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Baseball Player Behavior Classification System Using Long Short-Term Memory with Multimodal Features

Shih-Wei Sun, Ting-Chen Mou, Chih-Chieh Fang, Pao-Chi Chang, Kai-Lung Hua, Huang-Chia Shih
2019 Sensors  
camera and the statistical features extracted from the inertial sensors are used as features, and (iii) a deep learning-based scheme is proposed for training behavior classifiers.  ...  The contribution of this paper is threefold: (i) signals from a depth camera and from multiple inertial sensors are obtained and segmented, (ii) the time-variant skeleton vector projection from the depth  ...  The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.  ... 
doi:10.3390/s19061425 fatcat:dwb7acqdfzh77nbwqf7oosnzeq

Deep Learning-Based Violin Bowing Action Recognition

Shih-Wei Sun, Bao-Yun Liu, Pao-Chi Chang
2020 Sensors  
were trained using different modalities, to compensate for the strengths and weaknesses of each modality, based on deep learning methods with a decision-level fusion process.  ...  The contribution of this study is threefold: (1) a dataset comprising violin bowing actions was constructed from data captured by a depth camera and multiple inertial sensors; (2) data augmentation was  ...  The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.  ... 
doi:10.3390/s20205732 pmid:33050164 pmcid:PMC7601403 fatcat:idtd3kzhondszcelexpny4mlku

A survey of depth and inertial sensor fusion for human action recognition

Chen Chen, Roozbeh Jafari, Nasser Kehtarnavaz
2015 Multimedia tools and applications  
Bulling A, Blanke U, Schiele B (2014) A tutorial on human activity recognition using body-worn inertial sensors. ACM Comput Surv (CSUR) 46(3):33 9.  ...  A tutorial was presented in [8] covering a comprehensive discussion of designing and evaluating activity recognition systems using body-worn inertial sensors.  ... 
doi:10.1007/s11042-015-3177-1 fatcat:3m6xzmkpszbnjbp643wgnh5ru4

CNN based Multistage Gated Average Fusion (MGAF) for Human Action Recognition Using Depth and Inertial Sensors [article]

Zeeshan Ahmad, Naimul khan
2020 arXiv   pre-print
Experiments on three publicly available multimodal HAR datasets demonstrate that the proposed MGAF outperforms the previous state of the art fusion methods for depth-inertial HAR in terms of recognition  ...  At the input of the proposed MGAF, we transform the depth and inertial sensor data into depth images called sequential front view images (SFI) and signal images (SI) respectively.  ...  Hence the sensor is worn only on two positions for collecting data of 27 actions which is insufficient to capture all the dependencies and characteristics of data.  ... 
arXiv:2010.16073v1 fatcat:ig45mb2m7nggdplu5ejflsawc4

Wearable Sensors for Monitoring of Cigarette Smoking in Free-Living: A Systematic Review

Masudul H. Imtiaz, Raul I. Ramos-Garcia, Shashank Wattal, Stephen Tiffany, Edward Sazonov
2019 Sensors  
to cigarette smoking, in order to: (1) Investigate the behavioral and physiological manifestations of cigarette smoking targeted by wearable sensors for smoking detection; (2) explore sensor modalities  ...  The review identified five specific smoking manifestations targeted by sensors. The results suggested that no system reached 100% accuracy in the detection or evaluation of smoking-related features.  ...  Conflicts of Interest: Authors declare no financial conflict of interest. The content is solely the responsibility of the authors and does not necessarily represent official views of NIH.  ... 
doi:10.3390/s19214678 pmid:31661856 pmcid:PMC6864810 fatcat:tn7nclo2gjh4vgnum4bww4p44u

Wearable Devices for Assessment of Tremor

Basilio Vescio, Andrea Quattrone, Rita Nisticò, Marianna Crasà, Aldo Quattrone
2021 Frontiers in Neurology  
To date, electromyography (EMG) is the gold standard for the analysis and diagnosis of tremors.  ...  Such devices have proven to be useful for monitoring the efficacy of therapies or even aiding in differential diagnosis.  ...  RN, and MC: contribution to the writing of all sections. AlQ and RN: critical review of the manuscript. All authors contributed to manuscript revision and read and approved the submitted version.  ... 
doi:10.3389/fneur.2021.680011 pmid:34177785 pmcid:PMC8226078 fatcat:zbnvdcuf4nesragls5wmp4bgxu

Wear is Your Mobile? Investigating Phone Carrying and Use Habits with a Wearable Device

Kristof Van Laerhoven, Marko Borazio, Jan Hendrik Burdinski
2015 Frontiers in ICT  
We explore the trade-offs for both device types in a study that compares their sensor data and that explicitly examines how often these devices are being worn by the user.  ...  Mobile phones have become generic computing platforms, and even though they might not always be with the user, they are increasingly easy to develop for and have an unmatched variety of on-board sensors  ...  Acknowledgments We thank all study participants for their commitment in wearing the wrist-worn activity logger and using the Android app for at least 2 weeks.  ... 
doi:10.3389/fict.2015.00010 fatcat:es7edwakxje4zdukyvrz5tbrom

Activity Recognition for Ambient Assisted Living with Videos, Inertial Units and Ambient Sensors

Caetano Mazzoni Ranieri, Scott MacLeod, Mauro Dragone, Patricia Amancio Vargas, Roseli Aparecida Francelin Romero
2021 Sensors  
The second contribution is the proposal of a Deep Learning (DL) framework, which provides multimodal activity recognition based on videos, inertial sensors and ambient sensors from the smart home, on their  ...  based on videos and inertial sensors, providing a comparative analysis between the results on the two datasets considered.  ...  The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.  ... 
doi:10.3390/s21030768 pmid:33498829 fatcat:ocw65n4utjccjot554snom2vom

Interactive wearable systems for upper body rehabilitation: a systematic review

Qi Wang, Panos Markopoulos, Bin Yu, Wei Chen, Annick Timmermans
2017 Journal of NeuroEngineering and Rehabilitation  
The results indicated that accelerometers and IMUs are the most frequently used sensors, in most cases attached to the body through ad hoc contraptions for the purpose of improving range of motion and  ...  The development of interactive rehabilitation technologies which rely on wearable-sensing for upper body rehabilitation is attracting increasing research interest.  ...  Availability of data and materials Full search strategy available from the authors on request. Consent for publication All authors read and approved the manuscript for publication.  ... 
doi:10.1186/s12984-017-0229-y pmid:28284228 pmcid:PMC5346195 fatcat:2us5ekdwkffu5etutqxjvmh5sq

Signal processing challenges in cognitive assistive technology [Exploratory DSP]

M.R. Lightner, D. Erdogmus
2008 IEEE Signal Processing Magazine  
Similar arguments can be made for body-worn or otherwise carried (on a cane) inertial sensors. Developing new signal and image processing techniques is often driven by specific problem classes.  ...  In order to get more detailed activity information, these sensors are not sufficient, and body-worn inertial sensors are necessary. This approach has attracted considerable interest.  ... 
doi:10.1109/msp.2008.928315 fatcat:2oqwti6j6negfnyndc45yvioji

Datasets on object manipulation and interaction: a survey [article]

Yongqiang Huang, Yu Sun
2016 arXiv   pre-print
We report on modalities, activities, and annotations for each individual dataset and give our view on its use for object manipulation. We also compare the datasets and summarize them.  ...  A dataset is crucial for model learning and evaluation. Choosing the right dataset to use or making a new dataset requires the knowledge of those that are available.  ...  We reported on each dataset individually, gave our view on the relation between each dataset and object manipulation, and compared and summarized all of them together.  ... 
arXiv:1607.00442v1 fatcat:6islnas4bzenlctmgcdzl4qcqy

Combining wearable and environmental sensing into an unobtrusive tool for long-term sleep studies

Marko Borazio, Kristof Van Laerhoven
2012 Proceedings of the 2nd ACM SIGHIT symposium on International health informatics - IHI '12  
Inertial, ambient light, and time data tracked from a wrist-worn sensor, and additional night vision footage is used for later expert inspection.  ...  An evaluation on over 4400 hours of data from a focus group of test subjects demonstrates a high recall night segment detection, obtaining an average of 94%.  ...  ACKNOWLEDGEMENTS The authors would like to thank the staff at the collaborating sleep laboratories, as well as the anonymous volunteers that were kind enough to wear our sensor and deploy the camera at  ... 
doi:10.1145/2110363.2110375 dblp:conf/ihi/BorazioL12 fatcat:jccv33mkfff3lhhiuafvqflg6e

Modeling and simulation of sensor orientation errors in garments

Holger Harms, Oliver Amft, Gerhard Tröster
2009 Proceedings of the 4th International ICST Conference on Body Area Networks  
The feasibility of our body model and the garment-attached sensor deviation was validated in experimental data.  ...  A kinematic model of the human upper-body was developed to simulate upper limb postures and the output of virtual 3D acceleration sensors.  ...  An inertial unit containing one of each sensor modality was simulated at the upper arm and one at the forearm.  ... 
doi:10.4108/icst.bodynets2009.5977 dblp:conf/bodynets/HarmsAT09 fatcat:7bulitphnjh6jakdfbnim5anpm

Gesture spotting with body-worn inertial sensors to detect user activities

Holger Junker, Oliver Amft, Paul Lukowicz, Gerhard Tröster
2008 Pattern Recognition  
We present a method for spotting sporadically occurring gestures in a continuous data stream from body-worn inertial sensors.  ...  Our method is based on a natural partitioning of continuous sensor signals and uses a two-stage approach for the spotting task.  ...  Acknowledgement This work was partly supported by the Swiss State Secretariat for Education and Research (SER).  ... 
doi:10.1016/j.patcog.2007.11.016 fatcat:viabeqo6yzgcvegnpi6huq57li

Recognising complex activities with histograms of relative tracklets

Sebastian Stein, Stephen J. McKenna
2017 Computer Vision and Image Understanding  
One approach to the recognition of complex human activities is to use feature descriptors that encode visual interactions by describing properties of local visual features with respect to trajectories  ...  combining features from these sensor modalities.  ...  Acknowledgements The authors would like to thank Jianguo Zhang and Ruixuan Wang for valuable feedback on drafts of this paper. This research was funded by RCUK grants EP/G0 6 6019/1 and EP/K037293/1 .  ... 
doi:10.1016/j.cviu.2016.08.012 fatcat:bd43ecgf2jfxhlalsixz74seum
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