 fatcat:jbhyzk3uavcbtp2wai63rqo6ee

Detection of Emotion of Speech for RAVDESS Audio Using Hybrid Convolution Neural Network

Tanvi Puri, Mukesh Soni, Gaurav Dhiman, Osamah Ibrahim Khalaf, Malik alazzam, Ihtiram Raza Khan, Antonio Gloria
2022 Journal of Healthcare Engineering  
These properties were used in the classification of emotions using techniques, such as Long Short-Term Memory (LSTM), CNNs, Hidden Markov models (HMMs), and Deep Neural Networks (DNNs).  ...  In this paper, we use the Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) audio records.  ...  An extreme learning machine (ELM) [17] is the addition of a neural network with one hidden layer which is used to conduct a classification of emotional characteristics on the utterance level.  ... 
doi:10.1155/2022/8472947 pmid:35265307 pmcid:PMC8898841 fatcat:j4u4spkc5nfjzbfenmg226ivxu

Exploiting structured human interactions to enhance estimation accuracy in cyber-physical systems

Yunlong Gao, Shaohan Hu, Renato Mancuso, Hongwei Wang, Minje Kim, PoLiang Wu, Lu Su, Lui Sha, Tarek Abdelzaher
2015 Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems - ICCPS '15  
We demonstrate through simulations and a physical implementation the degree to which knowledge of workflow can increase sensing accuracy.  ...  The intellectual contribution lies in an algorithm for joint estimation of the current state of the workflow together with correction of noisy sensor measurements, given only the noisy measurements and  ...  Acknowledgment This work was funded in part by NSF grant CNS 13-29886 and DTRA grant HDTRA1-1010120.  ... 
doi:10.1145/2735960.2735965 dblp:conf/iccps/GaoHMWKWSSA15 fatcat:chwlbnxchbgxxm24mpurat5fpu

Two-step detection of water sound events for the diagnostic and monitoring of dementia

Patrice Guyot, Julien Pinquier, Xavier Valero, Francesc Alias
2013 2013 IEEE International Conference on Multimedia and Expo (ICME)  
The second stage improves the system precision by classifying the segmented streams into water/non-water sound events using Gammatone Cepstral Coefficients and Support Vector Machines.  ...  Specifically, water sounds are very useful to track and identify abnormal behaviors form everyday activities (e.g. hygiene, household, cooking, etc.).  ...  Among the classifiers, some of the most popular are: k-Nearest Neighbor (kNN), Gaussian Mixture Models (GMM), Support Vectors Machine (SVM) and Hidden Markov Models (HMM), the latter modelling the temporal  ... 
doi:10.1109/icme.2013.6607558 dblp:conf/icmcs/GuyotPVA13 fatcat:7b66oooquncl7eyqdrfmmwsfnu

Healthcare Techniques Through Deep Learning: Issues, Challenges and Opportunities

Dur-E-Maknoon Nisar, Rashid Amin, Noor-Ul-Huda Shah, Mohammed A. Al Ghamdi, Sultan H. Almotiri, Meshrif Alruily
2021 IEEE Access  
The Hidden Markov Models (HMMs) used Gaussian models to represent the sound waves. These models are amateurish for non-linear functions.  ...  HMMs Hidden Markov Models MAVIS Microsoft Audio Video Indexing Service BTG Brain tumor graphs MLP Multi-layer perception BP Backpropagation algorithm GBM Glioblastoma malignant brain tumor  ... 
doi:10.1109/access.2021.3095312 fatcat:3ddvsz5eozav7opv6vvanohcs4

Multimodal Machine Learning: A Survey and Taxonomy [article]

Tadas Baltrušaitis, Chaitanya Ahuja, Louis-Philippe Morency
2017 arXiv   pre-print
Multimodal machine learning aims to build models that can process and relate information from multiple modalities.  ...  In order for Artificial Intelligence to make progress in understanding the world around us, it needs to be able to interpret such multimodal signals together.  ...  Hidden Markov models (HMM) have also been used for visual speech generation [203] and textto-speech [245] tasks.  ... 
arXiv:1705.09406v2 fatcat:262fo4sihffvxecg4nwsifoddm

Sensor-Based Activity Recognition

Liming Chen, J. Hoey, C. D. Nugent, D. J. Cook, Zhiwen Yu
2012 IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)  
We make a primary distinction in this paper between data-driven and knowledge-driven approaches, and use this distinction to structure our survey.  ...  Then we review the major approaches and methods associated with sensor-based activity monitoring, modeling and recognition from which strengths and weaknesses of those approaches are highlighted.  ...  These include the dynamically multi-linked HMM model [137] , the hierarchical HMM model [138] , the Coupled HMM [139] , the mixed-memory Markov model [140] and the Layered Hidden Markov Models (LHMMs  ... 
doi:10.1109/tsmcc.2012.2198883 fatcat:6s6uew7xhjglva2wikyulmduiy

Multioccupant Activity Recognition in Pervasive Smart Home Environments

Asma Benmansour, Abdelhamid Bouchachia, Mohammed Feham
2015 ACM Computing Surveys  
The aim is to recognize the sequence of actions by a specific person using sensor readings. Most of the research has been devoted to activity recognition of single occupants in the environment.  ...  It presents the latest developments and highlights the open issues in this field.  ...  Thus, hierarchical graphical models (e.g., Hierarchical HMM or Abstract HMM) look more suitable in this case. Parallel Hidden Markov Model (PHMM).  ... 
doi:10.1145/2835372 fatcat:cmsotnnymbecng5g4ydkoj2ev4

A Survey of Content-Aware Video Analysis for Sports

Huang-Chia Shih
2018 IEEE transactions on circuits and systems for video technology (Print)  
Specifically, we focus on the video content analysis techniques applied in sportscasts over the past decade from the perspectives of fundamentals and general review, a content hierarchical model, and trends  ...  Content-aware analysis methods are discussed with respect to object-, event-, and context-oriented groups.  ...  , scoreboard identification [160] Audio SVM baseball Hit the ball, exciting speech Highlight extraction, summarization [161] Audio Entropic Prior Hidden Markov Models (EP-HMM) Baseball, golf  ... 
doi:10.1109/tcsvt.2017.2655624 fatcat:rwqzu46sgfb7tpkcav4ysmh6ae
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