Analyzing the Effectiveness and Contribution of Each Axis of Tri-Axial Accelerometer Sensor for Accurate Activity Recognition Article Swipe
Abdul Rehman Javed
,
Muhammad Usman Sarwar
,
Suleman Khan
,
Celestine Iwendi
,
Mohit Mittal
,
Neeraj Kumar
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.3390/s20082216
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.3390/s20082216
Recognizing human physical activities from streaming smartphone sensor readings is essential for the successful realization of a smart environment. Physical activity recognition is one of the active research topics to provide users the adaptive services using smart devices. Existing physical activity recognition methods lack in providing fast and accurate recognition of activities. This paper proposes an approach to recognize physical activities using only2-axes of the smartphone accelerometer sensor. It also investigates the effectiveness and contribution of each axis of the accelerometer in the recognition of physical activities. To implement our approach, data of daily life activities are collected labeled using the accelerometer from 12 participants. Furthermore, three machine learning classifiers are implemented to train the model on the collected dataset and in predicting the activities. Our proposed approach provides more promising results compared to the existing techniques and presents a strong rationale behind the effectiveness and contribution of each axis of an accelerometer for activity recognition. To ensure the reliability of the model, we evaluate the proposed approach and observations on standard publicly available dataset WISDM also and provide a comparative analysis with state-of-the-art studies. The proposed approach achieved 93% weighted accuracy with Multilayer Perceptron (MLP) classifier, which is almost 13% higher than the existing methods.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/s20082216
- https://www.mdpi.com/1424-8220/20/8/2216/pdf
- OA Status
- gold
- Cited By
- 110
- References
- 54
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3016422726
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3016422726Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/s20082216Digital Object Identifier
- Title
-
Analyzing the Effectiveness and Contribution of Each Axis of Tri-Axial Accelerometer Sensor for Accurate Activity RecognitionWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-04-14Full publication date if available
- Authors
-
Abdul Rehman Javed, Muhammad Usman Sarwar, Suleman Khan, Celestine Iwendi, Mohit Mittal, Neeraj KumarList of authors in order
- Landing page
-
https://doi.org/10.3390/s20082216Publisher landing page
- PDF URL
-
https://www.mdpi.com/1424-8220/20/8/2216/pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/1424-8220/20/8/2216/pdfDirect OA link when available
- Concepts
-
Accelerometer, Activity recognition, Computer science, Machine learning, Classifier (UML), Artificial intelligence, Multilayer perceptron, Artificial neural network, Data mining, Human–computer interaction, Operating systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
110Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 4, 2024: 10, 2023: 24, 2022: 40, 2021: 21Per-year citation counts (last 5 years)
- References (count)
-
54Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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