Preliminary study: IMU system validation for real-time feedback on swimming technique - Tolza, X.; Soto-Romero, G.; Fourniols, J. Y.; Acco, P. (Computer Methods in Biomechanics and Biomedical Engineering, 2017)
The use of Inertial Measurement Units (IMU) for sport performance monitoring has grown in the previous decade due to its ease of use and the growth of private market applications. In swimming monitoring, it has been highlighted (Dadashi et al. 2012; Callaway et al. 2015) that measuring performance with traditional 2D and 3D video-based systems have many downsides (light refraction, bubbles, time-consuming). Other alternative methods are also mentioned such as speed measurement using a tighten cord, but they disturb the swimmer`s technique and only provides feedback on the forward speed. The main problem of those solutions is that the data must be post processed and they do not provide an instant feedback to the swimmer. In this context, IMUs appear to be a low-cost solution, easy to use and not interfering with the swimmer`s technique, even if its data analysis requires a complex data mining process. Such real-time feedback for gesture and sport training is a solution that has been used many times: for instance karate training (Takahata et al. 2004), and various other sports (Spelmezan et al. 2008; Drobny et al. 2009). It has been shown (Zatoñ et al. 2014) that an immediate feedback can improve swimming technique. Measuring the performance is something much in demand for sportsmen to be able to keep track of their progress. For swimming, the most common performance criterion tends to be stroke length, stroke count and lap count (Dadashi et al. 2012), which are often summarized by coaches as the `Swim Golf ` (SWOLF) criteria (Perego et al. 2015). Those have been used in several scientific publications as references of the swimmer`s level (Peregoet al. 2015; Lemkaddem et al. 2016), but it also has been shown (Cardelli et al. 2000) that there is a significant correlation between the breathing characteristics and the swimmer`s skills plus the stroke characteristics. From this statement we wanted to validate an IMU devices mounted on the head of a swimmer to measure its breathing characteristics, and experiment on an instant feedback to correct those movements. The tested device is a Swimbot (Meudon, France), based on Newton 2 smart watch core (Ingenic, Beijing) including a 1.2 GhZ M200 CPU running a custom Android 5.1 with a 16 bits 9 axis IMU (MPU-9250 (InvenSense, San Jose, California) embedded, using the Android sensors fusion algorithm to provide a rotation quaternion at a sampling rate of 50 Hz. The other data provided are: accelerometer, magnetometer and gyroscope and two software sensors provided by Android: linear acceleration (without the gravity) and quaternion orientation. The device is placed under the swimming cap at the back of the head and also includes two bone conduction headphones placed just behind the ears for instant feedback under water, with an on-board memory of 2 Gb of data to store logs and data.