ArticleSensors (Basel, Switzerland)2023
Hang-Time HAR: A Benchmark Dataset for Basketball Activity Recognition Using Wrist-Worn Inertial Sensors.
Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- DaRA Dataset: Combining Wearable Sensors, Location Tracking, and Process Knowledge for Enhanced Human Activity and Human Context Recognition in Warehousing.Sensors (Basel, Switzerland) · 2026Article
- Towards Practical, Best Practice Video Annotation to Support Human Activity Recognition.Annotation of real-world data for artificial intelligence systems : 9th international workshop, ARDUOUS 2025, Bologna Italy, October 25-26, 2025, proceedings. International Workshop on Annotation of Real-World Data for Artificial Intell... · 2026Article
- Enhancing psychological resilience and decision-making in basketball players through emerging technologies.Scientific reports · 2025Article
- Human Activity Recognition via Attention-Augmented TCN-BiGRU Fusion.Sensors (Basel, Switzerland) · 2025Article
- Sensor-Driven Real-Time Recognition of Basketball Goal States Using IMU and Deep Learning.Sensors (Basel, Switzerland) · 2025Article
- Action Recognition in Basketball with Inertial Measurement Unit-Supported Vest.Sensors (Basel, Switzerland) · 2025Article
- A two-phase hybrid clustering framework exploring transitional activities in HAR.Discover artificial intelligence · 2025Article
- MS-TCRNet: Multi-Stage Temporal Convolutional Recurrent Networks for Action Segmentation Using Sensor-Augmented Kinematics.Pattern recognition · 2024Article
- CAPTURE-24: A large dataset of wrist-worn activity tracker data collected in the wild for human activity recognition.Scientific data · 2024Article
- Robust Feature Representation Using Multi-Task Learning for Human Activity Recognition.Sensors (Basel, Switzerland) · 2024Article
- Recognition of sports and daily activities through deep learning and convolutional block attention.PeerJ. Computer science · 2024Article
- Deep Wavelet Convolutional Neural Networks for Multimodal Human Activity Recognition Using Wearable Inertial Sensors.Sensors (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
We present a benchmark dataset for evaluating physical human activity recognition methods from wrist-worn sensors, for the specific setting of basketball training, drills, and games. Basketball activities lend themselves well for measurement by wrist-worn inertial sensors, and systems that are able to detect such sport-relevant activities could be used in applications of game analysis, guided training, and personal physical activity tracking. The dataset was recorded from two teams in separate countries (USA and Germany) with a total of 24 players who wore an inertial sensor on their wrist, during both a repetitive basketball training session and a game. Particular features of this dataset include an inherent variance through cultural differences in game rules and styles as the data was recorded in two countries, as well as different sport skill levels since the participants were heterogeneous in terms of prior basketball experience. We illustrate the dataset's features in several time-series analyses and report on a baseline classification performance study with two state-of-the-art deep learning architectures.
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