Activity and Location Recognition Using Wearable Sensors
IEEE Pervasive Computing
Activity Recognition and Monitoring Using Multiple Sensors on Different Body Positions
BSN '06 Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Shakra: tracking and sharing daily activity levels with unaugmented mobile phones
Mobile Networks and Applications
The Mobile Sensing Platform: An Embedded Activity Recognition System
IEEE Pervasive Computing
Proceedings of the 6th ACM conference on Embedded network sensor systems
An activity recognition system for mobile phones
Mobile Networks and Applications
SmartBuckle: human activity recognition using a 3-axis accelerometer and a wearable camera
Proceedings of the 2nd International Workshop on Systems and Networking Support for Health Care and Assisted Living Environments
ISWC '07 Proceedings of the 2007 11th IEEE International Symposium on Wearable Computers
Activity Recognition from Accelerometer Data on a Mobile Phone
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part II: Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living
Activity recognition from accelerometer data
IAAI'05 Proceedings of the 17th conference on Innovative applications of artificial intelligence - Volume 3
IMCE '09 Proceedings of the 1st international workshop on Interactive multimedia for consumer electronics
A practical approach to recognizing physical activities
PERVASIVE'06 Proceedings of the 4th international conference on Pervasive Computing
Activity classification using realistic data from wearable sensors
IEEE Transactions on Information Technology in Biomedicine
Activity recognition using hierarchical hidden markov models on a smartphone with 3D accelerometer
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part I
Physical activity monitoring with mobile phones
ICOST'11 Proceedings of the 9th international conference on Toward useful services for elderly and people with disabilities: smart homes and health telematics
A rotation based method for detecting on-body positions of mobile devices
Proceedings of the 13th international conference on Ubiquitous computing
Using active learning to allow activity recognition on a large scale
AmI'11 Proceedings of the Second international conference on Ambient Intelligence
Prioritizing data in emergency response based on context, message content and role
Proceedings of the 1st International Conference on Wireless Technologies for Humanitarian Relief
A review on vision techniques applied to Human Behaviour Analysis for Ambient-Assisted Living
Expert Systems with Applications: An International Journal
ACE: exploiting correlation for energy-efficient and continuous context sensing
Proceedings of the 10th international conference on Mobile systems, applications, and services
Geo-fencing: geographical-fencing based energy-aware proactive framework for mobile devices
Proceedings of the 2012 IEEE 20th International Workshop on Quality of Service
Energy efficient activity recognition based on low resolution accelerometer in smart phones
GPC'12 Proceedings of the 7th international conference on Advances in Grid and Pervasive Computing
Mining complex activities in the wild via a single smartphone accelerometer
Proceedings of the Sixth International Workshop on Knowledge Discovery from Sensor Data
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
Applications of mobile activity recognition
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
Towards the detection of unusual temporal events during activities using HMMs
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
Context-aware mobile music recommendation for daily activities
Proceedings of the 20th ACM international conference on Multimedia
A smartphone-based fall detection system
Pervasive and Mobile Computing
Online activity recognition using evolving classifiers
Expert Systems with Applications: An International Journal
Mobile activity recognition using ubiquitous data stream mining
DaWaK'12 Proceedings of the 14th international conference on Data Warehousing and Knowledge Discovery
Offline and online activity recognition on mobile devices using accelerometer data
IWAAL'12 Proceedings of the 4th international conference on Ambient Assisted Living and Home Care
IWAAL'12 Proceedings of the 4th international conference on Ambient Assisted Living and Home Care
A survey on smartphone-based systems for opportunistic user context recognition
ACM Computing Surveys (CSUR)
Walkie-Markie: indoor pathway mapping made easy
nsdi'13 Proceedings of the 10th USENIX conference on Networked Systems Design and Implementation
Walk detection and step counting on unconstrained smartphones
Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing
Classifying social actions with a single accelerometer
Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing
Stop questioning me!: towards optimizing user involvement during data collection on mobile devices
Proceedings of the 15th international conference on Human-computer interaction with mobile devices and services
WagTag: a dog collar accessory for monitoring canine activity levels
Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication
Sensor requirements for activity recognition on smart watches
Proceedings of the 6th International Conference on PErvasive Technologies Related to Assistive Environments
GaitTrack: Health Monitoring of Body Motion from Spatio-Temporal Parameters of Simple Smart Phones
Proceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical Informatics
Time series representation: a random shifting perspective
WAIM'13 Proceedings of the 14th international conference on Web-Age Information Management
Reduce the Number of Sensors: Sensing Acoustic Emissions to Estimate Appliance Energy Usage
Proceedings of the 5th ACM Workshop on Embedded Systems For Energy-Efficient Buildings
Bootstrapping activity modeling for ambient assisted living
ICSH'13 Proceedings of the 2013 international conference on Smart Health
Proceedings of International Conference on Advances in Mobile Computing & Multimedia
jActivity: supporting mobile web developers with HTML5/JavaScript based human activity recognition
Proceedings of the 12th International Conference on Mobile and Ubiquitous Multimedia
Learning a taxonomy of predefined and discovered activity patterns
Journal of Ambient Intelligence and Smart Environments
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Mobile devices are becoming increasingly sophisticated and the latest generation of smart cell phones now incorporates many diverse and powerful sensors. These sensors include GPS sensors, vision sensors (i.e., cameras), audio sensors (i.e., microphones), light sensors, temperature sensors, direction sensors (i.e., magnetic compasses), and acceleration sensors (i.e., accelerometers). The availability of these sensors in mass-marketed communication devices creates exciting new opportunities for data mining and data mining applications. In this paper we describe and evaluate a system that uses phone-based accelerometers to perform activity recognition, a task which involves identifying the physical activity a user is performing. To implement our system we collected labeled accelerometer data from twenty-nine users as they performed daily activities such as walking, jogging, climbing stairs, sitting, and standing, and then aggregated this time series data into examples that summarize the user activity over 10- second intervals. We then used the resulting training data to induce a predictive model for activity recognition. This work is significant because the activity recognition model permits us to gain useful knowledge about the habits of millions of users passively---just by having them carry cell phones in their pockets. Our work has a wide range of applications, including automatic customization of the mobile device's behavior based upon a user's activity (e.g., sending calls directly to voicemail if a user is jogging) and generating a daily/weekly activity profile to determine if a user (perhaps an obese child) is performing a healthy amount of exercise.