New Movesense Academic Program Projects Study Training Load and Develop a New Training Analysis Software
Movesense Academic Program is an initiative by the Movesense team and Movesense development partner Kaasa Solution to support scientific research with expert tools for collecting movement, heart rate and ECG data.
Two new projects were invited to Movesense Academic Program during the last quarter of 2021. In addition, we are discussing with a few very interesting projects that submitted their applications recently.
While previous projects announced in August concerned health, the latest research projects are related to sports:
Wearable sensor technology to monitor training load, prevent injury and improve health in high-performance athletes
Technion – Israel Institute of Technology, Haifa, Israel
Monitoring training and match load is a critical issue in elite-level sports training and research, and is particularly important for assessing and periodizing the physical exertion of training. Utilizing scientific principles to monitor load and the overall health of the athlete can be an important means of reducing the risk of overload, fatigue, and injury.
However, despite the increase in research in high performance sports and the scientific approach to load monitoring, there is no obvious solution to defining training load accurately and reliably. The term training load is widely used in sports science, but its definition and monitoring methods are inconsistent.
This study aims to combine the biomechanical and physiological parameters of an athlete to monitor training load. Load data is measured with 9-axis movement sensors, ECG, HR, and daily subjective reports of elite athletes’ levels of well-being including sleep, stress, injury, illness, and pain. Movesense sensors will be an essential tool for collecting athlete data during the project.
In addition, the team lead by assistant professor Arielle Fischer plans to use wearable motion capture and analysis to develop predictive algorithms to quantify reaction forces and loads that previously could only be measured in a laboratory setting using force plates.
By aggregating the data, the team intends to build an athlete-specific profile and provide a holistic view that enables better well-being, prevents injuries, and improves athlete performance.
Behavior and sports analysis on mixed methods
INEFC and University of Lleida, Spain
LINCE PLUS is an open source visualization tool for systematic observational studies in sports and health, developed in cooperation of University of Lleida and INEFC (National Institute of Physical Education of Catalonia) to address the lack of such tools for scientific research.
Lince Plus incorporates a series of characteristics that allow for collaboration and management of the observational research process, optimized for behavioral video analysis. The tool allows the integration of video recordings and selective sensor data, and the analysis of the behavior of subjects on any cinematic action.
Coordinated by Dr. Alberto Soto Fernández, the this project continues to develop the Lince Plus web application. The project is integrating quantitative data and qualitative data into a mix-methods research approach. Movesense is the first sensor to be integrated to the solution and will be the base for the cloud dimension of Lince Plus.
The featured image is showing Lince Plus in actual data collecting situation.
Learn more about Lince Plus in this research article.
