# Automatic sensor-based detection and classification of climbing activities

arXiv: https://arxiv.org/abs/1508.04153 · HTML: https://mlsanity.com/paper/1508.04153/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Jun 2015.

## Built on by (most cited first, 4 of 4)

- [Climbing Routes Clustering Using Energy-Efficient Accelerometers Attached to the Quickdraws](https://mlsanity.com/paper/2211.02680/) (2022)
- [The Way Up: A Dataset for Hold Usage Detection in Sport Climbing](https://mlsanity.com/paper/2505.12854/) (2025)
- [Lowering Detection in Sport Climbing Based on Orientation of the Sensor Enhanced Quickdraw](https://mlsanity.com/paper/2301.10164/) (2023)
- [Training-Free Hold-Usage Detection in Sport Climbing with Foundation Pose Models](https://mlsanity.com/paper/2609.30026/) (2026)

## Abstract (arXiv)

This article presents a method to automatically detect and classify climbing activities using inertial measurement units (IMUs) attached to the wrists, feet and pelvis of the climber. The IMUs record limb acceleration and angular velocity. Detection requires a learning phase with manual annotation to construct the statistical models used in the cusum algorithm. Full-body activity is then classified based on the detection of each IMU.