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نوره عبدالعزيز الحماد - Nora Alhammad

Lecturer

Information Technology Department

علوم الحاسب والمعلومات
Building 6 , Office T53 | noralhammad@ksu.edu.sa
publication
Journal Article
2021

Dynamic Segmentation for Physical Activity Recognition Using a Single Wearable Sensor

Al-Hammad, Nora . 2021

Data segmentation is an essential process in activity recognition when using machine learning techniques. Previous studies on physical activity recognition have mostly relied on the sliding window approach for segmentation. However, choosing a fixed window size for multiple activities with different durations may affect recognition accuracy, especially when the activities belong to the same category (i.e., dynamic or static). This paper presents and verifies a new method for dynamic segmentation of physical activities performed during the rehabilitation of individuals with spinal cord injuries. To adaptively segment the raw data, signal characteristics are analyzed to determine the suitable type of boundaries. Then, the algorithm identifies the time boundaries to represent the start- and endpoints of each activity. To verify the method and build a predictive model, an experiment was conducted in which data were collected using a single wrist-worn accelerometer sensor. The experimental results were compared with the sliding window approach, indicating that the proposed method outperformed the sliding window approach in terms of overall accuracy, which exceeded 5%, as well as model robustness. The results also demonstrated efficient physical activity segmentation using the proposed method, resulting in high classification performance for all activities considered.

Publication Work Type
PhD
Volume Number
11
Issue Number
6
Magazine \ Newspaper
Applied Sciences
more of publication
publications

Data segmentation is an essential process in activity recognition when using machine learning techniques. Previous studies on physical activity recognition have mostly relied on the sliding window…

by Nora Al-Hammad, Dr. Hmood Al-dossari
2021