Automatic temporal event detection of the Ollie movement during skateboarding using wearable IMUs

ABSTRACT

The Ollie movement is about the most dangerous fundamental skateboarding skill. This study proposed a peak heuristic algorithm to detect the key temporal events of the Ollie movement during skateboarding using IMUs. The proposed algorithm was used to detect four key temporal events including take-off (TO), peak flight height (HP), front wheel landing (FL), and back wheel landing (RL). Based on these temporal events, three temporal phases including ascending, descending, and flight were identified. The results showed that our proposed method could help accurately identify these key temporal events and phases. Knowledge of the temporal information about the Ollie movement could provide a basis for quantitative assessment of riders’ performance and injury risks. Practically, this proposed algorithm can benefit the outdoor injury risk monitoring of the skateboarding movement.

KEYWORDS:

• Ollie movement
• skateboarding
• temporal event detection
• wearable IMUs

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available from the corresponding author XQ at [email protected] upon reasonable request.

Additional information

Funding

This work was supported in part by the Natural Science Foundation of China [11702175, 32171306, 31570944], the Natural Science Foundation of Guangdong Province [2016A030310068], and Shenzhen Peacock Program.