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Probabilistic identification of sit-to-stand and stand-to-sit with a wearable sensor

Uriel Martinez-Hernandez, Abbas A. Dehghani-Sanij
2018 Pattern Recognition Letters  
Acknowledgments This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) for the 'Wearable soft robotics for independent living' project (EP/M026388/1).  ...  In this work, an approach composed of a Bayesian formulation and a sequential analysis method, is presented for identification of sit-to-stand (SiSt) and stand-to-sit (StSi) activities.  ...  Identification of SiSt and StSi, using the probabilistic approach and one wearable sensor, are validated with experiments in offline, realtime and a simulated environment.  ... 
doi:10.1016/j.patrec.2018.03.020 fatcat:mingdlmy2fgdppds3a3i3dq4f4

Combining multiple sensors for event recognition of older people

Carlos Fernando Crispim-Junior, Baptiste Fosty, Rim Romdhane, Qiao Ma, Francois Bremond, Monique Thonnat
2013 Proceedings of the 1st ACM international workshop on Multimedia indexing and information retrieval for healthcare - MIIRH '13  
The evaluation presents the preliminary results of this approach on two cases: the combination of events from heterogeneous sensors (a RGB camera and a wearable inertial sensor); and the combination of  ...  conflicting events from video cameras with a partially overlapped field of view (a RGB-and a RGB-D-camera).  ...  For instance, we present the modeling of a Person posture (e.g., Sitting, Standing) using events generated from a video-camera and a wearable inertial sensor.  ... 
doi:10.1145/2505323.2505329 dblp:conf/mm/JuniorFRMBT13 fatcat:dc54m4otejeddhawpo6h7ag7cq

A novel approach for modelling and classifying sit-to-stand kinematics using inertial sensors [article]

Maitreyee Wairagkar, Emma Villeneuve, Rachel King, Balazs Janko, Malcolm Burnett, Ann Ashburn, Veena Agarwal, R. Simon Sherratt, William Holderbaum, William Harwin
2021 arXiv   pre-print
We propose a three-segment body model for estimating sit-to-stand kinematics using only two wearable inertial sensors, placed on the shank and back.  ...  Sit-to-stand transitions are an important part of activities of daily living and play a key role in functional mobility in humans.  ...  Acknowledgments The authors would like to thank all the participants in this study who helped in recording the data and enabled this research.  ... 
arXiv:2107.06859v1 fatcat:a6dcxx2pjza75kzlphi3rxg2pa

Effectiveness of a Batteryless and Wireless Wearable Sensor System for Identifying Bed and Chair Exits in Healthy Older People

Roberto Shinmoto Torres, Renuka Visvanathan, Stephen Hoskins, Anton van den Hengel, Damith Ranasinghe
2016 Sensors  
They wore a batteryless, lightweight and wireless sensor over their attire and performed a set of broadly scripted activities.  ...  We investigate the recognition of bed and chair exits in real-time using a wireless wearable sensor worn by healthy older volunteers. Fourteen healthy older participants joined in supervised trials.  ...  We wish to thank Shailaja Nair for helping with the recruitment of participants for the trials.  ... 
doi:10.3390/s16040546 pmid:27092506 pmcid:PMC4851060 fatcat:5iudui24lvcjxayhlmql7x3kii

Daily Living Activity Recognition In-The-Wild: Modeling and Inferring Activity-Aware Human Contexts

Muhammad Ehatisham-ul-Haq, Fiza Murtaza, Muhammad Awais Azam, Yasar Amin
2022 Electronics  
The proposed idea is validated using a series of experiments, and it achieved an average balanced accuracy of 89.43%, which proves its effectiveness.  ...  , and phone states) using portable accelerometer sensors.  ...  Acknowledgments: This research work is supported by the School of Information Technology, Whitecliffe, Wellington, New Zealand, and Air University, Islamabad, Pakistan.  ... 
doi:10.3390/electronics11020226 fatcat:cqykt235grcv3bn2i6wfzexwyy

Evaluation of a monitoring system for event recognition of older people

Carlos Fernando Crispim-, Vasanth Bathrinarayanan, Baptiste Fosty, Alexandra Konig, Rim Romdhane, Monique Thonnat, Francois Bremond
2013 2013 10th IEEE International Conference on Advanced Video and Signal Based Surveillance  
Most of available research prototypes for older people monitoring focus on fall detection or gait analysis and rely on wearable, environmental, or video sensors.  ...  The prototype uses as input a 2D RGB camera, and its performance is compared to the use of a RGB-D camera.  ...  transfer is characterized by transfers between sitting and standing posture), and the identification of a person presence in one or more zones.  ... 
doi:10.1109/avss.2013.6636634 dblp:conf/avss/CrispimBFKRTB13 fatcat:weawmlj4mbaodpgsosfxvoxdei

Hierarchical Coherent Anomaly Fall Detection Low Bandwidth System with Combination of Wearable Sensors for Identifying Behavioral Abnormalities

Jilan Zhou, Yanmin Zhao
2020 IEEE Access  
The classification is spread on various sensor nodes, and a computer for a specific station, the distribution of multiple action classes is demonstrated to follow a mixture of subspace model for each action  ...  The probabilistic theoretical paradigm is used to identify three types of irregularities, including spatial deviations, timing anomalies, and anomalies of sequence.  ...  The wearable sensor is an Ocean node with a wireless connection with an intelligent home system and sends alarm telegrams automatically in case of a fall.A portable, lightweight, and non-toxic pH sensor  ... 
doi:10.1109/access.2020.3012001 fatcat:pywsfijx3vczhatkad6qf2fcly

Mining user activity as a context source for search and retrieval

Zhengwei Qiu, Aiden R. Doherty, Cathal Gurrin, Alan F. Smeaton
2011 2011 International Conference on Semantic Technology and Information Retrieval  
In this paper we discuss how we can gather user activity automatically as a context source from a wearable mobile device and we evaluate the accuracy of our proposed user activity recognition algorithm  ...  We discuss promising experimental results, possible approaches to improve our algorithms, and the impact of this work in modelling user context toward enhanced search and retrieval.  ...  Recall that the four activities we are concerned with are: Sitting/Standing,Walking, Driving and Lying down. A.  ... 
doi:10.1109/stair.2011.5995782 fatcat:w47d5kwxyrfbzjjm7oezqqot3a

Human activity recognition using multisensor data fusion based on Reservoir Computing

Filippo Palumbo, Claudio Gallicchio, Rita Pucci, Alessio Micheli
2016 Journal of Ambient Intelligence and Smart Environments  
Our results show that, with an appropriate configuration of the information fusion chain, the proposed system reaches a very good accuracy with a low deployment cost.  ...  In order to achieve an effective and responsive classification, a decision tree based on multisensor data-stream is applied fusing data coming from embedded sensors on the smartphone and environmental  ...  Acknowledgments This work is partially supported by the EU FP7 RU-BICON project (contract no. 269914), by the EU FP7 GiraffPlus project (contract no. 288173), and by the EU FP7 DOREMI project (contract  ... 
doi:10.3233/ais-160372 fatcat:w3mjkpnkfjf3lancfzr5h35iee

Event Recognition for Unobtrusive Assisted Living [chapter]

Nikos Katzouris, Alexander Artikis, Georgios Paliouras
2014 Lecture Notes in Computer Science  
In particular, we present our knowledge-driven approach to the detection of Activities of Daily Living (ADL) and functional ability, based on a probabilistic version of the Event Calculus.  ...  USEFIL is an FP7 project aiming to provide health-care assistance in a smart-home setting. We present the data fusion component of USEFIL which is based on a complex event recognition methodology.  ...  acknowledgement The research leading to these results has received funding from the European Union, Seventh Framework Programme (FP7/2007-2013), under grant agreements n o 288532 (USEFIL) and n o 619435  ... 
doi:10.1007/978-3-319-07064-3_41 fatcat:imszu6qqzbdp5he3hav6mdtx4e

A Hybrid Deep Residual Network for Efficient Transitional Activity Recognition Based on Wearable Sensors

Sakorn Mekruksavanich, Narit Hnoohom, Anuchit Jitpattanakul
2022 Applied Sciences  
This study aims to present a hybrid deep residual model for transitional activity recognition utilizing signal data from wearable sensors.  ...  The developed model enhances the ResNet model with hybrid Squeeze-and-Excitation (SE) residual blocks combining a Bidirectional Gated Recurrent Unit (BiGRU) to extract deep spatio-temporal features hierarchically  ...  , and lying) and six transitional actions (sit-to-stand, stand-to-sit, sit-to-lie, lie-to-sit, lie-to-stand, stand-to-lie).  ... 
doi:10.3390/app12104988 fatcat:3obt7tibjjbdhp72jvzyeozpp4

A Novel Hybrid Deep Learning Model for Activity Detection Using Wide-Angle Low-Resolution Infrared Array Sensor

K A Muthukumar, Mohdher Bouazizi, Tomaki Ohtsuki
2021 IEEE Access  
There is also a risk of damage to the device if they fall accidentally. In such situations, non-wearable devices provide several advantages compared with wearable ones.  ...  These conventional methods extract activity features manually to identify activities. As a result, the identification of activity with different people is less accurate. Mashiyama et al.  ... 
doi:10.1109/access.2021.3084926 fatcat:rgcbee4ltrhdrmw363jaweukru

Assisted living technologies for older adults

Parisa Rashidi
2012 Proceedings of the 2nd ACM SIGHIT symposium on International health informatics - IHI '12  
Link *See: A Tutorial Introduction to Automated Activity and Intention Recognition by Sebastian Bader, Thomas Kirste.  ...  A., Fausset, C. B., Rogers, W. A. (2011). Atlanta, GA: Georgia Institute of Technology, School of Psychology, Human Factors and Aging Laboratory.  ... 
doi:10.1145/2110363.2110478 dblp:conf/ihi/Rashidi12 fatcat:vavobpvbqzfslm4343duxh7yfe

C2FHAR: Coarse-to-Fine Human Activity Recognition with Behavioral Context Modeling using Smart Inertial Sensors

Muhammad Ehatisham-ul-Haq, Muhammad Awais Azam, Yasar Amin, Usman Naeem
2020 IEEE Access  
Smart sensing devices are furnished with an array of sensors, including locomotion sensors, which enable continuous and passive monitoring of human activities for the ambient assisted living.  ...  Moreover, it is essential to infer a user's behavioral context along with the physical activity to enable context-aware and knowledge-driven applications in real-time.  ...  These FGAs are related to the static activities of sitting and standing with the corresponding behavioral contexts.  ... 
doi:10.1109/access.2020.2964237 fatcat:zxmbpn3elrbelowwfldib3vhyi

Accelerometry-Based Classification of Human Activities Using Markov Modeling

Andrea Mannini, Angelo Maria Sabatini
2011 Computational Intelligence and Neuroscience  
wearable sensor systems are proposed for long-term monitoring.  ...  This paper is concerned with the machine learning algorithms needed to perform the classification task.  ...  They are also grateful to the anonymous reviewers for their valuable comments, which helped improving the quality of the paper.  ... 
doi:10.1155/2011/647858 pmid:21904542 pmcid:PMC3166724 fatcat:hqhesa5ncre6lnerbdtjcoenhy
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