Smart watches: A review of evolution in bio-medical sector
Smartwatch (SW) is a wearable gadget used in everyday life. It is equivalent to a customary
wristwatch and offers features similar to a smartphone. These features include access to the …
wristwatch and offers features similar to a smartphone. These features include access to the …
A federated learning and blockchain framework for physiological signal classification based on continual learning
A key challenge of physiological signal processing in the Internet of Medical Things is that
physiological signals usually have dynamic distribution changes. Another challenge is that …
physiological signals usually have dynamic distribution changes. Another challenge is that …
A scalable and transferable federated learning system for classifying healthcare sensor data
With the development of Internet of Medical Things, massive healthcare sensor data (HSD)
are transmitted in the Internet, which faces various security problems. Healthcare data are …
are transmitted in the Internet, which faces various security problems. Healthcare data are …
Anomaly detection in quasi-periodic time series based on automatic data segmentation and attentional LSTM-CNN
Quasi-periodic time series (QTS) exists widely in the real world, and it is important to detect
the anomalies of QTS. In this paper, we propose an a utomatic Q TS a nomaly d etection f …
the anomalies of QTS. In this paper, we propose an a utomatic Q TS a nomaly d etection f …
A novel deep learning architecture and MINIROCKET feature extraction method for human activity recognition using ECG, PPG and inertial sensor dataset
RK Bondugula, SK Udgata, KB Sivangi - Applied Intelligence, 2023 - Springer
The research in human activity recognition has gained prominence in various applications,
including healthcare, medical, and surveillance. The earlier popular techniques which relied …
including healthcare, medical, and surveillance. The earlier popular techniques which relied …
[HTML][HTML] Human activity recognition based on wrist PPG via the ensemble method
Human activity recognition via Electrocardiography (ECG) and Photoplethysmography
(PPG) is extensively researched. While ECG requires less filtering and is less prone to …
(PPG) is extensively researched. While ECG requires less filtering and is less prone to …
Exploring the Possibility of Photoplethysmography-Based Human Activity Recognition Using Convolutional Neural Networks
Various sensing modalities, including external and internal sensors, have been employed in
research on human activity recognition (HAR). Among these, internal sensors, particularly …
research on human activity recognition (HAR). Among these, internal sensors, particularly …
Behavior and task classification using wearable sensor data: A study across different ages
In this paper, we face the problem of task classification starting from physiological signals
acquired using wearable sensors with experiments in a controlled environment, designed to …
acquired using wearable sensors with experiments in a controlled environment, designed to …
An interpretable machine vision approach to human activity recognition using photoplethysmograph sensor data
The current gold standard for human activity recognition (HAR) is based on the use of
cameras. However, the poor scalability of camera systems renders them impractical in …
cameras. However, the poor scalability of camera systems renders them impractical in …
A deep learning architecture for human activity recognition using PPG and inertial sensor dataset
RK Bondugula, KB Sivangi, SK Udgata - Next Generation of Internet of …, 2022 - Springer
Human activity recognition helps identify the activity of a person based on data provided by
sensors. The wireless wearable sensors provide robust techniques for data collection and …
sensors. The wireless wearable sensors provide robust techniques for data collection and …