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

S Zhang, Y Li, S Zhang, F Shahabi, S **a, 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 …

Human activity recognition using inertial, physiological and environmental sensors: A comprehensive survey

F Demrozi, G Pravadelli, A Bihorac, P Rashidi - IEEE access, 2020‏ - ieeexplore.ieee.org
In the last decade, Human Activity Recognition (HAR) has become a vibrant research area,
especially due to the spread of electronic devices such as smartphones, smartwatches and …

Wearable sensor-based human activity recognition with transformer model

I Dirgová Luptáková, M Kubovčík, J Pospíchal - Sensors, 2022‏ - mdpi.com
Computing devices that can recognize various human activities or movements can be used
to assist people in healthcare, sports, or human–robot interaction. Readily available data for …

Human activity recognition from sensor data using spatial attention-aided CNN with genetic algorithm

A Sarkar, SKS Hossain, R Sarkar - Neural Computing and Applications, 2023‏ - Springer
Capturing time and frequency relationships of time series signals offers an inherent barrier
for automatic human activity recognition (HAR) from wearable sensor data. Extracting …

A novel hybrid bidirectional unidirectional LSTM network for dynamic hand gesture recognition with leap motion

S Ameur, AB Khalifa, MS Bouhlel - Entertainment Computing, 2020‏ - Elsevier
Due to the recent development of machine learning and sensor innovations, hand gesture
recognition systems become promising for the digital entertainment field. In this paper, we …

Smart fusion of sensor data and human feedback for personalized energy-saving recommendations

I Varlamis, C Sardianos, C Chronis, G Dimitrakopoulos… - Applied Energy, 2022‏ - Elsevier
Despite the variety of sensors that can be used in a smart home or office setup, for
monitoring energy consumption and assisting users to save energy, their usefulness is …

Convae-lstm: Convolutional autoencoder long short-term memory network for smartphone-based human activity recognition

D Thakur, S Biswas, ESL Ho, S Chattopadhyay - IEEE Access, 2022‏ - ieeexplore.ieee.org
The self-regulated recognition of human activities from time-series smartphone sensor data
is a growing research area in smart and intelligent health care. Deep learning (DL) …

Human action recognition using deep learning methods on limited sensory data

N Tufek, M Yalcin, M Altintas, F Kalaoglu… - IEEE Sensors …, 2019‏ - ieeexplore.ieee.org
In recent years, due to the widespread usage of various sensors action recognition is
becoming more popular in many fields such as person surveillance, human-robot interaction …

Design and implementation of a convolutional neural network on an edge computing smartphone for human activity recognition

T Zebin, PJ Scully, N Peek, AJ Casson… - IEEE Access, 2019‏ - ieeexplore.ieee.org
Edge computing aims to integrate computing into everyday settings, enabling the system to
be context-aware and private to the user. With the increasing success and popularity of deep …

Recurrent neural network for human activity recognition in embedded systems using ppg and accelerometer data

M Alessandrini, G Biagetti, P Crippa, L Falaschetti… - Electronics, 2021‏ - mdpi.com
Photoplethysmography (PPG) is a common and practical technique to detect human activity
and other physiological parameters and is commonly implemented in wearable devices …