A Study on Hyperparameters Configurations for an Efficient Human Activity Recognition System

• Type: Article in International Conference Proceedings Book
• Date: 2023

Authors

Ferreira, PJS (Author) Other; João Mendes-Moreira (Author) FEUP; João M. P. Cardoso (Author) FEUP

Conference proceedings International

Title: PROCEEDINGS OF THE 8TH INTERNATIONAL WORKSHOP ON SENSOR-BASED ACTIVITY RECOGNITION AND ARTIFICIAL INTELLIGENCE, IWOAR 2023

Pages: 11:1-11:6

8th International Workshop on Sensor-Based Activity Recognition and Artificial Intelligence (IWOAR)

Lubeck, GERMANY, SEP 21-22, 2023

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 1 Citation

Other information

Authenticus ID: P-00Z-3F6

DOI: 10.1145/3615834.3615851

Abstract (EN): Human Activity Recognition (HAR) has been a popular research field due to the widespread of devices with sensors and computational power (e.g., smartphones and smartwatches). Applications for HAR systems have been extensively researched in recent literature, mainly due to the benefits of improving quality of life in areas like health and fitness monitoring. However, since persons have different motion patterns when performing physical activities, a HAR system would need to adapt to the characteristics of the user in order to maintain or improve accuracy. Mobile devices, such as smartphones, used to implement HAR systems, have limited resources (e.g., battery life). They also have difficulty adapting to the device's constraints to work efficiently for long periods. In this work, we present a kNN-based HAR system and an extensive study of the influence of hyperparameters (window size, overlap, distance function, and the value of k) and parameters (sampling frequency) on the system accuracy, energy consumption, and response time. We also study how hyperparameter configurations affect the model's performance for the users and the activities. Experimental results show that adapting the hyperparameters makes it possible to adjust the system's behavior to the user, the device, and the target service. These results motivate the development of a HAR system capable of automatically adapting the hyperparameters for the user, the device, and the service.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6