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Using wearable sensors and real time inference to understand human recall of routine activities
2008
Proceedings of the 10th international conference on Ubiquitous computing - UbiComp '08
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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
2011
2011 International Conference on Internet of Things and 4th International Conference on Cyber, Physical and Social Computing
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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
2013
Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication - UbiComp '13 Adjunct
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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
2021
IEEE Access
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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
2011
Sensors
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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
2012
World wide web (Bussum)
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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?
2017
Evidence-Based Mental Health
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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
2020
Future Internet
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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
2015
Proceedings of the 13th Annual International Conference on Mobile Systems, Applications, and Services - MobiSys '15
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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
2009
Journal of Ambient Intelligence and Smart Environments
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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
2021
Sensors
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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]
2022
arXiv
pre-print
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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
2021
International Journal of Alzheimer's Disease
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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
2008
IEEE pervasive computing
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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
2016
2016 IEEE 29th International Symposium on Computer-Based Medical Systems (CBMS)
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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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