Article ; Online: Engineering Features from Raw Sensor Data to Analyse Player Movements during Competition.
2024 Volume 24, Issue 4
Abstract: Research in field sports often involves analysis of running performance profiles of players during competitive games with individual, per-position, and time-related descriptive statistics. Data are acquired through wearable technologies, which generally ... ...
Abstract | Research in field sports often involves analysis of running performance profiles of players during competitive games with individual, per-position, and time-related descriptive statistics. Data are acquired through wearable technologies, which generally capture simple data points, which in the case of many team-based sports are times, latitudes, and longitudes. While the data capture is simple and in relatively high volumes, the raw data are unsuited to any form of analysis or machine learning functions. The main goal of this research is to develop a multistep feature engineering framework that delivers the transformation of sequential data into feature sets more suited to machine learning applications. |
---|---|
MeSH term(s) | Movement ; Wearable Electronic Devices ; Running ; Team Sports ; Machine Learning |
Language | English |
Publishing date | 2024-02-18 |
Publishing country | Switzerland |
Document type | Journal Article |
ZDB-ID | 2052857-7 |
ISSN | 1424-8220 ; 1424-8220 |
ISSN (online) | 1424-8220 |
ISSN | 1424-8220 |
DOI | 10.3390/s24041308 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
More links
Kategorien
Order via subito
This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.