[HTML][HTML] Deep learning in human activity recognition with wearable sensors: A review on advances

S Zhang, Y Li, S Zhang, F Shahabi, S Xia, Y Deng… - Sensors, 2022 - mdpi.com
Mobile and wearable devices have enabled numerous applications, including activity
tracking, wellness monitoring, and human–computer interaction, that measure and improve …

Machine learning for microcontroller-class hardware: A review

SS Saha, SS Sandha, M Srivastava - IEEE Sensors Journal, 2022 - ieeexplore.ieee.org
The advancements in machine learning (ML) opened a new opportunity to bring intelligence
to the low-end Internet-of-Things (IoT) nodes, such as microcontrollers. Conventional ML …

A survey on unsupervised learning for wearable sensor-based activity recognition

AO Ige, MHM Noor - Applied Soft Computing, 2022 - Elsevier
Abstract Human Activity Recognition (HAR) is an essential task in various applications such
as pervasive healthcare, smart environment, and security and surveillance. The need to …

Tinyodom: Hardware-aware efficient neural inertial navigation

SS Saha, SS Sandha, LA Garcia… - Proceedings of the ACM …, 2022 - dl.acm.org
Deep inertial sequence learning has shown promising odometric resolution over model-
based approaches for trajectory estimation in GPS-denied environments. However, existing …

A deep local-temporal architecture with attention for lightweight human activity recognition

AO Ige, MHM Noor - Applied Soft Computing, 2023 - Elsevier
Abstract Human Activity Recognition (HAR) is an essential area of pervasive computing
deployed in numerous fields. In order to seamlessly capture human activities, various inertial …

UWHear: Through-wall extraction and separation of audio vibrations using wireless signals

Z Wang, Z Chen, AD Singh, L Garcia, J Luo… - Proceedings of the 18th …, 2020 - dl.acm.org
An ability to detect, classify, and locate complex acoustic events can be a powerful tool to
help smart systems build context-awareness, eg, to make rich inferences about human …

Auritus: An open-source optimization toolkit for training and development of human movement models and filters using earables

SS Saha, SS Sandha, S Pei, V Jain, Z Wang… - Proceedings of the …, 2022 - dl.acm.org
Smart ear-worn devices (called earables) are being equipped with various onboard sensors
and algorithms, transforming earphones from simple audio transducers to multi-modal …

Gene selection of microarray data using heatmap analysis and graph neural network

SK Pati, A Banerjee, S Manna - Applied Soft Computing, 2023 - Elsevier
It is not feasible to investigate the whole genes at a microscopic level for disease
classification in Genomics. It might take substantial time to execute any meaningful analysis …

Locomote: Ai-driven sensor tags for fine-grained undersea localization and sensing

SS Saha, C Davis, SS Sandha, J Park… - IEEE Sensors …, 2024 - ieeexplore.ieee.org
Long-term and fine-grained maritime localization and sensing are challenging due to
sporadic connectivity, constrained power budget, limited footprint, and hostile environment …

Summary of the Cooking Activity Recognition Challenge

SS Alia, P Lago, S Takeda, K Adachi… - Human Activity …, 2021 - Springer
Abstract Cooking Activity Recognition Challenge [1] is organized as a part of ABC2020 [2]. In
this work, we analyze and summarize the approaches of submissions of the Challenge. A …