Algorithms on strings, trees, and sequences: computer science and computational biology
Algorithms on strings, trees, and sequences: computer science and computational biology
A State-Based Approach to the Representation and Recognition of Gesture
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-Time American Sign Language Recognition Using Desk and Wearable Computer Based Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
Parametric Hidden Markov Models for Gesture Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
An HMM-Based Threshold Model Approach for Gesture Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Flexible pattern matching in strings: practical on-line search algorithms for texts and biological sequences
An Online Algorithm for Segmenting Time Series
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Simple and Practical Sequence Nearest Neighbors with Block Operations
CPM '02 Proceedings of the 13th Annual Symposium on Combinatorial Pattern Matching
WearNET: A Distributed Multi-sensor System for Context Aware Wearables
UbiComp '02 Proceedings of the 4th international conference on Ubiquitous Computing
Context Awareness by Analyzing Accelerometer Data
ISWC '00 Proceedings of the 4th IEEE International Symposium on Wearable Computers
An HMM-Based Approach for Gesture Segmentation and Recognition
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 3
A symbolic representation of time series, with implications for streaming algorithms
DMKD '03 Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery
Implementation and Evaluation of a Low-Power Sound-Based User Activity Recognition System
ISWC '04 Proceedings of the Eighth International Symposium on Wearable Computers
Continuous Recognition of Arm Activities With Body-Worn Inertial Sensors
ISWC '04 Proceedings of the Eighth International Symposium on Wearable Computers
Toward wearable social networking with iBand
CHI '05 Extended Abstracts on Human Factors in Computing Systems
Recognition and reproduction of gestures using a probabilistic framework combining PCA, ICA and HMM
ICML '05 Proceedings of the 22nd international conference on Machine learning
Using Ultrasonic Hand Tracking to Augment Motion Analysis Based Recognition of Manipulative Gestures
ISWC '05 Proceedings of the Ninth IEEE International Symposium on Wearable Computers
Multi Activity Recognition Based on Bodymodel-Derived Primitives
LoCA '09 Proceedings of the 4th International Symposium on Location and Context Awareness
Escalation: complex event detection in wireless sensor networks
EuroSSC'07 Proceedings of the 2nd European conference on Smart sensing and context
Preprocessing techniques for context recognition from accelerometer data
Personal and Ubiquitous Computing
Cyclic and non-cyclic gesture spotting and classification in real-time applications
AMDO'10 Proceedings of the 6th international conference on Articulated motion and deformable objects
IEEE Transactions on Information Technology in Biomedicine - Special section on affective and pervasive computing for healthcare
Complex Event Detection in Extremely Resource-Constrained Wireless Sensor Networks
Mobile Networks and Applications
Improving the classification accuracy of streaming data using SAX similarity features
Pattern Recognition Letters
A bag-of-features-based framework for human activity representation and recognition
Proceedings of the 2011 international workshop on Situation activity & goal awareness
Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems
Motion primitive-based human activity recognition using a bag-of-features approach
Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium
Recognition of manual actions using vector quantization and dynamic time warping
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part I
Searching and mining trillions of time series subsequences under dynamic time warping
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
ACM Computing Surveys (CSUR)
Locally regularized sliced inverse regression based 3D hand gesture recognition on a dance robot
Information Sciences: an International Journal
Behavior-oriented data resource management in medical sensing systems
ACM Transactions on Sensor Networks (TOSN)
Complex activity recognition using context-driven activity theory and activity signatures
ACM Transactions on Computer-Human Interaction (TOCHI)
Pointing gesture recognition using compressed sensing for training data reduction
Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication
A tutorial on human activity recognition using body-worn inertial sensors
ACM Computing Surveys (CSUR)
ACM Transactions on Knowledge Discovery from Data (TKDD) - Special Issue on ACM SIGKDD 2012
Data mining a trillion time series subsequences under dynamic time warping
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Context awareness is one mechanism that allows wearable computers to provide information proactively, unobtrusively and with minimal user disturbance. Gestures and activities are an important aspect of the user's context. Detection and classification of gestures may be computationally expensive for low-power, miniaturized wearable platforms, such as those that may be integrated into garments. In this paper we introduce a novel method for online and real-time spotting and classification of gestures. Continuous user motion, acquired from a body-worn network of inertial sensors, is represented by strings of symbols encoding motion vectors. Fast string matching techniques, inspired from bioinformatics, spot trained gestures and classify them. Robustness to gesture variability is provided by approximate matching efficiently implemented through dynamic programming. Our method is successfully demonstrated by spotting and classifying the occurrences of trained gestures within a continuous recording of a complex bicycle maintenance task. It executes in real-time on a desktop computer with a fraction of CPU time. Only simple integer arithmetic operations are required, which makes this method ideally suited for implementation on body-worn sensor nodes and real-time operation.