R
Ranadeep Deb
Researcher at Arizona State University
Publications - 5
Citations - 124
Ranadeep Deb is an academic researcher from Arizona State University. The author has contributed to research in topics: Wearable technology & Activity recognition. The author has an hindex of 3, co-authored 4 publications receiving 70 citations.
Papers
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Proceedings ArticleDOI
Online human activity recognition using low-power wearable devices
TL;DR: In this article, a neural network classifier was proposed for human activity recognition using the fast Fourier and discrete wavelet transforms of a textile-based stretch sensor and accelerometer data.
Journal ArticleDOI
OpenHealth: Open-Source Platform for Wearable Health Monitoring
TL;DR: An open-source platform for wearable health monitoring that can enable autonomous collection of clinically relevant data is presented and reference implementations of human activity and gesture recognition applications within this platform are provided.
Proceedings ArticleDOI
Online Human Activity Recognition using Low-Power Wearable Devices
TL;DR: This paper presents the first HAR framework that can perform both online training and inference, and starts with a novel technique that generates features using the fast Fourier and discrete wavelet transforms of a textile-based stretch sensor and accelerometer data.
Journal ArticleDOI
A Systematic Survey of Research Trends in Technology Usage for Parkinson’s Disease
TL;DR: There is a substantial and steady growth in the use of mobileTechnology in the PD contexts, particularly in the last four years of the period under study, which reflects the research community's growing interest in assessing PD with wearable devices.
Posted Content
OpenHealth: Open Source Platform for Wearable Health Monitoring
TL;DR: OpenHealth as discussed by the authors is an open source platform for wearable health monitoring, which includes a wearable device, standard software interfaces and reference implementations of human activity and gesture recognition applications, and can enable autonomous collection of clinically relevant data.