Proceedings of the ... ACM International Conference on Ubiquitous Computing . UbiComp (Conference)最新文献_第2页

A Practical Approach for Recognizing Eating Moments with Wrist-Mounted Inertial Sensing. 利用腕式惯性传感器识别进食时刻的实用方法

Proceedings of the ... ACM International Conference on Ubiquitous Computing . UbiComp (Conference) Pub Date : 2015-09-01 DOI: 10.1145/2750858.2807545

Edison Thomaz, Irfan Essa, Gregory D Abowd

{"title":"A Practical Approach for Recognizing Eating Moments with Wrist-Mounted Inertial Sensing.","authors":"Edison Thomaz, Irfan Essa, Gregory D Abowd","doi":"10.1145/2750858.2807545","DOIUrl":"10.1145/2750858.2807545","url":null,"abstract":"Recognizing when eating activities take place is one of the key challenges in automated food intake monitoring. Despite progress over the years, most proposed approaches have been largely impractical for everyday usage, requiring multiple on-body sensors or specialized devices such as neck collars for swallow detection. In this paper, we describe the implementation and evaluation of an approach for inferring eating moments based on 3-axis accelerometry collected with a popular off-the-shelf smartwatch. Trained with data collected in a semi-controlled laboratory setting with 20 subjects, our system recognized eating moments in two free-living condition studies (7 participants, 1 day; 1 participant, 31 days), with F-scores of 76.1% (66.7% Precision, 88.8% Recall), and 71.3% (65.2% Precision, 78.6% Recall). This work represents a contribution towards the implementation of a practical, automated system for everyday food intake monitoring, with applicability in areas ranging from health research and food journaling.","PeriodicalId":90688,"journal":{"name":"Proceedings of the ... ACM International Conference on Ubiquitous Computing . UbiComp (Conference)","volume":"2015 ","pages":"1029-1040"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5839104/pdf/nihms728790.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35898510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MobileRF: A Robust Device-Free Tracking System Based On a Hybrid Neural Network HMM Classifier. 基于混合神经网络HMM分类器的鲁棒无设备跟踪系统。

Proceedings of the ... ACM International Conference on Ubiquitous Computing . UbiComp (Conference) Pub Date : 2014-01-01 DOI: 10.1145/2632048.2632097

Anindya S Paul, Eric A Wan, Fatema Adenwala, Erich Schafermeyer, Nick Preiser, Jeffrey Kaye, Peter G Jacobs

{"title":"MobileRF: A Robust Device-Free Tracking System Based On a Hybrid Neural Network HMM Classifier.","authors":"Anindya S Paul, Eric A Wan, Fatema Adenwala, Erich Schafermeyer, Nick Preiser, Jeffrey Kaye, Peter G Jacobs","doi":"10.1145/2632048.2632097","DOIUrl":"https://doi.org/10.1145/2632048.2632097","url":null,"abstract":"We present a device-free indoor tracking system that uses received signal strength (RSS) from radio frequency (RF) transceivers to estimate the location of a person. While many RSS-based tracking systems use a body-worn device or tag, this approach requires no such tag. The approach is based on the key principle that RF signals between wall-mounted transceivers reflect and absorb differently depending on a person's movement within their home. A hierarchical neural network hidden Markov model (NN-HMM) classifier estimates both movement patterns and stand vs. walk conditions to perform tracking accurately. The algorithm and features used are specifically robust to changes in RSS mean shifts in the environment over time allowing for greater than 90% region level classification accuracy over an extended testing period. In addition to tracking, the system also estimates the number of people in different regions. It is currently being developed to support independent living and long-term monitoring of seniors.","PeriodicalId":90688,"journal":{"name":"Proceedings of the ... ACM International Conference on Ubiquitous Computing . UbiComp (Conference)","volume":"2014 ","pages":"159-170"},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/2632048.2632097","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32937685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 28

Multi-sensor physical activity recognition in free-living. 自由生活中的多传感器身体活动识别。

Proceedings of the ... ACM International Conference on Ubiquitous Computing . UbiComp (Conference) Pub Date : 2014-01-01 DOI: 10.1145/2638728.2641673

Katherine Ellis, Suneeta Godbole, Jacqueline Kerr, Gert Lanckriet

引用次数: 43

Assessing the Availability of Users to Engage in Just-in-Time Intervention in the Natural Environment. 评估用户在自然环境中参与即时干预的可用性。

Proceedings of the ... ACM International Conference on Ubiquitous Computing . UbiComp (Conference) Pub Date : 2014-01-01 DOI: 10.1145/2632048.2636082

Hillol Sarker, Moushumi Sharmin, Amin Ahsan Ali, Md Mahbubur Rahman, Rummana Bari, Syed Monowar Hossain, Santosh Kumar

{"title":"Assessing the Availability of Users to Engage in Just-in-Time Intervention in the Natural Environment.","authors":"Hillol Sarker, Moushumi Sharmin, Amin Ahsan Ali, Md Mahbubur Rahman, Rummana Bari, Syed Monowar Hossain, Santosh Kumar","doi":"10.1145/2632048.2636082","DOIUrl":"https://doi.org/10.1145/2632048.2636082","url":null,"abstract":"Wearable wireless sensors for health monitoring are enabling the design and delivery of just-in-time interventions (JITI). Critical to the success of JITI is to time its delivery so that the user is available to be engaged. We take a first step in modeling users' availability by analyzing 2,064 hours of physiological sensor data and 2,717 self-reports collected from 30 participants in a week-long field study. We use delay in responding to a prompt to objectively measure availability. We compute 99 features and identify 30 as most discriminating to train a machine learning model for predicting availability. We find that location, affect, activity type, stress, time, and day of the week, play significant roles in predicting availability. We find that users are least available at work and during driving, and most available when walking outside. Our model finally achieves an accuracy of 74.7% in 10-fold cross-validation and 77.9% with leave-one-subject-out.","PeriodicalId":90688,"journal":{"name":"Proceedings of the ... ACM International Conference on Ubiquitous Computing . UbiComp (Conference)","volume":"2014 ","pages":"909-920"},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/2632048.2636082","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33032762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 112

Passive and In-situ Assessment of Mental and Physical Well-being using Mobile Sensors. 利用移动传感器对身心健康进行被动和原位评估。

Proceedings of the ... ACM International Conference on Ubiquitous Computing . UbiComp (Conference) Pub Date : 2011-01-01 DOI: 10.1145/2030112.2030164

Mashfiqui Rabbi, Shahid Ali, Tanzeem Choudhury, Ethan Berke

{"title":"Passive and In-situ Assessment of Mental and Physical Well-being using Mobile Sensors.","authors":"Mashfiqui Rabbi, Shahid Ali, Tanzeem Choudhury, Ethan Berke","doi":"10.1145/2030112.2030164","DOIUrl":"https://doi.org/10.1145/2030112.2030164","url":null,"abstract":"The idea of continuously monitoring well-being using mobile-sensing systems is gaining popularity. In-situ measurement of human behavior has the potential to overcome the short comings of gold-standard surveys that have been used for decades by the medical community. However, current sensing systems have mainly focused on tracking physical health; some have approximated aspects of mental health based on proximity measurements but have not been compared against medically accepted screening instruments. In this paper, we show the feasibility of a multi-modal mobile sensing system to simultaneously assess mental and physical health. By continuously capturing fine grained motion and privacy-sensitive audio data, we are able to derive different metrics that reflect the results of commonly used surveys for assessing well-being by the medical community. In addition, we present a case study that highlights how errors in assessment due to the subjective nature of the responses could potentially be avoided by continuous sensing and inference of social interactions and physical activities.","PeriodicalId":90688,"journal":{"name":"Proceedings of the ... ACM International Conference on Ubiquitous Computing . UbiComp (Conference)","volume":"2011 ","pages":"385-394"},"PeriodicalIF":0.0,"publicationDate":"2011-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/2030112.2030164","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32721225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 235

Using Wearable Activity Type Detection to Improve Physical Activity Energy Expenditure Estimation. 利用可穿戴活动类型检测改进体育活动能量消耗估算。

Proceedings of the ... ACM International Conference on Ubiquitous Computing . UbiComp (Conference) Pub Date : 2010-09-01 DOI: 10.1145/1864349.1864396

Fahd Albinali, Stephen S Intille, William Haskell, Mary Rosenberger

引用次数: 0