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Using wearable sensors and real time inference to understand human recall of routine activities

Predrag Klasnja, Beverly L. Harrison, Louis LeGrand, Anthony LaMarca, Jon Froehlich, Scott E. Hudson
2008 Proceedings of the 10th international conference on Ubiquitous computing - UbiComp '08  
We used a novel wearable sensor platform that runs a real time activity inference engine to collect in situ ground truth.  ...  We report on a study investigating the effect of sampling frequency of self-reports of two routine activities (sitting and walking) on recall accuracy and annoyance.  ...  Participants' responses are compared to ground truth data obtained from wearable sensors.  ... 
doi:10.1145/1409635.1409656 dblp:conf/huc/KlasnjaHLLFH08 fatcat:umkx7mbvyjfflmhnlb3kj72gju

Living with Internet of Things: The Emergence of Embedded Intelligence

Bin Guo, Daqing Zhang, Zhu Wang
2011 2011 International Conference on Internet of Things and 4th International Conference on Cyber, Physical and Social Computing  
With the development of sensing, wireless communication, and Internet technologies, we are now living in a world that is filled with various smart thingsthe Internet of Things.  ...  The paper discusses the research history, characteristics, general architecture, major applications, and research issues of EI.  ...  MIT's Real Time Rome project uses aggregated data from mobile phones, buses and taxies in Rome to better understand urban dynamics in real-time.  ... 
doi:10.1109/ithings/cpscom.2011.11 dblp:conf/ithings/GuoZW11 fatcat:fdgg26mbenci7hls7awyprt5ba

Practical food journaling

Edison Thomaz
2013 Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication - UbiComp '13 Adjunct  
technologies techniques and evaluate it using cross-fold validation. over the last decade, sensors have been employed to automatically infer many aspects of human activity Routine characterizes  ...  human life, and these routines [9, 11].  ... 
doi:10.1145/2494091.2501089 dblp:conf/huc/Thomaz13 fatcat:evuy2bvh5jfmrf3imsdikzgpcq

Fusing Ambient and Mobile Sensor Features Into a Behaviorome for Predicting Clinical Health Scores

Diane J Cook, Maureen Schmitter-Edgecombe
2021 IEEE Access  
We also observe an improvement in predictive performance when multiple sensor modalities are used and when joint inference is employed.  ...  In this study, we analyze this relationship by building a behaviorome, or set of digital behavior markers, from a fusion of data collected from ambient and wearable sensors.  ...  ACKNOWLEDGMENT The authors would like to thank members of the WSU CASAS lab for their assistance in this study.  ... 
doi:10.1109/access.2021.3076362 pmid:34017671 pmcid:PMC8132971 fatcat:2wlfbexozjbdrhgn2om53aszsy

Towards Smart Homes Using Low Level Sensory Data

Asad Masood Khattak, Phan Tran Ho Truc, Le Xuan Hung, La The Vinh, Viet-Hung Dang, Donghai Guan, Zeeshan Pervez, Manhyung Han, Sungyoung Lee, Young-Koo Lee
2011 Sensors  
We focus on activity recognition using video-based, wearable sensor-based, and location-based activity recognition engines and then use intelligent processing to analyze the context of the activities performed  ...  To provide spontaneous and robust healthcare services, knowledge of a patient's real-time daily life activities is required.  ...  The above discussed systems do not use real-time activities or only use one type of real-time activity to generate reminders or make decisions.  ... 
doi:10.3390/s111211581 pmid:22247682 pmcid:PMC3251999 fatcat:o7pyj6qwt5e5lgnryziegyj3oy

From the internet of things to embedded intelligence

Bin Guo, Daqing Zhang, Zhiwen Yu, Yunji Liang, Zhu Wang, Xingshe Zhou
2012 World wide web (Bussum)  
The Internet of Things (IoT) represents the future technology trend of sensing, computing, and communication.  ...  In this paper, however, we attempt to enhance the IoT with intelligence and awareness.  ...  The Real Time Rome project of MIT uses aggregated data from buses and taxies to better understand urban dynamics in real-time [9] . Liu et al.  ... 
doi:10.1007/s11280-012-0188-y fatcat:ocyb57s5mvhmtep5ezcf7pbcku

The promise of digital mood tracking technologies: are we heading on the right track?

Gin S Malhi, Amber Hamilton, Grace Morris, Zola Mannie, Pritha Das, Tim Outhred
2017 Evidence-Based Mental Health  
However, these methods are often inaccurate due to recall bias and compliance issues, and are limited in their capacity to collect and process data over long periods of time.  ...  The growing understanding that mood disorders are dynamic in nature and fluctuate over variable epochs of time has compelled researchers to develop innovative methods of monitoring mood.  ...  It has opened a window to investigate real-time human behaviour with unprecedented granularity.  ... 
doi:10.1136/eb-2017-102757 pmid:28855245 fatcat:lnz4uawutfeihdwgccafukcgba

RFID RSS Fingerprinting System for Wearable Human Activity Recognition

Shuaieb, Oguntala, AlAbdullah, Obeidat, Asif, Abd-Alhameed, Bin-Melha, Kara-Zaïtri
2020 Future Internet  
The mapping of the analysed data against a set of reference position datasets is used to accurately track the vertical and horizontal positioning of a patient within a confined space in real-time.  ...  However, the accuracy of the activity recognition algorithm performs below the threshold performance for walking and standing, which is due to similarities in the target height, weight and body density  ...  In these studies, the locomotion pattern is used in finding the routine cluster at different time intervals within the room to understand associated human reactions and behaviours [14, 15] .  ... 
doi:10.3390/fi12020033 fatcat:gpj6bjlzojenzfcrphsczg6aga

ZOE

Nicholas D. Lane, Petko Georgiev, Cecilia Mascolo, Ying Gao
2015 Proceedings of the 13th Annual International Conference on Mobile Systems, Applications, and Services - MobiSys '15  
Towards building the critical mass of understanding and experience necessary to tackle such questions, we have designed and implemented ZOE -a match-box sized (49g) collar-or lapel-worn sensor that pushes  ...  First, ZOE aims to perform multiple deep sensor inferences that span key aspects of everyday life (viz. personal, social and place information) on continuously sensed data; while also offering this data  ...  We would also like to thank the anonymous reviewers and our shepherd, Jeremy Gummeson, for helping us improve the paper.  ... 
doi:10.1145/2742647.2742672 dblp:conf/mobisys/LaneGMG15 fatcat:wkfkgrccbzhohf4z6hvyr3z7qq

Wearable EOG goggles: Seamless sensing and context-awareness in everyday environments

Andreas Bulling, Daniel Roggen, Gerhard Tröster
2009 Journal of Ambient Intelligence and Smart Environments  
This self-contained wearable device consists of goggles with dry electrodes integrated into the frame and a small pocket-worn component with a DSP for real-time EOG signal processing.  ...  In two case studies, we demonstrate that EOG is a suitable measurement technique for the recognition of reading activity and eyebased human-computer interaction.  ...  The device allows for unobtrusive recordings of EOG signals and their real-time processing and enables online inference of activity and context.  ... 
doi:10.3233/ais-2009-0020 fatcat:mw46qmepqvbcriltnb3weu2n44

Review of Wearable Devices and Data Collection Considerations for Connected Health

Vini Vijayan, James Connolly, Joan Condell, Nigel McKelvey, Philip Gardiner
2021 Sensors  
This paper discusses current techniques used to track and record various human body movements, as well as techniques used to measure activity and sleep from long-term data collected by wearable technology  ...  Wearable sensors can typically assess and quantify the wearer's physiology and are commonly employed for human activity detection and quantified self-assessment.  ...  Acknowledgments: Thank you to the supervisory team. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/s21165589 pmid:34451032 pmcid:PMC8402237 fatcat:qubolay6wjb35orvkwtunwz7e4

A Survey of Passive Sensing in the Workplace [article]

Subigya Nepal, Gonzalo J. Martinez, Shayan Mirjafari, Koustuv Saha, Vedant Das Swain, Xuhai Xu, Pino G. Audia, Munmun De Choudhury, Anind K. Dey, Aaron Striegel, Andrew T. Campbell
2022 arXiv   pre-print
In this article, we survey recent research on the use of passive sensing in the workplace to assess wellbeing and productivity of the workforce.  ...  New passive sensing technology is emerging capable of assessing human behavior with the goal of promoting better cognitive and physical capabilities at work.  ...  Many of the papers discussed are still in an exploratory phase, where datadriven research is advancing what sensor streams and models can best capture dimensions of the workplace and workforce.  ... 
arXiv:2201.03074v1 fatcat:6xupuqnd7rgezbiopvxjg4dhey

Current State of Non-wearable Sensor Technologies for Monitoring Activity Patterns to Detect Symptoms of Mild Cognitive Impairment to Alzheimer's Disease

Rajaram Narasimhan, Muthukumaran G., Charles McGlade, Francesco Panza
2021 International Journal of Alzheimer's Disease  
Non-wearable sensors are less intrusive and can monitor activities at naturalistic environment with no interference to an individual's daily routines.  ...  This review seeks to answer the following questions: (1) What is the evidence for use of non-wearable sensor technologies in early detection of MCI/AD utilizing daily activity data in an unobtrusive manner  ...  mean age: NS; duration: 6 months Daily routine pattern RNN Expressed human routine as a time series inference based on the raw data stream from sensors.  ... 
doi:10.1155/2021/2679398 pmid:33628484 pmcid:PMC7889365 fatcat:wrfbr62qbzhslfki7hocyihi4a

The Mobile Sensing Platform: An Embedded Activity Recognition System

Tanzeem Choudhury, Gaetano Borriello, Sunny Consolvo, Dirk Haehnel, Beverly Harrison, Bruce Hemingway, Jeffrey Hightower, Predrag "Pedja" Klasnja, Karl Koscher, Anthony LaMarca, James A. Landay, Louis LeGrand (+4 others)
2008 IEEE pervasive computing  
The US National Science Foundation partially supported this work under grant IIS 0433637.  ...  To better understand the usefulness of different sensor modalities in inferring human activities, we designed and built a multimodal sensor board that simultaneously captured data from seven different  ...  So, for example, a fitness application could use real-time activity information to encourage users to perform opportunistic activities.  ... 
doi:10.1109/mprv.2008.39 fatcat:t4p2hdgoujcspk5gn5a3uwijwa

Towards Situation-Aware Mobile Applications in Mental Health

Ariel S. Teles, Artur Rocha, Francisco J. Silva, Joao Correia Lopes, Donal OSullivan, Pepijn Van de Ven, Markus Endler
2016 2016 IEEE 29th International Symposium on Computer-Based Medical Systems (CBMS)  
This work describes SituMan (Situation Manager), a mobile system that makes use of the sensors commonly included in most mobile platforms and a fuzzy inference engine to attempt to infer user context and  ...  EMA has been used in psychotherapy to minimize the effects of recall bias in the assessment of patient mood, as well as in the recollection of other experiences and behaviours.  ...  ACKNOWLEDGEMENTS The authors would like to thank European Community's Seventh Framework Programme, as well as FAPEMA and CNPQ (Brazilian research funding agencies) for the financial support of this work  ... 
doi:10.1109/cbms.2016.7 dblp:conf/cbms/TelesRSLOVE16 fatcat:vyelu2c54rcjvpm76wgyiawgge
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