Wearable Wellness Monitoring Using ECG and Accelerometer Data
ISWC '05 Proceedings of the Ninth IEEE International Symposium on Wearable Computers
Ultra-low power data storage for sensor networks
Proceedings of the 5th international conference on Information processing in sensor networks
Computational Intelligence in Biomedical Engineering
Computational Intelligence in Biomedical Engineering
A fuzzy clustering neural network architecture for classification of ECG arrhythmias
Computers in Biology and Medicine
An integral approach to programming sensor networks
CCNC'09 Proceedings of the 6th IEEE Conference on Consumer Communications and Networking Conference
Wavelet-based low-delay ECG compression algorithm for continuous ECG transmission
IEEE Transactions on Information Technology in Biomedicine
A 36μW heartbeat-detection processor for a wireless sensor node
ACM Transactions on Design Automation of Electronic Systems (TODAES)
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Optimizing performance of wireless sensor networks leads to trade-offs between local computation and communication. With the usage of on-node processing, the lifetime of the sensor nodes can be extended as raw data does not need to be sent out and logged by an external device. In this paper we present our approach for on-node processing of ECG signals to signal abnormal heart rate conditions. We develop an algorithm that is significantly simpler than traditional approaches but has similar quality and that can run on sensors with very limited resources. We give results of our approach when applied to reference sequences. We also estimate the amount of information that gets transmitted over the wireless link in case of applying the on-node processing algorithm and compare it with the remote logging case. We propose fusing movement information with ECG data to provide a more accurate assessment of the patients current health.