Deep Activity Recognition Models with Triaxial Accelerometers

11/15/2015
by   Mohammad Abu Alsheikh, et al.
0

Despite the widespread installation of accelerometers in almost all mobile phones and wearable devices, activity recognition using accelerometers is still immature due to the poor recognition accuracy of existing recognition methods and the scarcity of labeled training data. We consider the problem of human activity recognition using triaxial accelerometers and deep learning paradigms. This paper shows that deep activity recognition models (a) provide better recognition accuracy of human activities, (b) avoid the expensive design of handcrafted features in existing systems, and (c) utilize the massive unlabeled acceleration samples for unsupervised feature extraction. Moreover, a hybrid approach of deep learning and hidden Markov models (DL-HMM) is presented for sequential activity recognition. This hybrid approach integrates the hierarchical representations of deep activity recognition models with the stochastic modeling of temporal sequences in the hidden Markov models. We show substantial recognition improvement on real world datasets over state-of-the-art methods of human activity recognition using triaxial accelerometers.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
10/04/2018

Activity Recognition using Hierarchical Hidden Markov Models on Streaming Sensor Data

Activity recognition from sensor data deals with various challenges, suc...
research
10/13/2021

Tutorial on Deep Learning for Human Activity Recognition

Activity recognition systems that are capable of estimating human activi...
research
01/25/2018

Personalized Human Activity Recognition Using Convolutional Neural Networks

A major barrier to the personalized Human Activity Recognition using wea...
research
02/02/2018

Learning Attribute Representation for Human Activity Recognition

Attribute representations became relevant in image recognition and word ...
research
10/11/2022

Joint Human Orientation-Activity Recognition Using WiFi Signals for Human-Machine Interaction

WiFi sensing is an important part of the new WiFi 802.11bf standard, whi...
research
04/29/2016

Deep, Convolutional, and Recurrent Models for Human Activity Recognition using Wearables

Human activity recognition (HAR) in ubiquitous computing is beginning to...
research
12/20/2021

Attention-Based Sensor Fusion for Human Activity Recognition Using IMU Signals

Human Activity Recognition (HAR) using wearable devices such as smart wa...

Please sign up or login with your details

Forgot password? Click here to reset