The best paper award at ICCE 2020

I received the Best Paper Award at the International Conference on Consumer Electronics 2020 (ICCE 2020), held by the Institute of Electrical and Electronics Engineers (IEEE), in the United States of America. The ICCE conference is an academic event that is organized by the IEEE organization and held at the same time as the Consumer Electronics Show (CES), an annual trade show displaying the best electronic products from around the world.

The award-winning research paper presented at ICCE 2020 was on “IMU-based Spectrogram Approach with Deep Convolutional Neural Networks for Gait Classification.” This study utilized inertial measurement units (IMU) that were attached to the body and deep learning technology to analyze gait signals, categorizing them into the following three groups: normal, abnormal, and athlete.

Observing gait is a fundamental method used to monitor an individual’s health, and this method is often used in hospitals through gait tests to assess the health of patients. The results of this study propose new technologies that can categorize different types of gait based on their characteristics, thus facilitating for more simplified and more accurate health assessments.