With help from a 3D-camera Photon Sports has developed reliable and easy-to-use technology tomeasure and give feedback to athletes during performance tests. This technology makes it possibleto directly extract a number of parameters Key Performance Indicators (KPIs).In most field sports, multidirectional acceleration and deceleration are key areas to improveto become quicker as an athlete. However, it has become clear that only using the 3D-camera hassome limitations. This project aims to investigate if accelerometers can provide us with this extrainformation and thereby complement measurement technology to the measurements PhotonSports are doing today.We have done a three-part project where we first focused on time synchronization betweenclocks from the 3D-camera and the accelerometers. In the second part, we investigated how wellwe can extract the ground contact time (gct) during sprint using accelerometers attached to thefeet of the athlete. In the third and last part, we studied how we can combine both the 3D-cameraand the accelerometers to extract new KPIs that we were unable to extract before.From our developed time-synchronization algorithm, we found that the result is promisingif one looks at how the measured acceleration data from both devices are matching each othervisualy, however, it does not agree with the reference data we have extracted using a Software-Development-Kit (SDK) and Photon Sports already developed application. The gct was evaluatedto values in most cases either ranging between 100 ms and 200 ms or 300 ms and 400 ms. Whencomparing to earlier studies it seems like gct in the 100−200 ms interval are closer to the correctvalue whilst there has been some error in the calculations in the later interval. By combiningthe camera and the accelerometers we were able to extract leg stiffness and reactivity index as newKPIs. The KPIswere evaluated to a reasonable value, however, it became apparent both fromcalculationsof the newKPIs and the gct that the lowsampling rate of the camera and the accelerometersare an obstacle to reliably compute these parameters. We could therefor conclude that if PhotonSports want to introduce new tests where accelerometers are used they should be aware of the limitationsthat comes with i low sampling rate and be sure they try to compute KPIs that are possibleto evaluate with the sampling rate they have.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:umu-209827 |
| Date | January 2023 |
| Creators | Nilsson, Adam |
| Publisher | Umeå universitet, Institutionen för fysik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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