Title
Leveraging Wearable Sensors for Human Daily Activity Recognition with Stacked Denoising Autoencoders.
Abstract
Activity recognition has received considerable attention in many research fields, such as industrial and healthcare fields. However, many researches about activity recognition have focused on static activities and dynamic activities in current literature, while, the transitional activities, such as stand-to-sit and sit-to-stand, are more difficult to recognize than both of them. Consider that it may be important in real applications. Thus, a novel framework is proposed in this paper to recognize static activities, dynamic activities, and transitional activities by utilizing stacked denoising autoencoders (SDAE), which is able to extract features automatically as a deep learning model rather than utilize manual features extracted by conventional machine learning methods. Moreover, the resampling technique (random oversampling) is used to improve problem of unbalanced samples due to relatively short duration characteristic of transitional activity. The experiment protocol is designed to collect twelve daily activities (three types) by using wearable sensors from 10 adults in smart lab of Ulster University, the experiment results show the significant performance on transitional activity recognition and achieve the overall accuracy of 94.88% on three types of activities. The results obtained by comparing with other methods and performances on other three public datasets verify the feasibility and priority of our framework. This paper also explores the effect of multiple sensors (accelerometer and gyroscope) to determine the optimal combination for activity recognition.
Year
DOI
Venue
2020
10.3390/s20185114
SENSORS
Keywords
DocType
Volume
activity recognition,transitional activities,stacked denoising autoencoders,wearable sensors,resampling technique
Journal
20
Issue
ISSN
Citations 
18
1424-8220
1
PageRank 
References 
Authors
0.35
33
7
Name
Order
Citations
PageRank
Qin Ni111.36
Zhuo Fan210.35
Lei Zhang322.05
Chris D. Nugent41150128.39
Ian Cleland59823.12
Yuping Zhang611.03
Nan Zhou710.35