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A Supervised Learning Approach for Robust Health Monitoring using Face Videos [article]

Mayank Gupta and Lingjun Chen and Denny Yu and Vaneet Aggarwal
2021 arXiv   pre-print
The proposed approach used facial recognition to detect the face in each frame of the video using facial landmarks, followed by supervised learning using deep neural networks to train the machine learning  ...  In this paper, we used a non-contact method that only requires face videos recorded using commercially-available webcams.  ...  Thus, this paper considers the use of a non-contact based approach where the passive video of the face can be used to estimate the health metrics.  ... 
arXiv:2102.00322v1 fatcat:fkdbudtqsfga7lz5vbe74pbf3m

Detection of Abnormal Behavior with Self-Supervised Gaze Estimation [article]

Suneung-Kim, Seong-Whan Lee
2021 arXiv   pre-print
In this paper, we present a single video conferencing solution using gaze estimation in preparation for these problems. Gaze is an important cue for the tasks such as analysis of human behavior.  ...  Our contribution is as follows. i) We find and apply the optimal network for the gaze estimation method and apply a self-supervised method to improve accuracy. ii) For anomaly detection, we present a new  ...  Methods for using image domains are used by pixel prediction approaches to learn embeddings.  ... 
arXiv:2107.06530v1 fatcat:5d5xvczlcnartfxsr2j54l2nui

The Way to my Heart is through Contrastive Learning: Remote Photoplethysmography from Unlabelled Video [article]

John Gideon, Simon Stent
2021 arXiv   pre-print
The ability to reliably estimate physiological signals from video is a powerful tool in low-cost, pre-clinical health monitoring.  ...  In addition, we incorporate a learned saliency resampling module into both our unsupervised approach and supervised baseline.  ...  We wish to thank Luke Fletcher for quickening our pulses at the right time, and the team at the Shapiro Cardiovascular Center at BWH from the bottom of (one of) our hearts.  ... 
arXiv:2111.09748v1 fatcat:b4cu75whefgj3cpc2jyr6fznku

Deep Learning Methods for Remote Heart Rate Measurement: A Review and Future Research Agenda

Chun-Hong Cheng, Kwan-Long Wong, Jing-Wei Chin, Tsz-Tai Chan, Richard H. Y. So
2021 Sensors  
While traditional HR monitors usually require contact with skin, remote photoplethysmography (rPPG) enables contactless HR monitoring by capturing subtle light changes of skin through a video camera.  ...  Heart rate (HR) is one of the essential vital signs used to indicate the physiological health of the human body.  ...  Acknowledgments: We are grateful for the support from the Innovation and Technology Commission of Hong Kong and Undergraduate Research Opportunities Program of the Hong Kong University of Science and Technology  ... 
doi:10.3390/s21186296 pmid:34577503 fatcat:hbs6lqqprvcpnio25i52jukn6m

Special issue on Assistive Computer Vision and Robotics - Part I

Giovanni Maria Farinella, Takeo Kanade, Marco Leo, Gerard G. Medioni, Mohan Trivedi
2016 Computer Vision and Image Understanding  
Martinel et al. presents a food recognition system exploiting a supervised learning algorithm useful to selects the optimal features for the problem.  ...  The paper "A Supervised Extreme Learning Committee for Food Recognition" by N.  ... 
doi:10.1016/j.cviu.2016.05.010 fatcat:tiiosvi5lbagnecmyekiz2p57m

MetaPhys: Few-Shot Adaptation for Non-Contact Physiological Measurement [article]

Xin Liu, Ziheng Jiang, Josh Fromm, Xuhai Xu, Shwetak Patel, Daniel McDuff
2021 arXiv   pre-print
In this paper, we present a novel meta-learning approach called MetaPhys for personalized video-based cardiac measurement for contactless pulse and heart rate monitoring.  ...  Our method uses only 18-seconds of video for customization and works effectively in both supervised and unsupervised manners.  ...  Robustness to Skin Type Our motivation for adopting a meta-learning approach is to improve generalization.  ... 
arXiv:2010.01773v3 fatcat:c3v3ca4vmvg7tdtjzttzrzrwze

Measurement of Physiological Factor like Heart Rate using Facial Video Analysis

Sanam Kazi, Mubasshira Mansuri, Nileshkumar Pandey, Altamash Khot
2020 International Journal of Computer Applications  
The method proposed not only uses the near-infrared channel which is designed originally to be hidden from users; but it also exploits the associated depth information for improved robustness to head pose  ...  Recently, several paper reported methods to measure heart rate remotely from face videos.  ...  The summarize result of the recently deployed monitoring approaches with a focus on automated detecting devices for monitoring health threats of aged patients who living alone at home.  ... 
doi:10.5120/ijca2020920264 fatcat:k3ad7yi2pvhgnmr65nscl4yxfu

Federated Remote Physiological Measurement with Imperfect Data [article]

Xin Liu, Mingchuan Zhang, Ziheng Jiang, Shwetak Patel, Daniel McDuff
2022 arXiv   pre-print
We develop the first mobile federated learning camera-based sensing system and show that it can perform competitively with traditional state-of-the-art supervised approaches.  ...  In health-related machine learning applications the ability to learn predictive models without data leaving a private device is attractive, especially when these data might contain features (e.g., photographs  ...  [3] proposed to use federated learning to train a supervised classification model for cardiac events.  ... 
arXiv:2203.05759v1 fatcat:7u2virztyzfczcbixkgyf26mou

Competency-Based Assessment for Clinical Supervisors: Design-Based Research on a Web-Delivered Program

Rachel Bacon, Lauren Therese Williams, Laurie Grealish, Maggie Jamieson
2015 JMIR Research Protocols  
A design-based research approach offers a practical process for such Web-based tool development, highlighting pedagogical barriers for planning purposes. (JMIR Res Protoc 2015;4(1):e26)  ...  The interviews were transcribed verbatim and thematic analysis conducted from a pedagogical perspective using van Manen's highlighting approach.  ...  Acknowledgments This research was made possible due to funding made available by Health Workforce Australia, an Australian Government Initiative, as part of the 2012 National Clinical Supervision Fellowship  ... 
doi:10.2196/resprot.3893 pmid:25803172 pmcid:PMC4376162 fatcat:4nwfpfjdhbezdkjfjogefjxyiq

Deep Video Anomaly Detection: Opportunities and Challenges [article]

Jing Ren, Feng Xia, Yemeng Liu, Ivan Lee
2021 arXiv   pre-print
In this paper, we present a comprehensive review of deep learning-based methods to detect the video anomalies from a new perspective.  ...  Moreover, we summarise the characteristics and technical problems in current deep learning methods for video anomaly detection.  ...  ACKNOWLEDGMENT The authors would like to thank Teng Guo, Shuo Yu, and Ke Sun for their help with the first draft of this paper.  ... 
arXiv:2110.05086v1 fatcat:5tpj4bqdd5csbp6efvvcqvufeq

Deep Motion Analysis for Epileptic Seizure Classification

David Ahmedt-Aristizabal, Kien Nguyen, Simon Denman, Sridha Sridharan, Sasha Dionisio, Clinton Fookes
2018 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)  
A video dataset from 12 patients with MTLE and 6 patients with ETLEin an Australian hospital has been collected for experiments.  ...  from facial and pose semiology using recorded videos.  ...  We demonstrated that it is feasible with deep learning algorithms to study standard 2D monitoring videos stored in the Epilepsy Monitoring Unit (EMU), which neurologists currently capture and use in their  ... 
doi:10.1109/embc.2018.8513031 pmid:30441151 fatcat:fg2b5xvwbvfijo5wtwdsbcmiki

Anomalous Human Activity Recognition in Surveillance Videos

2019 International journal of recent technology and engineering  
It is time-consuming to determine the activity from a surveillance video, due to its size, hence there is a need to compress the video using adaptive compression approaches.  ...  This paper is a survey on different approaches for Human Activity recognition which has utmost significance in pervasive computing due to its many applications in real-life.  ...  Hence there is a need for techniques that use deep learning for unsupervised and semi-supervised learning of anomaly detection systems.  ... 
doi:10.35940/ijrte.b1064.0782s719 fatcat:352q6ou655dr7oj2jtk2rl6eca

A Unique Framework for Contactless Estimation of Body Vital Signs using Facial Recognition

M. Bhanu Sridhar, Sai Himaja Kinthada, Bhargavi Marni
2021 International journal of computer science and mobile computing  
The main idea of our project is to design contactless technology for the support of patients who suffer from blood pressure disorders and coronary heart diseases using machine learning approach.  ...  The orientation of this paper is to monitor the blood pressure considering the facial changes and movements in a video to get rid of cuff-based measurement of blood pressure.  ...  This face detection algorithm is applied to each frame in the video and outputs a bounding box for each face it detects.  ... 
doi:10.47760/ijcsmc.2021.v10i12.002 fatcat:mtsrwgwzjjdf3dtwpiyipbs72y

AI-enabled remote monitoring of vital signs for COVID-19: methods, prospects and challenges

Honnesh Rohmetra, Navaneeth Raghunath, Pratik Narang, Vinay Chamola, Mohsen Guizani, Naga Rajiv Lakkaniga
2021 Computing  
Screening and monitoring the health of a large number of susceptible or infected individuals is a challenging task.  ...  Recent advances in Machine Learning (ML) and Deep Learning (DL) have strengthened the power of imaging techniques and can be used to remotely perform several tasks that previously required the physical  ...  Conclusion Use of Machine Learning and Deep Learning techniques has tremendous potential and advantages for use over the traditional used approaches for vital signs monitoring.  ... 
doi:10.1007/s00607-021-00937-7 fatcat:jf5gu4ocj5cs3eerzlya625duq

Worker's Helmet Recognition and Identity Recognition Based on Deep Learning

Jie Wang, Guangzu Zhu, Shiqi Wu, Chunshan Luo
2021 Open Journal of Modelling and Simulation  
For decades, safety has been a concern for the construction industry.  ...  Experiments show that the method has a high recognition accuracy rate, fast recognition speed, accurate recognition of workers and helmet detection, and solves the problem of poor supervision of real-name  ...  Therefore, there is a critical demand for on-site safety supervision to enhance construction sites safety.  ... 
doi:10.4236/ojmsi.2021.92009 fatcat:v7zeitnx5faafmgehuzcmkoive
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