New Entropy Measures of Short Term Signals for Smart Wearable Devices
Grant number: DP190101248 | Funding period: 2019 - 2022
This project aims to improve reliability and accuracy of wearable devices by developing a new set of computationally efficient algorithms. Wearable devices can be very effective in remote and continuous monitoring to detect short or bursty anomalous events. Present devices are unable to detect such events effectively due to limited capability in processing short length signal. This project will provide computationally efficient algorithms for signal quality analysis and enhanced feature extraction methods in resource constrained wearable devices. This will improve the reliability and performance of wearable devices for adoption in intelligent decision-making systems.
Related publications (3)
Modified Distribution Entropy as a Complexity Measure of Heart Rate Variability (HRV) Signal
Radhagayathri Udhayakumar, Chandan Karmakar, Peng Li, Xinpei Wang, Marimuthu Palaniswami
The complexity of a heart rate variability (HRV) signal is considered an important nonlinear feature to detect cardiac abnormaliti..
Automated Scoring of Hemiparesis in Acute Stroke From Measures of Upper Limb Co-Ordination Using Wearable Accelerometry.
Shreyasi Datta, Chandan K Karmakar, Aravinda S Rao, Bernard Yan, Marimuthu Palaniswami
Stroke survivors usually experience paralysis in one half of the body, i.e., hemiparesis, and the upper limbs are severely affecte..